id
stringlengths 7
10
| image
imagewidth (px) 4
733
| query
stringclasses 1
value | answers
stringlengths 7
66.1k
|
|---|---|---|---|
train_0 | What is described in this image? | Fig. 4 shows the TGA thermograms of P-CNT, A-CNT, and D-CNT Fig. 4. TGA thermograms of CNT samples. |
|
train_1 | What is described in this image? | Both XRD patterns (Fig. 1) and IR spectrum (Fig. 2) (Fig. 2). IR bands at 3573 and 632 cm-1 were assigned to OH stretching and librational modes, respectively, and the bands at 1090 and 1048, 963, and 602 and Fig. 2. IR spectrum of stoichiometric (Ca/P = 5/3) HAp powder. |
|
train_2 | What is described in this image? | Chitosan, a partially deacetylated derivative of chitin, is a linear polysaccharide consisting of ß (1,4)-linked D-glucosamine residues (deacetylated unit) with a variable number of randomly located N-acetyl-glucosamine groups (acetylated unit) (Figure 1). As one of the most abundant natural biopolymers on earth, it is extensively used for food packaging, biosensors, water treatment, and drug delivery [15]. It has been reported that chitosan-based biomaterials could promote chondrogenesis [16]. Figure 1 The structure of partially deacetylated chitosan. DA means a copolymer characterized by its average degree of deacetylation |
|
train_3 | What is described in this image? | The cross-sectional morphologies of these two samples are shown in Figs. 18 and 19. Fig. 18 shows a homogeneous morphology of the PEBAX® MH 1657 nanocomposite membrane, while Fig. 19 shows an inhomogeneous structure with ellipsoidal inclusions for the PEBAX® 2533 nanocomposite membrane. These inclusions are located all over the cross section of the membrane, and they are larger and more numerous versus the top of the membrane. They are a result of the poor miscibility of PEG-POSS with the poly (tetramethylene oxide) domains, what will become more evident from the elemental mapping figures shown in Fig. 21. 2533 nanocomposite membrane is shown in Fig. 21. The elemental maps reveal two clearly separated areas of PEBAX® 2533 and PEG- |
|
train_4 | What is described in this image? | Based on the diffractograms presented in Fig. 5 (A), it can be suggested that loratadine is present in its crystalline form since it exhibits several well defined peaks at a diffractogram angle of 20. This phenomenon was also observed by Skapin and Matijevic (25), when studying the preparation of colloidal particles of loratadine. Consistent with findings reported in other papers concerning the use of PVP K30 as a carrier in solid dispersions, the XRD pattern of Fig. 5 (B) showed no detection of any prominent peak pertaining to the polymer, a characteristic of amorphous state [14,26,27]. Based on the diffractograms presented in Fig. 5 (A), it can be suggested that loratadine is present in its crystalline form since it exhibits several well defined peaks at a diffractogram angle of 20. This phenomenon was also observed by Skapin and Matijevic (25), when studying the preparation of colloidal particles of loratadine. Consistent with findings reported in other papers concerning the use of PVP K30 as a carrier in solid dispersions, the XRD pattern of Fig. 5 (B) showed no detection of any prominent peak pertaining to the polymer, a characteristic of amorphous state [14,26,27]. The diffraction patterns of the physical mixtures, demonstrated in Fig. 5 (C), revealed overlapping peaks for the drug and the polymer, thus indicating that in the physical mixtures loratadine was maintained in its crystalline state. Conversely, an absence of XRD peaks was observed in solid dispersions produced by either the rotary evaporation (D) or the spray-drying (E) methods. These results indicated, in accordance with DSC observations, that loratadine was no longer present in its crystalline form in the solid dispersions but existed in the amorphous state. One of the major drawbacks encountered in solid dispersions is the physicochemical instability, because the drug can recrystallize upon storage. To address to this issue, we carried out XRD experiments to evaluate the solid dispersions stored at room temperature after 6 months. Results present in Fig. 5 (G and F) show that the drug remained amorphous which is an indication of the stability of the products, a finding generally achieved with solid dispersions prepared with PVP. |
|
train_5 | What is described in this image? | Figure 220 kJ mol -1, A = 1015 min-1. 1 to 9: models F1, A2, A3, R2, R3, D2, D3 and D4, respectively. (With the permission of Wiley-Heyden Ltd.) |
|
train_6 | What is described in this image? | Fig. 8 illustrates the TGA thermograms of microcapsule samples, which well describe the thermal stabilities of the microcapsules. As shown in Fig. 8, pure n-eicosane exhibits a typical one-step thermal degradation behavior and suffers a rapid weight loss in the range of 172–210 °C due to the major pyrolysis of linear alkane chains. It almost decomposed completely after 230 °C and no char remained at temperatures in excess of 550 ℃. The characteristic temperature (Tmax) corresponding to the weight loss occurred at a maximum rate is usually considered as an indicator for the thermal stability of a material. As shown in Fig. 8b, the DTG curve reveals that pure n-eicosane has a Tmax of 208.3 ℃, indicating a low level of thermal stability for this organic PCM. Similar to pure n-eicosane, three microcapsule samples all present a one-stage thermal decomposition, and however, their Tmax's are improved significantly at least by 50 ℃. Such an improvement in Tmax is attributed to the encapsulation of a compact and rigid ZnO shell, which prevents the n-eicosane core from decomposing and thus improves its thermal stability. It is noteworthy in Fig. 8b that the Tmax increases slightly with decreasing the weight ratio of neicosane/Zn(CH3COO)2-2H2O, indicating that a thicker shell can lead to a higher thermal stability for the resulting microcapsules. Fig. 8 illustrates the TGA thermograms of microcapsule samples, which well describe the thermal stabilities of the microcapsules. As shown in Fig. 8, pure n-eicosane exhibits a typical one-step thermal degradation behavior and suffers a rapid weight loss in the range of 172–210 °C due to the major pyrolysis of linear alkane chains. It almost decomposed completely after 230 °C and no char remained at temperatures in excess of 550 ℃. The characteristic temperature (Tmax) corresponding to the weight loss occurred at a maximum rate is usually considered as an indicator for the thermal stability of a material. As shown in Fig. 8b, the DTG curve reveals that pure n-eicosane has a Tmax of 208.3 ℃, indicating a low level of thermal stability for this organic PCM. Similar to pure n-eicosane, three microcapsule samples all present a one-stage thermal decomposition, and however, their Tmax's are improved significantly at least by 50 ℃. Such an improvement in Tmax is attributed to the encapsulation of a compact and rigid ZnO shell, which prevents the n-eicosane core from decomposing and thus improves its thermal stability. It is noteworthy in Fig. 8b that the Tmax increases slightly with decreasing the weight ratio of neicosane/Zn(CH3COO)2-2H2O, indicating that a thicker shell can lead to a higher thermal stability for the resulting microcapsules. Fig. 8 illustrates the TGA thermograms of microcapsule samples, which well describe the thermal stabilities of the microcapsules. As shown in Fig. 8, pure n-eicosane exhibits a typical one-step thermal degradation behavior and suffers a rapid weight loss in the range of 172–210 °C due to the major pyrolysis of linear alkane chains. It almost decomposed completely after 230 °C and no char remained at temperatures in excess of 550 ℃. The characteristic temperature (Tmax) corresponding to the weight loss occurred at a maximum rate is usually considered as an indicator for the thermal stability of a material. As shown in Fig. 8b, the DTG curve reveals that pure n-eicosane has a Tmax of 208.3 ℃, indicating a low level of thermal stability for this organic PCM. Similar to pure n-eicosane, three microcapsule samples all present a one-stage thermal decomposition, and however, their Tmax's are improved significantly at least by 50 ℃. Such an improvement in Tmax is attributed to the encapsulation of a compact and rigid ZnO shell, which prevents the n-eicosane core from decomposing and thus improves its thermal stability. It is noteworthy in Fig. 8b that the Tmax increases slightly with decreasing the weight ratio of neicosane/Zn(CH3COO)2-2H2O, indicating that a thicker shell can lead to a higher thermal stability for the resulting microcapsules. Fig. 8 illustrates the TGA thermograms of microcapsule samples, which well describe the thermal stabilities of the microcapsules. As shown in Fig. 8, pure n-eicosane exhibits a typical one-step thermal degradation behavior and suffers a rapid weight loss in the range of 172–210 °C due to the major pyrolysis of linear alkane chains. It almost decomposed completely after 230 °C and no char remained at temperatures in excess of 550 ℃. The characteristic temperature (Tmax) corresponding to the weight loss occurred at a maximum rate is usually considered as an indicator for the thermal stability of a material. As shown in Fig. 8b, the DTG curve reveals that pure n-eicosane has a Tmax of 208.3 ℃, indicating a low level of thermal stability for this organic PCM. Similar to pure n-eicosane, three microcapsule samples all present a one-stage thermal decomposition, and however, their Tmax's are improved significantly at least by 50 ℃. Such an improvement in Tmax is attributed to the encapsulation of a compact and rigid ZnO shell, which prevents the n-eicosane core from decomposing and thus improves its thermal stability. It is noteworthy in Fig. 8b that the Tmax increases slightly with decreasing the weight ratio of neicosane/Zn(CH3COO)2-2H2O, indicating that a thicker shell can lead to a higher thermal stability for the resulting microcapsules. |
|
train_7 | What is described in this image? | Fig. 6. FT-IR spectra of paraffin, HDPE, SEBS and SEBS/paraffin/HDPE (1:6:0.5). HDPE (1:6:0.5) are shown in Fig. 6. As it can be seen, paraffin, HDPE and SEBS/paraffin/HDPE (1:6:0.5) have three identical characteristic absorption peaks: stretching vibration absorption peaks of -CH2 at around 2918 cm-1 and 2849 cm-1, -CH2 and |
|
train_8 | What is described in this image? | The precursor of this Ca-rich phase was partially crystallized after the decomposition of the nitrates by calcination at 600℃ for 30 min (Fig. 8). The crystalline phase detected by XRD is CaO. The DSC curve displays a weak exothermic event at about 880°C. After heating to 930°C, the major phases evidenced by XRD are CaO, C5A3, and C12A7. At 1100°C, C3A is the major phase with remaining C12A7 and a trace of CaO. At 1230℃ pure C3A is obtained. XRD diagrams of the spray-dried sample having the bulk Fig. 8. XRD diagrams of powders b and c (see Fig. 8) having the CaO |
|
train_9 | What is described in this image? | The IR spectra of the present glass system are shown in Fig. 3. The spectra consist of strong absorption bands at 640-675, 926-935, 1236-1256, and 1342-1406 cm-1 and weak bands at 420-490, 766–783, 1100 and 1544–1748 cm–1. The observed IR bands are given in Table 2 and the band assignments are given in Table 3. The band around 640 cm-1 is due to the stretching vibrations of Te-O in TeO4 trigonal bipyramidal (tbp) units [13]. It is observed from Fig. 3 that the band at 640 cm-1 is shifting to 675 cm-1 as ZnO content is increased from 0 to 30 mol% at the expense of TeO2 and B2O3. The intensity and the broadness of 640 cm - 1 band decreased while the intensity of band at 675 cm-1 increases with ZnO content. This observation suggests that the higher coordination [TeO4] units transformed into the lower coordination (TeO3) units with the addition of ZnO content. The weak band around (766–783) cm¯1 is ascribed to the stretching vibrations of Te–Oecq of distorted TeO4 units [13]. The band around 926 cm¯1 is ascribed to the B-O stretching vibrations of BO4 units. The intensity of the band at 926 cm¯¹ is found to decrease and also shifts to 935 cm¯¹ The IR spectra of the present glass system are shown in Fig. 3. The spectra consist of strong absorption bands at 640-675, 926-935, 1236-1256, and 1342-1406 cm-1 and weak bands at 420-490, 766–783, 1100 and 1544–1748 cm–1. The observed IR bands are given in Table 2 and the band assignments are given in Table 3. The band around 640 cm-1 is due to the stretching vibrations of Te-O in TeO4 trigonal bipyramidal (tbp) units [13]. It is observed from Fig. 3 that the band at 640 cm-1 is shifting to 675 cm-1 as ZnO content is increased from 0 to 30 mol% at the expense of TeO2 and B2O3. The intensity and the broadness of 640 cm - 1 band decreased while the intensity of band at 675 cm-1 increases with ZnO content. This observation suggests that the higher coordination [TeO4] units transformed into the lower coordination (TeO3) units with the addition of ZnO content. The weak band around (766–783) cm¯1 is ascribed to the stretching vibrations of Te–Oecq of distorted TeO4 units [13]. The band around 926 cm¯1 is ascribed to the B-O stretching vibrations of BO4 units. The intensity of the band at 926 cm¯¹ is found to decrease and also shifts to 935 cm¯¹ Fig. 3. FTIR spectra of TeO2-B2O3-ZnO-V2Os glasses. |
|
train_10 | What is described in this image? | Fig. 4a shows a DSC plot for mannitol, showing an endothermic peak at 167 °C, with the onset of the melting at approximately 160 ℃. This corresponds well to the value of 166-168 ℃ given by the Merck Index (Budavari). Fig. 4b ~ 172 and ~ 187 ℃. The DSC in Fig. 4a shows endothermic peaks at ~ 175 ℃ and ~ 200 ℃, |
|
train_11 | What is described in this image? | Fig. 5. POM images of green WPUs. Fig. 5 exhibits the POM images of crystals of green WPUs with a magnification of 25 times. As is presented obviously in Fig. 5, crystals of green WPUs become smaller and their numbers reduce from WPU-I to WPU-VI. As the phase separation degree increases form WPU-I to WPU-VI, more and larger hard domains form in the polymer matrix, which restrict the crystallization and compress the volume and number of crystals of soft segments. 3.5. Schematic illustration of the relation between phase separation and crystallization Based on the above discussion, it's believed that the increase of phase separation degree leads to the decrease of crystallization capacity of soft segments of green WPUs. Crystallization of soft segments of green WPUs under different phase separation degree is illustrated in Fig. 6. As mentioned before, phase separation of PUs is the result of aggregation of hard segments. When the phase separation degree is low, hard segments disperse in soft phase, showing little effect on the crystallization of soft segments. The crystallization of soft segments is similar to that of the long-chain diols which comprise soft segments, giving rise to high crystallinity and big crystals. When the phase separation degree is high, hard domains can "pull" and/or "push" soft segments, then destroy the ordered arrangement of long-chain diols, and confine the crystallization ability of soft segments, resulting in low crystallinity and small crystals. Fig. 5 exhibits the POM images of crystals of green WPUs with a magnification of 25 times. As is presented obviously in Fig. 5, crystals of green WPUs become smaller and their numbers reduce from WPU-I to WPU-VI. As the phase separation degree increases form WPU-I to WPU-VI, more and larger hard domains form in the polymer matrix, which restrict the crystallization and compress the volume and number of crystals of soft segments. 3.5. Schematic illustration of the relation between phase separation and crystallization Based on the above discussion, it's believed that the increase of phase separation degree leads to the decrease of crystallization capacity of soft segments of green WPUs. Crystallization of soft segments of green WPUs under different phase separation degree is illustrated in Fig. 6. As mentioned before, phase separation of PUs is the result of aggregation of hard segments. When the phase separation degree is low, hard segments disperse in soft phase, showing little effect on the crystallization of soft segments. The crystallization of soft segments is similar to that of the long-chain diols which comprise soft segments, giving rise to high crystallinity and big crystals. When the phase separation degree is high, hard domains can "pull" and/or "push" soft segments, then destroy the ordered arrangement of long-chain diols, and confine the crystallization ability of soft segments, resulting in low crystallinity and small crystals. |
|
train_12 | What is described in this image? | (Scheme 2). The structure of HODEAz (8) was confirmed by FTIR and 13C NMR spectroscopy. The FTIR spectrum shows a strong absorption band at 2133 cm-1 due to asymmetric stretching vibration of azide group (N3) and also a shift of the carbonyl group band from 1707 to 1720 cm-1 due to the formation of a more electron withdrawing azide group (Figure 3). In addition, a band due to the C=C-H stretching vibration appeared at 3008 cm-1. In the 1H NMR spectrum of HODEAz (8), a triplet peak of the methylene group attached to an azide group (CH2-CON3) appears at 2.31 ppm and vinylic protons (CH=CH) appear at 5.2-5.60 ppm (Figure 4). 13C NMR Figure 3. FTIR spectra of ricinoleic acid (7), HODEAz (8), and PU NMR spectroscopy. The conversion of acyl azide group into intermediate isocyanate via "Curtius rearrangement" and followed by condensation with the secondary hydroxyl group was confirmed on the basis of bands observed at 3334 and 1691 cm-1 due to the urethane N-H stretching vibration and the C=O stretching vibrations of the PU (Figure 3). The vinylic double bond in the PU remains intact, showed by the =C-H bond stretching vibration band at 3010 cm-1. Urethane formation was also confirmed by 1H NMR spectroscopy, with the peak corresponding to methylene protons attached to acyl azide group in the monomer HODEAz (8) is shifted to downfield due to urethane formation as well a new peak appearing in the range of 4.6 to 4.8 ppm due to NH protons of the urethane group |
|
train_13 | What is described in this image? | Fig. 5 shows the DSC curves of PMMA/paraffin microcapsules after 200, 500 and 1000 of thermal cycling. The melting peak point of the PMMA/paraffin microcapsules changed in the range 33.40–35.71 °C when its crystallizing peak point changed in the range 25.41-27.56 ℃ after 200, 500 and 1000 of cycling, respectively. Based on these results, it is obvious that the PMMA/paraffin microcapsules have good thermal reliability in terms of the changes in its phase change temperatures. Also, the average latent heats of melting and crystallization of the PCM Fig. 5. The DSC thermogram for PMMA/paraffin microcapsules after thermal cycling |
|
train_14 | What is described in this image? | based on the self-diffusion coefficient (0.8 × 10-15 cm2/s) at 170 °C for polystyrene of Mw = 1000 kg/mol is ~2 h.20,81 In order to further prove that the Tg depression observed is not an artifact caused by degradation of the material, we perform a combination of compression and thermal annealing under an inert environment at 170 ℃ for 5 h in a platen press at 10, 000 psi, which results in reversion of the rods to bulk behavior, as shown in Fig. 5. We note that simple annealing (without compression) at 170 °C for 5 h did not result in reversion of the film; this was similar to our observation for stacked thin films (which required pressure to revert to bulk),20 but differed from single thin films, which dewet and thickened (and thereby, reverted to the bulk) under simple thermal treatment.1 In order to test the importance of the free surface, we plot the magnitude of the Tg depression as a function of characteristic length scale (h* = V/S, where V is the volume and S is the surface area) in Fig. 6 for our unsupported nanorods compared with data on polystyrene ultrathin films, 12,5,10 stacked thin films,21 nanowires from the work of Zhu and co-workers,39 and nanospheres from Priestley and co-workers43 and from Cangialosi and co-workers.45 The characteristic length is taken to be as follows: |
|
train_15 | What is described in this image? | Fig. 4 represents at the left-hand side HPer DSC curves of the PP melting at heating rates of 10°C/min (Fig. 4a) and 300 °C/min (Fig. 4b) after applying controlled cooling rates from 5 up to 250 °C/min. The HPer DSC curves are corrected for the extrapolated onset values according to Table III in [2]. At the right-hand side, the characteristic peak temperature values - Tc, Tm, Tm1 (the low-temperature melting peak), and Tm2 (the hightemperature melting peak) - of PP are plotted as a function of the cooling rate, all corrected for sample mass, cooling rate and heating rate. Fig. 4 represents at the left-hand side HPer DSC curves of the PP melting at heating rates of 10°C/min (Fig. 4a) and 300 °C/min (Fig. 4b) after applying controlled cooling rates from 5 up to 250 °C/min. The HPer DSC curves are corrected for the extrapolated onset values according to Table III in [2]. At the right-hand side, the characteristic peak temperature values - Tc, Tm, Tm1 (the low-temperature melting peak), and Tm2 (the hightemperature melting peak) - of PP are plotted as a function of the cooling rate, all corrected for sample mass, cooling rate and heating rate. Fig. 4 represents at the left-hand side HPer DSC curves of the PP melting at heating rates of 10°C/min (Fig. 4a) and 300 °C/min (Fig. 4b) after applying controlled cooling rates from 5 up to 250 °C/min. The HPer DSC curves are corrected for the extrapolated onset values according to Table III in [2]. At the right-hand side, the characteristic peak temperature values - Tc, Tm, Tm1 (the low-temperature melting peak), and Tm2 (the hightemperature melting peak) - of PP are plotted as a function of the cooling rate, all corrected for sample mass, cooling rate and heating rate. When no reorganization takes place, one expects the melting peak temperature to follow more or less the crystallization peak temperature with increasing preceding cooling rate. The lowest melting temperature, Tml, in Fig. 4a however, follows the crystallization temperature only to a limited extent: the less lowering of Tml compared to Tc is thought to be caused by extensive reorganization during heating, leading to increased perfection and/or increase in crystallite dimensions. The second, highest melting temperature, 7m2, remains more or less constant with increased preceding cooling rate, indicating it is caused by reorganization via recrystallization during the relatively slow heating at 10°C/min. Such a second melting temperature typically arises when the applied heating rate is roughly lower than the preceding cooling rate used. Fig. 4b shows only one melting peak during fast heating at 300 ℃/min after various preceding cooling rates and 7m follows the crystallization temperature again to a limited extent. In this case, the applied heating rate is for all cases equal to or higher than the cooling rate used. The rather When no reorganization takes place, one expects the melting peak temperature to follow more or less the crystallization peak temperature with increasing preceding cooling rate. The lowest melting temperature, Tml, in Fig. 4a however, follows the crystallization temperature only to a limited extent: the less lowering of Tml compared to Tc is thought to be caused by extensive reorganization during heating, leading to increased perfection and/or increase in crystallite dimensions. The second, highest melting temperature, 7m2, remains more or less constant with increased preceding cooling rate, indicating it is caused by reorganization via recrystallization during the relatively slow heating at 10°C/min. Such a second melting temperature typically arises when the applied heating rate is roughly lower than the preceding cooling rate used. Fig. 4b shows only one melting peak during fast heating at 300 ℃/min after various preceding cooling rates and 7m follows the crystallization temperature again to a limited extent. In this case, the applied heating rate is for all cases equal to or higher than the cooling rate used. The rather |
|
train_16 | What is described in this image? | Fig. 7. Evolution of storage modulus C' and complex viscosity nº as a function of time for 25 wt% UHMWPE in "inverse quenching" with a fixed frequency of 0.1 Hz and strain of 2.0% Fig. 7 displays the changes of storage modulus and complex viscosity during time sweeps with a fixed frequency of 0.1 Hz and strain of 2.0% at 115 °C, 117 °C, 118 °C, and 119 °C. The initial phase separation temperature was chosen as 115°C, which is sufficient to have liquid-liquid phase separation but no crystallization for the 100 min annealing time according to Fig. 6. C' gradually increases with time at 115 ℃ denoting the liquid-liquid phase separation. As the temperature goes up to 117 °C, C' increases successively and gradually approach a fixed value during a period of 100 min, suggesting the further liquid-liquid phase separation. |
|
train_17 | What is described in this image? | Fig. 2. Plot of the DSC data for the 5 mol% Eu-doped FCZ glass with different heating rates from 5 K/min to 25 K/min in steps of 5 K/min. The curves are vertically displaced for clarity. where To is the onset, To the end of crystallization temperature and dHc/dT the heat flow into or out of the sample when it is heated or cooled to a temperature T. An illustration for different heating rates is given in Fig. 2 for the 5 mol% Eu-doped FCZ glass. Shifts in peak |
|
train_18 | What is described in this image? | scan. The optimum annealing condition would be to hold a sample at the T' temperature for a considerable period of time, because the maximum amount of ice could then form, which would allow the solution to concentrate maximally up to the C' concentration. However, the exact T' temperature and the required annealing time are not usually known, so estimates of these parameters tend to be used, and the degree of devitrification achieved depends on the quality of these estimates. The thermograms obtained from sucrose solutions in the concentration range 10-80% annealed at -30℃ for 30 min are shown in Fig. 3. Only a simple second-order glass transition is observed in Fig. 3 from the vitrified samples (i.e. scan. The optimum annealing condition would be to hold a sample at the T' temperature for a considerable period of time, because the maximum amount of ice could then form, which would allow the solution to concentrate maximally up to the C' concentration. However, the exact T' temperature and the required annealing time are not usually known, so estimates of these parameters tend to be used, and the degree of devitrification achieved depends on the quality of these estimates. The thermograms obtained from sucrose solutions in the concentration range 10-80% annealed at -30℃ for 30 min are shown in Fig. 3. Only a simple second-order glass transition is observed in Fig. 3 from the vitrified samples (i.e. >66% sucrose) which did not form any ice. In contrast to this, for the other samples which did form ice, the initial glass transition is followed by a larger second transition which precedes the ice-melting peak. The first transition is generally accepted to be a glass transition associated with the freezeconcentrated phase present. However, it is the origin of the second transition which is the subject of most of the controversy.12-14 Although the thermograms from the samples which contain ice are more complicated than those from completely vitrified samples, the annealing process does reveal some simple trends in their behaviour which occur as a function of concentration. Each of the ice-containing samples shown in Fig. 3 has an initial glass-transition temperature at ca. - 45 ℃, which by comparison to the thermograms from the totally vitrified samples corresponds to a sucrose concentration of ca. 78%. This result questions the validity of the much lower C. value of 64% calculated from the area of the ice-melting endotherm.1,5-9 This concentration of ca. 78% Fig. 3 DSC thermograms for 10-80% sucrose solutions which had been annealed at -30°C for 30 min. To assist comparison, the thermograms have been normalised (w/g) to take into account variations in sample weight Many of the previous studies1.5-9 have been conducted on solutions of relatively low concentration, which were probably chosen to ensure that reproducible results could be obtained. However, we have now shown that reproducible results can also be obtained from concentrated solutions when suitable annealing protocols are adopted (Fig. 3). A double transition is routinely observed immediately prior to the ice-melting endotherm, and whereas it is generally accepted that the first transition is related to a glass transition, there is increasing controversy12-14 over the origin of the second transition. This second transition has been called the 'T' transition', which is claimed1.5-9 to occur when the maximally freeze concentrated liquid phase goes through a second glass transition. However, we question whether this really is a glass transition for the following reasons: (1) Fig. 5 and the data in Table 1 clearly demonstrate that the maximum freeze concentration occurs at a temperature of -40°C, which is significantly below the temperature of this transition (i.e. - 32°C); (2) Fig. 5 and Table 1 also demonstrate that when the sample was annealed at -32℃ there was a significant reduction in T2, which must have resulted from a dilution of the concentrated solution due to melting of some of the ice present at this elevated temperature; (3) Fig. 3 shows that the change in heat capacity associated with this transition is clearly in excess of the corresponding change at the glass transition of totally vitrified samples; (4) the second transitions shown in Fig. 3 are significantly sharper than the corresponding glass transitions in the completely vitrified samples; (5) it is not a second-order transition because there is no corresponding step increase in the baseline after the icemelting peak (Fig. 3). In the light of all this evidence, we propose that the second transition in the DSC thermogram, which has been called the 'T' glass-transition temperature',1.5-9 is not a glass transition, but is a transition which relates to the onset of ice dissolution. Therefore this transition should be considered as the temperature at which the mobility of the solute sucrose has increased sufficiently that 793 mixing and dissolution of ice can begin, allowing transition to the equilibrium solubility limit at that temperature. -40°C, which is significantly below the temperature of this transition (i.e. - 32°C); (2) Fig. 5 and Table 1 also demonstrate that when the sample was annealed at -32℃ there was a significant reduction in T2, which must have resulted from a dilution of the concentrated solution due to melting of some of the ice present at this elevated temperature; (3) Fig. 3 shows that the change in heat capacity associated with this transition is clearly in excess of the corresponding change at the glass transition of totally vitrified samples; (4) the second transitions shown in Fig. 3 are significantly sharper than the corresponding glass transitions in the completely vitrified samples; (5) it is not a second-order transition because there is no corresponding step increase in the baseline after the icemelting peak (Fig. 3). In the light of all this evidence, we propose that the second transition in the DSC thermogram, which has been called the 'T' glass-transition temperature',1.5-9 is not a glass transition, but is a transition which relates to the onset of ice dissolution. Therefore this transition should be considered as the temperature at which the mobility of the solute sucrose has increased sufficiently that 793 mixing and dissolution of ice can begin, allowing transition to the equilibrium solubility limit at that temperature. -40°C, which is significantly below the temperature of this transition (i.e. - 32°C); (2) Fig. 5 and Table 1 also demonstrate that when the sample was annealed at -32℃ there was a significant reduction in T2, which must have resulted from a dilution of the concentrated solution due to melting of some of the ice present at this elevated temperature; (3) Fig. 3 shows that the change in heat capacity associated with this transition is clearly in excess of the corresponding change at the glass transition of totally vitrified samples; (4) the second transitions shown in Fig. 3 are significantly sharper than the corresponding glass transitions in the completely vitrified samples; (5) it is not a second-order transition because there is no corresponding step increase in the baseline after the icemelting peak (Fig. 3). In the light of all this evidence, we propose that the second transition in the DSC thermogram, which has been called the 'T' glass-transition temperature',1.5-9 is not a glass transition, but is a transition which relates to the onset of ice dissolution. Therefore this transition should be considered as the temperature at which the mobility of the solute sucrose has increased sufficiently that 793 mixing and dissolution of ice can begin, allowing transition to the equilibrium solubility limit at that temperature. |
|
train_19 | What is described in this image? | Sample I was measured in the temperature range of 90–360 K in order to investigate melting process of the title compound. Fig. 1 shows the temperature dependences of the heat flow (DSC curves) obtained while first cooling (lower curve) at the rate of 20 K min-1 and subsequent heating (upper curve) of [Ca(H2O)4](ClO4)2 sample I at the rate of 30 K min-1. In Fig. 1 one can see five anomalies on Sample I was measured in the temperature range of 90–360 K in order to investigate melting process of the title compound. Fig. 1 shows the temperature dependences of the heat flow (DSC curves) obtained while first cooling (lower curve) at the rate of 20 K min-1 and subsequent heating (upper curve) of [Ca(H2O)4](ClO4)2 sample I at the rate of 30 K min-1. In Fig. 1 one can see five anomalies on the upper curve (heating curve). Four of them at Te1, T2, T23 and Te are very small in comparison with the fifth one which is connected with the melting of the sample at Tm = 350 K. These small anomalies are better visible in the insertion, also presented in Fig. 1. While cooling the liquid (melted or rather better to say dissolved in its own coordinated water) sample I from 360 to 90 K at a rate of 30 K min-1, an exothermic sharp peak at ca. 247 K can be observed, as can be seen in Fig. 2. Thus a re-crystallization into a crystalline phase take place. |
|
train_20 | What is described in this image? | Fig. 5 shows the conversion dependence of the glass transition temperature. The one-to-one relation between the glass transition temperature and conversion can be seen. The relation between the glass transition temperature and conversion was precisely discussed in a previous study by Wisanrakkit and Gillham [3]. According to their study, the glass transition temperature prior to gelation (α < αχε) varies with increasing number average molecular weight as follows: Fig. 5. Relation between conversion and glass transition temperature. Line represents the fitting result of Wisanrakkit's model [3]. long linear polymer, Tg™ is maximum glass transition temperature of the fully cured materials, Kx is constant parameters, and Ao is the initial amine concentration. The result of a dynamic Monte Carlo percolation grid simulation also predicts that the glass transition temperature increases strongly after gelation when cross-linking starts to occur more frequently [12]. The line in Fig. 5 represents the fitting result of Wisanrakkit's model. The fitting parameter of Wisanrakkit's model is summarized in Table 1. It suggests that the experimental results can successfully describe the overall change in glass transition during the reaction. The result of previous study also shows same trend [3]. reveals the quasi-real-time change in the glass transition at non-isothermal curing. Fig. 7(a) shows the relation between the glass transition temperature and temperature during heating at a rate of 2 K min -1. It is clearly shown that the glass transition temperature increases with temperature. Combining both the temperature-a profile obtained from DSC and temperature-Ts profile obtained from FSC, the conversion dependence of the glass transition temperature can be obtained, as shown in Fig.7(b). The results of Figs. 5 and 7(b) are similar in that To increases with increasing conversion. Here, the value of To in Fig. 7(b) is higher than that of Fig. 5. The reason is not clear at the present stage. There may be several reaction mechanisms due to the multi components of the curing agent. Furthermore, it is known that the diffusion control reaction becomes influential after vitrification [3]. In the case of non-isothermal curing with a wide range of temperatures, both diffusion control reaction and chemical-controlled reaction mechanisms may compete at each temperature. As a result, the glass transition could be changed in spite of the same conversion. |
|
train_21 | What is described in this image? | Fig. 5. Temperature-modulated DSC of prepreg material pre-cured for 30 min at 180 °C, modulation amplitude 0.5 K, underlying heating rate 10 K/min, modulation period 60 s; total, reversing and non-reversing signals. |
|
train_22 | What is described in this image? | (Figure 11) allows to obtain the activation energy for the nonautocatalytic reaction, Eal and for the autocatalytic |
|
train_23 | What is described in this image? | Figure 26. Thermograms at different heating rates ß and for a solution at xo = 0.2; from [16]. we can also plot a curve whose extrapolation gives also Tiquidus However, in certain cases, it is not always possible to locate correctly these points. For example, in Figure 26, the points of the top are rather characteristic of the solidus than of the liquidus. It is why, we have defined other points which could be characteristic of the end of the peak. In Figure 2, we have defined, in addition to the temperature Tpeak and Tend = Tpl(tend), the temperatures T1/2 which is the temperature where we calculate the half height of the peak and Toon the extreme end of the peak. When ß -> 0 all these temperatures tend to Tiquidus. It is the case illustrated in Figure 31. |
|
train_24 | What is described in this image? | By observing the fractured samples, it is possible to relate the stress-strain trends slopes to the failure modes experienced by the laminates. Fig. 3 and Fig. 4 show macrographs of the tested samples at the beginning and at the end of the aging exposition (i.e., after 0 and 84 days, respectively). and the area interested by buckling phenomena becomes larger after the aging exposition (Fig. 4c-f). |
|
train_25 | What is described in this image? | under a nitrogen atmosphere. TGA thermograms are shown in Figure 8. The onset temperature of degradation of the polymers increased with poly(ether diamine) length. The values of 5% weight reduction temperature, Tas, for poly- Figure 8. TGA thermograms for cross-linked poly(BA-eda600), poly- |
|
train_26 | What is described in this image? | study). The addition of sucrose enhanced both the peak and final viscosities of the gum-starch pastes (p< 0.05) and had a much greater influence than Xan substitution (Fig. 3a and b), indicating After TS or TS/Xan dispersions were gelatinized, the pastes were subjected to both thermal and shear stresses at the holding temperature (95 ℃). Further disruption of starch granules and leaching out of starch molecules caused a decrease in viscosity. The resultant drop in viscosity from peak to a holding strength (minimum viscosity after the peak, occurring around the beginning of RVA cooling stage) was determined and defined as breakdown. Therefore, the breakdown measures the susceptibility of gelatinized starch to disintegration due to the loss of starch granule integrity and subsequent disruption, leading to a reduction of the paste viscosity (Christianson et al., 1981; Pongsawatmanit et al., 2007). The breakdown of TS/Xan pastes revealed almost constant values with increasing Xan substitution (p > 0.05) at the same sucrose concentration. However, breakdown values of TS or TS/Xan pastes increased significantly with sucrose addition (p<0.05, Table 2, Fig. 3c) under the influence of applied shear to the mixtures. The results indicate that formed aggregates among polysaccharides and sucrose molecules in the pastes through hydrogen bonding and polymer entanglement are more sensitive to disruption under isothermal shear with increasing sucrose concentration. The RVA setback obtained from the measurement occurs not only due to the degree of reassociation of gelatinized starch (particularly amylose) molecules during cooling, but also due to the simple kinetic effect of cooling on viscosity. The setback value indicates short-term retrogradation of starch (Pongsawatmanit et al., 2006). It was determined from the increase in viscosities of TS and TS/Xan pastes from holding strength value to final viscosity after cooling down to 50 ℃ at 6 ℃/min. Setback increased with increasing sucrose concentration and decreased with increasing Xan substitution (p < 0.05) (Fig. 3d). The effect of Xan on the extent of the decrease in setback values of TS/Xan pastes with and without sucrose was also observed. Setback values of 5% w/w TS and TS/Xan pastes (mixing ratio = 9/1) decreased from 1050 mPas to 440 mPa s and from 360 mPa s to 260 mPa s for the pastes containing 30% and 0% sucrose, respectively. These results imply that for the TS-based formulation containing sucrose, Xan addition could reduce the setback of the TS pastes leading to lower syneresis (Pongsawatmanit and Srijunthongsiri, 2008). |
|
train_27 | What is described in this image? | Fig. 5a and b shows the changes of ΔHm and Tm of chitosan and galactomannan films, respectively, with the increase of glycerol concentration. For chitosan films the increase of glycerol concentration leads to an increase of AHm, and to a decrease of Tm values. The higher values of ΔΗΜ are possibly explained by the increase of the crystallinity of chitosan films (Sperling, 2006). When glycerol concentration increases, a greater polymer mobility (lower Tg values) is obtained that favors the formation of crystalline domains The thermograms (results not shown) had a flat shape indicating an amorphous structure of these films (Mathew & Dufresne, 2002; Yakimets et al., 2007). Fig. 5b shows that the increase of glycerol concentration leads to higher values of ΔΗΜ, that can be explained by the formation of crystalline domains, favored by the increase of the polymer mobility (lower Tg values) how was already explained elsewhere (Fabra et al., 2010; Mathew & Dufresne, 2002; Sperling, 2006). Also, the increase of the moisture content in the film matrix when more hydrogen bonds are available can influence the crystallinity of the films (Chen et al., 2008). Tm values were not statistical significance influenced (p > 0.05) by the increase of glycerol concentration. |
|
train_28 | What is described in this image? | For example, the amount of exotherms after blending 5 wt% of SWCNTs into coumarin-Py BZ was 139.2 J g-1, approximately 30.3 J g-1 lower than that of pure coumarin-Py BZ. Kim et al. observed a decrease in the enthalpy of a PBZ derivative after blending with CNTs, attributable to the hindered mobility of the ring-opened benzoxazine, thereby decreasing the crosslinking density of the PBZ.30 Fig. 11 presents the DSC profiles of pure coumarin-Py BZ and its blend with 3 wt% of SWCNTs, after each curing stage. Again, the amount of exotherms decreased upon increasing the curing temperature, as noted above. A temperature of 240 ℃ was required for the maximum exothermic peak to disappear completely, similar to that of pure coumarin-Py BZ in the absence of SWCNTs. Fig. 12 displays the effect of the SWCNT content on the glass transition temperature of poly(coumarin-Py BZ). When the SWCNTs content was 1, 3, or 5 wt%, the glass transition temperature of the nanocomposite was lower (ca. 185-187 ℃) than that of pure coumarin-Py BZ (200 ℃). We attribute these lower glass transition temperatures to the lower crosslinking densities of poly(coumarin-Py BZ) after blending with the SWCNTs. Fig. 13 presents the thermal stabilities of these systems under a N2 atmosphere, as investigated using TGA. We used the weight loss temperature (Ta1o) as the standard. The weight loss temperatures corresponding to the Mannich cleavage of the poly DSC profiles of poly(coumarin–Py BZ), incorporating various Fig. 12 SWCNT contents, after thermal curing. |
|
train_29 | What is described in this image? | 4.2.3. Fit of experimental data Last step in the kinetic analysis is determination of the preexponential factor A. As was already suggested earlier, it is advantageous to confirm the value of this parameter by independent evaluation within the framework of different models (if possible). In our work the values of A were determined by curvefitting for the JMA model (input parameters were E and m) and by calculation according to Eq. (12) for the AC model. The results are listed in Table 1; several chosen experimental crystallization curves fitted by JMA model are then shown in Fig. 11 (full set of all particle size fractions fitted by the JMA model is to be found in Appendix 4). Fits by the AC model (not displayed explicitly in this work) were slightly better, mostly for coarse fractions where the deviation from the surface first order kinetics due to the evincing bulk crystallization started to take effect. This is, however, an expected finding as in the case of JMA model it is the sole parameter m, which is responsible for the shape of the crystallization peak and any deviation from the kinetics defined by this parameter shows itself instantly, while in the case of the AC model each parameter (M and N) "controls" one edge of the peak, thus higher flexibility is granted. Nonetheless, even the AC fits were not perfect as the steeply developing bulk crystallization overlapping the background surface kinetics produced an abruptly digressive peak edge while the leading edge was still driven by the first order kinetics (see Fig. 11). In consequence the data corresponding dominantly to the bulk kinetics cover a relatively narrow a range and therefore the parameter M still results from averaged response of both involved mechanisms. 4.2.3. Fit of experimental data Last step in the kinetic analysis is determination of the preexponential factor A. As was already suggested earlier, it is advantageous to confirm the value of this parameter by independent evaluation within the framework of different models (if possible). In our work the values of A were determined by curvefitting for the JMA model (input parameters were E and m) and by calculation according to Eq. (12) for the AC model. The results are listed in Table 1; several chosen experimental crystallization curves fitted by JMA model are then shown in Fig. 11 (full set of all particle size fractions fitted by the JMA model is to be found in Appendix 4). Fits by the AC model (not displayed explicitly in this work) were slightly better, mostly for coarse fractions where the deviation from the surface first order kinetics due to the evincing bulk crystallization started to take effect. This is, however, an expected finding as in the case of JMA model it is the sole parameter m, which is responsible for the shape of the crystallization peak and any deviation from the kinetics defined by this parameter shows itself instantly, while in the case of the AC model each parameter (M and N) "controls" one edge of the peak, thus higher flexibility is granted. Nonetheless, even the AC fits were not perfect as the steeply developing bulk crystallization overlapping the background surface kinetics produced an abruptly digressive peak edge while the leading edge was still driven by the first order kinetics (see Fig. 11). In consequence the data corresponding dominantly to the bulk kinetics cover a relatively narrow a range and therefore the parameter M still results from averaged response of both involved mechanisms. One more very interesting fact arises from the curves in Fig. 11 and Appendix 4. It can be seen that although in case of coarse fractions the surface crystallization mechanism does not evince markedly (see Fig. 7) it is still this mechanism which is crucial for the overall shape of the crystallization peak, i.e. with the only exception of pure bulk samples each set of crystallization curves measured within one particle size fraction had a similar leading peak edge, which is a "fingerprint" of first order kinetics and the only difference caused by ascending bulk crystallization was to be seen in the steepness of the digressive peak edge. Only in the case of bulk samples the peaks were significantly shifted in temperature representing true bulk kinetics. Similar trend may also be observed for slowest heating rates and coarse fractions, where the number of surface defects in combination with higher activation energy for this type of crystallization does not suffice to initiate the bulk crystallization, which in this case starts to manifest independently. The presented conclusion is also in agreement with the rather significant shift of crystallization temperatures with particle size, which cannot be attributed only to the thermal gradients arising from larger grain sizes but is an evident result of the initiating process (surface crystallization) having less pronounced effect. |
|
train_30 | What is described in this image? | Based on recently collected test results, the authors recommend that at least three temperature steps above and below the approximate temperature range for the PCM phase transition process shall be considered. Fig. 7 describes a proposed process of development of a temperature range for the dynamic HFMA testing. A major challenge is to know at what temperatures the dynamic HFMA test need to be started and later terminated. The DSC enthalpy profile for the PCM used in the tested material can be utilized for this purpose. The main goal of this analysis is to estimate non-PCM related enthalpy changes for temperature levels below and above the melting point for the test specimen itself, and for the testing apparatus. Assuming that mass of the sample is not changing during the dynamic HFMA test, enthalpy change rates should stay constant within the part of the test when PCM is frozen, and subsequently during the entire part of the test when the PCM is melted. Consequently, they can be easily extracted from the total enthalpy change measured for each temperature step. Due to the fact that differences in specific heat-related enthalpy changes are insignificant, for temperature regions with frozen and melted PCM, the energy effects associated to partly-frozen/melted PCM can be neglected. Fig. 7. Example of estimation of the temperature ranges for dynamic HFMA test for a blend of thermal insulation and microencapsulated PCM. |
|
train_31 | What is described in this image? | Cold-crystallization was chosen as a crystallization method because it leads to more intense spherulite nucleation resulting in shorter crystallization time and smaller spherulite sizes.17 Pristine PLA showed cold-crystallization temperature at about 124.11°C. The cold-crystallization temperature of PLA decreased as the PEG content increased in parallel with the shift in To as shown in Figure 2. The cold-crystallization decreased to 74.30℃ for the blend containing 10 wt% PEG plasticizer. The significant depression of Tcc and the decrease in Tx indicated that the PEG was compatible with PLA. It clearly appeared that the decreasing of Tcc and Tg of PLA because of enhanced chain mobility as the plasticizer content increased.18 Enhanced chain mobility increased the rate of crystallization, which allowed PLA to crystallize at lower temperature. Furthermore, the crystallization peak was narrowed as the content plasticizer increases because of increased ability of PLA to crystallize.19 When a polymer molecule crystallizes, this high degree of organization becomes a major factor in overall structure. Low crystallinity of PLA (13.87%) in this study was destroyed by the addition of PEG-200 plasticizer. However, high crystallinity polymer prevents compatibility with plasticizers, because they are unable to separate the polymer molecules sufficiently to move in between them. Generally, the elongation at break of PLA/PEG blend increase as crystallinity decrease because of the increasing mobility of the system. Crystallinity, if well developed, increases the elongation at break and further decreases the drawability of PLA.20 The impact of the plasticizer on the thermal stability often takes into account when studying a plasticized polymer. One of most accepted methods to study the thermal properties of polymeric materials is thermogravimetry. The integral (TGA) and derivative (DTG) thermogravimetric curves provide information about the nature and extent of degradation of the polymeric materials. The TGA and DTG thermograms of PLA/PEG blends are given in Figure 2. A detailed evaluation of the thermograms is presented in Table IV. Cold-crystallization was chosen as a crystallization method because it leads to more intense spherulite nucleation resulting in shorter crystallization time and smaller spherulite sizes.17 Pristine PLA showed cold-crystallization temperature at about 124.11°C. The cold-crystallization temperature of PLA decreased as the PEG content increased in parallel with the shift in To as shown in Figure 2. The cold-crystallization decreased to 74.30℃ for the blend containing 10 wt% PEG plasticizer. The significant depression of Tcc and the decrease in Tx indicated that the PEG was compatible with PLA. It clearly appeared that the decreasing of Tcc and Tg of PLA because of enhanced chain mobility as the plasticizer content increased.18 Enhanced chain mobility increased the rate of crystallization, which allowed PLA to crystallize at lower temperature. Furthermore, the crystallization peak was narrowed as the content plasticizer increases because of increased ability of PLA to crystallize.19 When a polymer molecule crystallizes, this high degree of organization becomes a major factor in overall structure. Low crystallinity of PLA (13.87%) in this study was destroyed by the addition of PEG-200 plasticizer. However, high crystallinity polymer prevents compatibility with plasticizers, because they are unable to separate the polymer molecules sufficiently to move in between them. Generally, the elongation at break of PLA/PEG blend increase as crystallinity decrease because of the increasing mobility of the system. Crystallinity, if well developed, increases the elongation at break and further decreases the drawability of PLA.20 The impact of the plasticizer on the thermal stability often takes into account when studying a plasticized polymer. One of most accepted methods to study the thermal properties of polymeric materials is thermogravimetry. The integral (TGA) and derivative (DTG) thermogravimetric curves provide information about the nature and extent of degradation of the polymeric materials. The TGA and DTG thermograms of PLA/PEG blends are given in Figure 2. A detailed evaluation of the thermograms is presented in Table IV. |
|
train_32 | What is described in this image? | Fig. 3 shows the solid-solid and liquid-liquid thermal transitions (Tr) of the oleic acid detected during heating and cooler processes both Fig. 3. Thermal cycle of oleic acid from Solid 1 to Liquid 1 (heating process) and from Liquid 1 to Solid 1 (cooling process) with the Tand AH experimental data for the transitions. |
|
train_33 | What is described in this image? | 3.1. SEM images of MFC–PVA composite surface and fracture topographies Fig. 1 shows typical SEM images of MFC–PVA composite (noncrosslinked, 10% MFC), surface topography (A) that shows the MFC distribution and facture surface (B) after tensile testing. From Fig. 1A, it can be clearly seen that the MFC fibrils are randomly organized but uniformly distributed within PVA and some of them are just at the surface of the composite. Fig. 1B clearly shows the MFC fibrils protruding out from the PVA at the facture surface. 3.1. SEM images of MFC–PVA composite surface and fracture topographies Fig. 1 shows typical SEM images of MFC–PVA composite (noncrosslinked, 10% MFC), surface topography (A) that shows the MFC distribution and facture surface (B) after tensile testing. From Fig. 1A, it can be clearly seen that the MFC fibrils are randomly organized but uniformly distributed within PVA and some of them are just at the surface of the composite. Fig. 1B clearly shows the MFC fibrils protruding out from the PVA at the facture surface. 3.1. SEM images of MFC–PVA composite surface and fracture topographies Fig. 1 shows typical SEM images of MFC–PVA composite (noncrosslinked, 10% MFC), surface topography (A) that shows the MFC distribution and facture surface (B) after tensile testing. From Fig. 1A, it can be clearly seen that the MFC fibrils are randomly organized but uniformly distributed within PVA and some of them are just at the surface of the composite. Fig. 1B clearly shows the MFC fibrils protruding out from the PVA at the facture surface. Fig. 1. Typical SEM images. (A) Surface topography of the MFC-PVA composites. (B) Fracture surface of the MFC-PVA composite. Both specimens contain 10% MFC. |
|
train_34 | What is described in this image? | where T, is the peak exothermic temperature at a certain heating rate. The plots of In(B/T_2) versus 1/Tp are shown in Figure 3, and the values of E and A could be obtained from the slope and intercept of the linear fitting curve, respectively. The linear fit results of Ozawa method are also displayed in Figure 3. The calculated parameters (E, and A) are listed in Table 2. The activation energies obtained from the Kissinger and Ozawa methods were 77.49 kJ/mol and 80.24 kJ/mol, respectively. However, it has been reported that Ozawa method is relatively inaccurate [27] and should not be used without performing an iterative correction procedure for the value of E [28]. |
|
train_35 | What is described in this image? | Fig. 9 shows representative stress vs strain curves of PLA specimens (PLA-I, PLA-EI, PLA-IA and PLA-EIA). The values of the main mechanical properties obtained from those curves are summarized in Table 8. Fig. 9. Representative stress vs strain curves from tensile testing for processed PLA. |
|
train_36 | What is described in this image? | A peak value of Von Mises stress of 1134 MPa at a depth of 352 µm was calculated based on the axial and hoop stress o1 and o3, Fig. 5. A study of residual stress in LPBF by Mercelis and Kruth (24) showed that the as-built residual stresses are in the range of the material yield stress. However, the residual stresses are reduced after removal from the baseplate. Therefore, although no further measurements were made, the residual stress in the test bar used in the experiments will be lower than the values presented in Fig. 5. Furthermore at temperatures above 650 ℃ the strength of the tool steel base reduces significantly, compared to the build itself. Therefore, at the higher heat treatment temperatures, the baseplate would have negligible effect on residual stress [25]. Fig. 5. Residual stress represented by Von Mises stress in LPBF CM247LC builds. |
|
train_37 | What is described in this image? | naringenin-PC complex. The results of the DSC test confirmed the association of naringenin and PC in the complex as both peaks representing naringenin and PC changed position (Fig. 3). Phospholipids (Fig. 3b) showed two major peaks at 83.21 and 107.90 ℃ and a small peak at 64.45 ℃. naringenin-PC complex. The results of the DSC test confirmed the association of naringenin and PC in the complex as both peaks representing naringenin and PC changed position (Fig. 3). Phospholipids (Fig. 3b) showed two major peaks at 83.21 and 107.90 ℃ and a small peak at 64.45 ℃. (107.90 ℃) which is relatively less sharp. Naringenin (Fig. 3a) showed a sharp endothermic peak at 253.08 ℃. On the other hand naringenin-PC complex (Fig. 3c) showed two peaks at 51.23 and 62.21 ℃, which is different from the peaks of the individual components of the complex. Moreover the onset temperature is 48.18 °C only. It is evident that the original peaks of naringenin and phospholipids disappear from the thermogram of complex and the phase transition temperature is lower than that of phospholipids. Fig. 3 DSC thermograms of naringenin (a); PC (b) and naringenin-PC complex (c) |
|
train_38 | What is described in this image? | Thermogravimetric analysis (TGA) of PHMB shows a clear water loss up to 420 K, with a water mass of 5.47% (Figure 8); it means less than one water molecule per biguanide group in the solid material. Probably, a higher amount of water is adsorbed at material surface and an even lower molar ratio of water to biguanide is present in the material bulk. It is an important aspect to consider when evaluating the water effect in material properties. The mass loss with peak at 536 K is believed to be the loss of guanidine from chain ends, and the loss at 637 K is the guanidine and chloride loss from broken biguanide groups, with extensive backbone fragmentation. At 746 K the degradation of backbone takes place, leaving 11.2% of mass (in polymer basis), probably graphite and carbon nitride. Figure 8. Thermogravimetric analysis of PHMB under N2 flux and 10 K min 1 heating rate. |
|
train_39 | What is described in this image? | Figure 13 compares the two runs that exhibited endothermic peaks. In both the peak occurs at a much higher temperature than the decomposition peak exhibited by Cu(OH)2 alone (Figure 6) and above the temperature where the exothermic peak was expected. In both cases, it appears that the pressure capsule leaked during the run and this loss of pressure in the capsule prevented the reaction from occurring. Figure 13. DSC analysis of Cu(OH)2 + CuBr2 mixture, 2 endothermic runs |
|
train_40 | What is described in this image? | Changing the orientational order in the CLCPs leads to internal stresses and changes of the sample shape.[23,25] We measured the stress generated in the CLCP fibers upon exposure to UV light by thermomechanical analysis (TMA). It was difficult to measure the generated stress in a single fiber due to the measurement limit of TMA. We bundled three pieces of the fiber together side by side and fixed the top and bottom of the CLCP fibers using epoxy glue. As shown in Figure 3a, the bundled CLCP fibers were fixed by clamping both ends of the fibers and Figure 3. a) Schematic illustration of the experimental setup. b) Change in stress of the CLCP fibers when exposed to UV light at 366 nm with different intensities at 90°C. An external stress of 930 kPa was loaded initially on the fibers to keep their length unchanged. Average size of the fiber: 6 mm × 80 μm. fiber. Initial stress was loaded onto the bundled fibers to keep their length constant. The stretching direction was parallel to the fiber axis. Upon irradiation with UV light, the generated stress increased and reached 120 and 210 kPa when the light intensity was 45 and 110 mW cm-2, respectively. It was found that a higher intensity of UV light could generate larger stress, as shown in Figure 3b. Additionally, the bending time of the fibers decreased significantly with an increase in light intensity because actinic light with a higher intensity produces a higher concentration of cis-azobenzene moieties and, thus, a larger surface contraction. |
|
train_41 | What is described in this image? | (black line in Fig. 5). The total integrated measured heat flow is proportional to the latent heat release due to ice formation. Fig. 5 Freezing signals of homogeneous ice nucleation of five monodisperse droplet samples (diameter indicated). Black lines are experimental data and the orange solid lines and grey dashed lines are fits to the data in order to obtain Jo(T). The orange line indicates the range between T1 10 and 7,00. Experimental Tom and Tmax are indicated by green and magenta triangles, respectively. (magenta triangles in Fig. 5) or by assigning an onset temperature (green triangles in Fig. 5). Normally this analysis is performed with commercial software that is part of a DSC (magenta triangles in Fig. 5) or by assigning an onset temperature (green triangles in Fig. 5). Normally this analysis is performed with commercial software that is part of a DSC where T is given in Kelvin, and T = 235 K is a scaled temperature to allow for meaningful resolution of the intercept b. Eqn (6) was employed to perform the least-square fitting analysis described above for each individual experiment in the temperature range between 234.15 K to 240.15 K. The resulting individual best-fit thermograms are also shown in Fig. 5 as solid orange and grey dashed lines. (The solid orange line indicates the temperature range where, according to our fit, between 10% Fig. 9 Expanded view of DSC thermogram obtained from the sample with a droplet diameter of 96 µm ±11 µm cooled at a rate of –1 K min-1. The large freezing signal between 235 K and 238 K is due to homogeneous ice nucleation and is also shown in Fig. 5. The smaller freezing signals at temperatures above 239 K are most likely due to heterogeneous ice nucleation in individual and coagulated droplets, see inset. From the decay of these signals we inferred the heat dissipation rate for our thermogram simulation. |
|
train_42 | What is described in this image? | Fig. 6. TCR of the main heater resistance as function of the temperature. The two curves correspond to the measurements performed with the two ovens (CTS and metrology well). The calculated TCR as function of temperature is reported in Fig. 6. Once the relation between temperature and main heater resistance is known the thermopile can also be calibrated. The output voltages of the thermopile (Utp) are recorded for different |
|
train_43 | What is described in this image? | Fig. 1 shows thermogravimetric and differential scanning calorimetry analyses of starch films. As observed in Fig. 1(A), dehydration takes place in the starch from ambient temperature up to 130 °C. The weight loss during this phase is related to the moisture content. After the isothermal of 30 min to complete the dehydration of starch, the weight loss suddenly drops at a temperature of 290 °C, which corresponds to the thermal degradation of the starch. Fig. 1 shows thermogravimetric and differential scanning calorimetry analyses of starch films. As observed in Fig. 1(A), dehydration takes place in the starch from ambient temperature up to 130 °C. The weight loss during this phase is related to the moisture content. After the isothermal of 30 min to complete the dehydration of starch, the weight loss suddenly drops at a temperature of 290 °C, which corresponds to the thermal degradation of the starch. Prior to the DSC analysis, an isothermal at 130°C has also been performed as shown in Fig. 1(B). Decrease of the heat flow is measured from ambient temperature up to 130 °C. Once the content of moisture is lost, classic increase of the heat flow related to the starch as a function of temperature is observed up to 220 °C. Then, above 220°C, the heat flow decreases to reach an endothermic peak with a maximum located at around 290 °C. Thus, initial thermal degradation of the starch starts at 220°C. The initial decrease might be related to breaking of inter-chain weak bonds. Then, endothermic peak might be related to the cleavage of macromolecular chains, resulting in its thermal degradation. By means of DSC, at a low scanning rate such as depicted in Fig. 1(B), anhydrous amorphous starch degrades before to reach the glass transition. The relative low scanning rates used by means of DSC might lead to unwanted thermal reactions during heating. A Fig. 1. Thermogravimetric (A) and differential scanning calorimetry (B) analyses of starch films. First, starch was heated up to 130' C at 10 K min " . Dehydration was ensu through isothermal for 30 min. Then, starch was heated up to 400°C at 5 K min-1 |
|
train_44 | What is described in this image? | Frequently melting of drug substance is accompanied by decomposition. MDSC is capable of deconvoluting overlapping melting and decomposition processes as shown in Fig. 5 where the total heat flow signal shows inadequate resolution of the melt endotherm and the decomposition exotherm. Separation of the events by MDSC Fig. 5. Modulated DSC thermogram of a drug substance exhibiting overlapping melting with decomposition. The melt endotherm is seen in the reversible signal and can clearly be resolved from the decomposition exotherm in the non-reversible heat flow. |
|
train_45 | What is described in this image? | the degree of transformation as a function of the time or the temperature can be calculated and plotted. The calculated results for different cooling rates are presented in Figure 3. The calculated curves labeled "Transformed fraction vs Temperature" and "Transformed fraction vs Time" (Figure 3) trace the course of the ß => a transformation in the Ti-6Al-4V alloy. It must be emphasized, however, that for all cooling rates, a small amount of residual (or retained) |
|
train_46 | What is described in this image? | Data of the temperature dependence of the glass transition width can hardly be found in the literature. More data are published from the average temperature fluctuation in the cooperative rearrangement regions (CRR), 8T.2,9,45,46 The temperature dependence of 8T for PS was measured by Huth et al.47 and recently by Chua at al.25 The data of Ref. 25 are shown in the temperature range of interest in Fig. 3. The data in Fig. 3 are fitted with Eq. (10) using B = 570 K and Ty = 333 K.23 The fitted curve in Fig. 3 indicates that Eq. (10) well describes the temperature dependence of ST. Sq was determined to be 2.29 and is related to the KWW exponent according to oq ~ 1.07/ß Kww.45 The result of this estimation (Bkww ~ 0.47) agrees well with the literature value of 0.44.45 The temperature dependence of the width of the dynamic glass transition can therefore be described by The vitrification function, K, was determined from the data in Fig. 5 and the fitting curve in Fig. 3. As shown in Fig. 5, k is independent on the cooling rate. The experimental data indicate that the width of the thermal and dynamical glass transition are proportional. This means that the vitrification kinetics is basically temperature independent. |
|
train_47 | What is described in this image? | ~1200cm ̄1 (C-OH stretching) from carboxylic groups and at ~1050 cm-1 (skeletal C-O or C-C stretching) peak from carbonyl, carboxylic, and epoxy groups, which confirms the presence of oxygen-containing functional groups.28,29 The peak at 1620 cm-1 can be assigned to the vibrations of the adsorbed water molecules and also the contributions from the skeletal vibrations of un-oxidized graphitic domains.30 The C1s XPS spectrum of graphite before chemical treatment is shown in Fig. 2(a). The peak centred at 284.5 eV corresponds to graphitic carbon (non-oxygenated) (O-C *= O), respectively. 25,26 The peaks at 532.4 eV and 533.3eV in the O1s spectrum of GO (Fig. 2(c)) can be assigned to contributions from C=O* and C-O *-C/C-O *- H |
|
train_48 | What is described in this image? | Fig. 4. Relative mechanical properties for PCL based nanocomposites reinforced with unmodified and chemically modified Luffa cylindrica nanocrystals. The non-linear mechanical behavior of PCL based nanocomposites was characterized by tensile tests performed at room temperature. The tensile modulus, strength and strain at break determined from typical stress–strain curves were determined for the neat PCL matrix and PCL based nanocomposites. The average relative mechanical properties are plotted in Fig. 4, for which the accuracy was found to be 10%. The relative data were calculated from the ratio of a given property divided by the one of the neat matrix. The positive impact of the surface-chemical modification on the mechanical properties is clearly shown in Fig. 4. The stiffness of PCL with the increase in tensile modulus was markedly improved with the surface-chemical treatment of L. cylindrica nanocrystals (PCL/12 wt% MLW nanocomposite). In addition to the increase in strain at break, the strength at break is found to be maintained compared to mechanical data obtained for the nanocomposite reinforced with unmodified nanoparticles (Fig. 4). It can be estimated that the increase in the tensile modulus is attributed to the better filler/matrix adhesion allowing a higher homogeneity and the formation of hard domains resulting from chain tangling effect between surface-grafted cellulose nanocrystals and PCL matrix. The increase in strain at break is probably caused by the breaking of Table 3 The positive impact of the surface-chemical modification on the mechanical properties is clearly shown in Fig. 4. The stiffness of PCL with the increase in tensile modulus was markedly improved with the surface-chemical treatment of L. cylindrica nanocrystals (PCL/12 wt% MLW nanocomposite). In addition to the increase in strain at break, the strength at break is found to be maintained compared to mechanical data obtained for the nanocomposite reinforced with unmodified nanoparticles (Fig. 4). It can be estimated that the increase in the tensile modulus is attributed to the better filler/matrix adhesion allowing a higher homogeneity and the formation of hard domains resulting from chain tangling effect between surface-grafted cellulose nanocrystals and PCL matrix. The increase in strain at break is probably caused by the breaking of Table 3 |
|
train_49 | What is described in this image? | Fig. 1. The XRD pattern of NBT–BT calcined at 850 °C compared with the standard XRD pattern (PDF 36-0340). Fig. 1 shows the XRD pattern of NBT and 0.92NBT-0.08BT |
|
train_50 | What is described in this image? | Thermograms shown in Fig. 3 enlighten differences between samples obtained from different cultivars (Cornulara and Cellina di Nardò), but identical growing area (Carpignano) and extraction system (SS). Moreover, crystallization and melting profiles of EVOOs from the same cultivar (Ogliarola salentina) and growing area (Carpignano), but milled by SS and LS system, clearly differed (Fig. 4). |
|
train_51 | What is described in this image? | (TGA), and the weight loss are shown in Figure 3. The weight loss of 5% is taken as the effective decomposition temperature Figure 3. TGA spectra of thermoplastic shape-memory polyimides. |
|
train_52 | What is described in this image? | transformation, but the transformation temperatures change remarkably with the change of SLM process parameters (i.e. v, h or P). Fig. 4a shows that the transformation peaks shift gradually to lower temperatures with the increase of scanning speeds. The A->M transformation peak temperature (Mg) of the as-built samples decreases monotonically from 294 to 262 K with the increase of scanning speeds from 400 to 1200 mm s -1 (Fig. 5a), while keeping P = 120 W and h = 80 um unchanged. Fig. 4b shows that solution treatment (1273 K for 2 h) reduces only the transformation interval, i.e. the peaks become sharper, but the position of transformation peaks remains essentially unaffected, as indicated by the M2 temperature of the solution-treated samples in Fig. 5a. Fig. 4c shows that the transformation peaks shift to lower temperatures with the increase of hatch spacing. The Mp temperature of the as-built sample decreases from 290 to 268 K with the increase of hatch spacing from 40 to 110 um (Fig. 5b), while keeping P = 120 W and v = 800 mm s-1 unchanged. After solution treatment, the trend remains (Fig. 4d), and Mo temperature decreases from 294 to 271 K with the increase of hatch spacing (Fig. 5b) Fig. 4c shows that the transformation peaks shift to lower temperatures with the increase of hatch spacing. The Mp temperature of the as-built sample decreases from 290 to 268 K with the increase of hatch spacing from 40 to 110 um (Fig. 5b), while keeping P = 120 W and v = 800 mm s-1 unchanged. After solution treatment, the trend remains (Fig. 4d), and Mo temperature decreases from 294 to 271 K with the increase of hatch spacing (Fig. 5b) Fig. 4e indicates that the transformation peaks of the as-built samples shift to higher temperatures, meanwhile the peaks become sharper with the increase of laser power. The Mp temperature increases from 265 to 285K with the increase of laser power from 60 to 200 W (Fig. 5c), while keeping v = 600 mm s-1 and h = 80 um unchanged. However, the A->M transformation start (Ms) temperature remains essentially unchanged, and varies between 291 and 294 K (Fig. 5c). After solution treatment, the transformation peaks become sharper (Fig. 4f), and the Mp temperature increases from 265 to 284 K with the decrease of the laser power. The M2 temperature decreases slightly from 289 to 277 K (Fig. 5c). The above results indicate that the A .- M transformation temperature of SLM-fabricated NiTi alloys changes monotonically with the respective change of scanning speed, hatch spacing, or laser power. This provides a feasible method to tailor the phase transformation temperature of NiTi alloys by AM. Fig. 5 also shows that the transformation heat associated with the forward A->M transformation (HAM) varies 5 between 21 and 29 J g -1, which is comparable to conventional NiTi materials [44], indicating a full A->M transformation in the SLM-fabricated NiTi samples. consistent with the DSC results in Fig. 5. Fig. 11 also indicates that the variation of scanning speed has more influences on the M2100 temperature as compared with the variation of hatch spacing or laser power. As presented in Fig. 11d, Mg100 decreases by 43 K from 312 to 269 K with the increase of scanning speed from 400 to 1200 mm s-1, while M2100 decreases by only 24 K with the decrease of laser power |
|
train_53 | What is described in this image? | interactions (Figure 4c). These intermolecular interactions propagate through the cocrystal structure to form 2D layers, with each layer making a dihedral angle of 55.6° with the (001) direction with a repetition period equal to the length of the aaxis (8.035 Å; Figure 4a).12 After the phase transition of the crystal into Form I (with new dimensions 0.95 mm × 0.34 mm × 0.05 mm; Figure 2b), the major face of the crystal has changed from the (001) plane of Form II to the (11T) plane of Form I. Layered structure still appears in the Form I crystal, but with remarkably weakened intralayer hydrogen bonds of C- H ... N (d/Å, 0/º: 2.647, 161.2), C-H ... O (d/Å, 0/º: 2.669, 161.5), and C-H ... C (d/A, 0/°: 2.893, 136.4). More importantly, dramatic changes take place after the transition in the stacking pattern of the layers: each layer leans to the (11I) face in Form I crystal with a dihedral angle of 27.7º along a stack axis of nearly [101] direction and a repeat distance of 14.098 Å (Figure 4b). The changes in the packing motifs of the molecular layers-the dihedral angle decreasing from 55.6º in Form II to 27.7º in Form I and the repetition period increasing Figure 4. (a) Crystal packing of Form II (viewed down the b-axis). |
|
train_54 | What is described in this image? | were performed by X-ray diffractometer and given in Fig. 1. The scanning electron microscope (SEM) was used to investigate the micro morphologies of NMK and EVM and introduced in Fig. 2. The physical properties of EVM are summarized in Table 2 NMK has plate like structure and characterized by large length to thickness aspect ratio; it is especially favourable in matrix reinforcement, and the platelet thickness is only 1-20 nm, although its dimensions in length and width can be measured in hundreds of nanometers, with a majority of platelets in 200–500 nm range after purification. Fig. 2. SEM micrographs of (a) NMK and (b) EVM. |
|
train_55 | What is described in this image? | Figure 2 shows a typical H NMR spectrum for a HPCB sample (prepared from dissolved bagasse pulp): the strong peak at 1.0 ppm is assigned to methyl protons, whereas the broad peak from 2.8 to 4.7 ppm is attributed to the cyclic glucose units. 1H NMR spectroscopy was employed for determining the DS of the HPC sample. The DS value was calculated and it was found to be 1.87. Figure 2: 1 H NMR spectrum for the HPCg sample prepared from dissolved bagasse pulp Figure 2 presents the H NMR spectrum of the synthesized HPCB. The prepared HPC spectrum shows signals at 1.2 ppm due to the methyl groups in the hydroxypropyl chain and at 2.8 to 4.5 ppm corresponding to the cyclic glucose units, which are present in both HPCB and its derivatives. Upon derivatization of HPCB, the common signals at around 6.9 and 7.9 ppm are due to aromatic protons. For ABPC-2, the resonance peak observed at 1.33 ppm is attributed to the protons in terminal -CH3 in the alkoxy chain. The signal at 3.9 ppm is assigned to the protons of O-CH2-CH3. ABPC-10 and 12 showed similar absorptions around 0.95 ppm for the terminal -CH3 groups and in the range of 1.1-1.8 ppm for the protons of -CH2 groups in the alkoxy chain. |
|
train_56 | What is described in this image? | fracture surfaces are found in Fig. 3(a,b). The rough surfaces are formed by the shear band propagation along wavy paths. Close examination finds that fracture of a relatively ductile metallic glass sample consists of three stages. As representatively shown by the as-cast sample in Fig. 3(a), as soon as a sharp crack initiate from the interior end of the notch, it propagates rapidly to a short distance because of sudden release of the stored energy, as indicated by Stage I. Subsequent crack propagation is slow and branches sideward due to the blunting effect of the developed plastic deformation. This forms a largely extended and rather rough fracture region, as indicated by Stage II. With further increase of the external load, the crack propagates rapidly and catastrophically. On the contrary, bending tests on samples annealed for 21 and 168 hours give rise to relatively flat fracture surfaces, as demonstrated in Fig. 3(c,d). Particularly, fracture surface of the 168 hour-annealed sample exhibits a mirror finish. In these two cases, the intrinsic plasticity has little resistance to the crack propagation, and cracks will propagate rapidly throughout the entire sample once initiated. fracture surfaces are found in Fig. 3(a,b). The rough surfaces are formed by the shear band propagation along wavy paths. Close examination finds that fracture of a relatively ductile metallic glass sample consists of three stages. As representatively shown by the as-cast sample in Fig. 3(a), as soon as a sharp crack initiate from the interior end of the notch, it propagates rapidly to a short distance because of sudden release of the stored energy, as indicated by Stage I. Subsequent crack propagation is slow and branches sideward due to the blunting effect of the developed plastic deformation. This forms a largely extended and rather rough fracture region, as indicated by Stage II. With further increase of the external load, the crack propagates rapidly and catastrophically. On the contrary, bending tests on samples annealed for 21 and 168 hours give rise to relatively flat fracture surfaces, as demonstrated in Fig. 3(c,d). Particularly, fracture surface of the 168 hour-annealed sample exhibits a mirror finish. In these two cases, the intrinsic plasticity has little resistance to the crack propagation, and cracks will propagate rapidly throughout the entire sample once initiated. fracture surfaces are found in Fig. 3(a,b). The rough surfaces are formed by the shear band propagation along wavy paths. Close examination finds that fracture of a relatively ductile metallic glass sample consists of three stages. As representatively shown by the as-cast sample in Fig. 3(a), as soon as a sharp crack initiate from the interior end of the notch, it propagates rapidly to a short distance because of sudden release of the stored energy, as indicated by Stage I. Subsequent crack propagation is slow and branches sideward due to the blunting effect of the developed plastic deformation. This forms a largely extended and rather rough fracture region, as indicated by Stage II. With further increase of the external load, the crack propagates rapidly and catastrophically. On the contrary, bending tests on samples annealed for 21 and 168 hours give rise to relatively flat fracture surfaces, as demonstrated in Fig. 3(c,d). Particularly, fracture surface of the 168 hour-annealed sample exhibits a mirror finish. In these two cases, the intrinsic plasticity has little resistance to the crack propagation, and cracks will propagate rapidly throughout the entire sample once initiated. Figure 3. Fracture surfaces of the as-cast sample in (a) and samples annealed at 300°C for 9 hours in |
|
train_57 | What is described in this image? | It can be seen from Fig. 6 that, with increasing the crosslink density in the first-formed PU network, the transition This indicated that the increase in crosslink density of the first-formed PU network obstructs phase separation and increases component mixing. Compared with Fig. 6, Fig. Fig. 6. dC./dT versus temperature signal for the 70 : 30 PU/PEMA IPNs crosslinked with different PU network crosslink levels (PPG:TMP). The PEMA networks were crosslinked with 5 mol% TEGDM. |
|
train_58 | What is described in this image? | Electrooptical properties of eutectic mixtures. At 35 °C all eight tricomponent mixtures except mixture W-240 are orthoconic having strictly 45° tilt, as demonstrated by rotating the cells between crossed polarizers without changing of quality of the dark state (Fig. 7). The electrooptical response characterization of the all eight tricomponent mixtures is presented in ref. 26. In this work we present electrooptical results for cells filled with the mixture W-242 having the lowest melting point, see Fig. 8 as an example. This characterization consists of recording low frequency (0.1 Hz) hysteresis curves using AC triangular voltage signals with different amplitudes. The results in Fig. 8a show that the hysteresis loops are symmetric, the observed threshold voltage and saturation voltage are Vth = 17 V and Vsat. = 21 V Fig. 7 Observed texture of rubbed cell filled with W-242 between crossed polarizers when the cell is in the OFF state and in the ON state. |
|
train_59 | What is described in this image? | PGA = 309 K, PLLA = 332 K, and PTMC = 261 K [31] In particular, Eq. 2 calculates the Tg of terpolymers with same composition as those investigated in this work, and the obtained values are plotted in a bar graph in Fig. 6, where they are compared with the experimental DSC and DMTA data. It is clear that the calculated values follow the same trend with composition as the experimental Tg, showing that the modified Fox equation (Eq. 2) can be used to predict, with good approximation, the glass transition of the terpolymers as a function of comonomer content. A range of glass transition temperatures, achieved by targeted variations of the relative content of the three monomers, is accessible to this terpolymers system leading to the materials with tunable physical properties. Figure 6. Glass transition temperature of terpolymers: experimental data from DSC, DMTA, and calculated values from the Fox equation. |
|
train_60 | What is described in this image? | Fig. 10 illustrates the magnetization hysteresis loops of the ballmilled Ni-Mn-Ga powder and sintered samples measured at room temperature (25 °C). The hysteresis loops confirm that the used powder and sample sintered in argon atmosphere exhibited ferromagnetic behaviors at room temperature. The measured values of saturation magnetization (Ms), coercivity (Hc) and remanent magnetization (Mr) of the powder and sintered samples are given in Table 4. The measured coercivity of the powder and samples sintered in vacuum and argon atmospheres were 359 mT, Fig. 10. Magnetic hysteresis loops measured at 25 °C for ball-milled Ni-Mn-Ga powder, and sintered samples in vacuum and argon atmospheres. Inset is a magnified view of the origin. Table 4 Calculated magnetic properties of the ball-milled Ni-Mn-Ga powder 'A', and sintered samples in vacuum 'B' and argon 'C' atmospheres from Fig. 10. |
|
train_61 | What is described in this image? | Figure 6. Emission wavelength of the repeated vapochromic behavior by grinding (around 545 nm) and exposing to ether (around 592 nm) treatments (excited at 365 nm). the formed orange sample further converted to green when the exposure time was long enough (over 0.5 h, d process). After the produced green emissive sample iv was ground, the conversion of vapochromic luminescence could be readily repeated. The reversibility of emission changes was confirmed by the repeated grinding-vapor exposing processes (Figure 6 and Figures S5 and S6 in the Supporting Information). The emission peaks of the orange and green states appeared at 592 and 545 nm, respectively, and the two emissive states could be easily and mutually switched. XRD and thermogravimetric analysis (TGA) experiments have been performed on the samples exposed to the solvent vapors. As shown in the XRD spectra (Figures S7 in the Supporting Information), the samples obtained after exposure to ether and THF vapors are two crystalline states with obviously different diffraction patterns. The orange material from ether vapor exhibited the same XRD pattern as the heated solid, suggesting that they have similar molecular-packing structures. TGA curves (Figures S8 in the Supporting Information) showed that the green sample from THF vapor lost 4.40% in weight between 129 and 156 °C, while the orange sample did not exhibit such a transition process. The lost weight can be attributed to the loss of THF vapor molecules, and the mole ratio (THF/ |
|
train_62 | What is described in this image? | Figure 1. Growth rates of the various compounds plotted after (a) normalizing to the glass transition temperature (T.) and (b) normalizing to the melting temperature (In). Growth rates of the different compounds are color coded on the basis of whether they are class I and II (red symbols) or class III (blue symbols). Classification is based on the crystallization behavior during cooling of the melt and subsequent heating using the method described previously.3 Growth Rate of Compounds. The growth rates of the various compounds are shown in Figure 1. Since the different compounds studied all have different glass transition and melting temperatures, it is necessary to normalize the temperature scale to allow an appropriate comparison of the growth rates. The normalization can be done either with respect to the T (normalizing for molecular mobility and assuming that all compounds have the same mobility at Tx) or with respect to the Tm (normalizing for differences in the extent of undercooling which influences the thermodynamic driving force). T/Tg and △T, i.e., (Tm - T), were used as the two temperature normalization approaches. Figure la shows the data which has been normalized to To, while Figure 1b shows the normalization based on the extent of undercooling. It can be seen that when normalized to Tg the growth rates of the fastest and slowest growing compounds vary by about 4 orders of magnitude, while the variation is about 5 orders of magnitude difference when normalized with respect to △T. It can also be observed that the relative order of the compounds changes when normalized to different temperature scales. For example, when normalized to To the compound with the fastest crystal growth rate is griseofulvin, closely followed by nilutamide, celecoxib, and tolbutamide, while using the undercooling yields acetaminophen and pimozide as the fasted growing compounds. Growth Rate of Compounds. The growth rates of the various compounds are shown in Figure 1. Since the different compounds studied all have different glass transition and melting temperatures, it is necessary to normalize the temperature scale to allow an appropriate comparison of the growth rates. The normalization can be done either with respect to the T (normalizing for molecular mobility and assuming that all compounds have the same mobility at Tx) or with respect to the Tm (normalizing for differences in the extent of undercooling which influences the thermodynamic driving force). T/Tg and △T, i.e., (Tm - T), were used as the two temperature normalization approaches. Figure la shows the data which has been normalized to To, while Figure 1b shows the normalization based on the extent of undercooling. It can be seen that when normalized to Tg the growth rates of the fastest and slowest growing compounds vary by about 4 orders of magnitude, while the variation is about 5 orders of magnitude difference when normalized with respect to △T. It can also be observed that the relative order of the compounds changes when normalized to different temperature scales. For example, when normalized to To the compound with the fastest crystal growth rate is griseofulvin, closely followed by nilutamide, celecoxib, and tolbutamide, while using the undercooling yields acetaminophen and pimozide as the fasted growing compounds. Crystallization from undercooled melts is governed by two processes, nucleation and growth, whereby the overall crystallization kinetics depends on the magnitude of these two processes and their temperature dependencies. Thus, when a compound can readily form a glass, for example, by cooling from the melt, this could occur from a variety of factors including low nucleation rate, low growth rate, a combination of these factors, or poor overlap between the temperature regions where nucleation and growth are favorable. In an effort to deconvolute some of these effects, the bulk growth rates of the various compounds can be compared to their glass forming ability upon cooling of the melt and the glass stability following reheating. Parts a and b of Figure 1 show a plot of growth rates versus temperature whereby the compounds have been color coded on the basis of their GFA/GS assessed using the cooling and heating method described previously.3 Interestingly, several of the compounds which show good glass forming ability and stability (i.e., resistance to devitrification, "class III" compounds) actually had very high crystal growth rates. In fact, the growth rates of the class III compounds span the entire range of growth rates observed and class III compounds had both among the fastest and slowest growth rates for the group of compounds examined. In contrast, those compounds with poor glass stability (class II or I-b compounds whereby class II From a risk assessment perspective, the data shown in Figure 1 is very revealing, assuming that the relative magnitude of growth rates translates reasonably well to the lower temperatures where products are stored. Hence, class III compounds that have very high growth rates (Figure 1, compounds with blue symbols that populate the upper half of the figure) clearly have good glass forming ability because of a low tendency to form nuclei under the conditions of the experiment. However, it should be noted that, during the processing operations used to make amorphous formulations, residual or process-induced nuclei may be present in the system. In this instance, the system may have a high probability of undergoing crystallization over the shelf life of the product, since the crystal growth rate is relatively high. In contrast, class III compounds with inherently low growth rates (Figure 1, compounds with blue symbols that populate the lower half of the figure) will exhibit much slower crystallization kinetics, even if nuclei are present. Clearly, compounds with poor glass stability (class II and class I-b, compounds with red symbols) are already in the higher risk category with fast growth rates. Therefore, we can generate an extended classification that provides an improved picture of the crystallization tendency of a compound, taking into account both the nucleation and growth behavior. From a risk assessment perspective, the data shown in Figure 1 is very revealing, assuming that the relative magnitude of growth rates translates reasonably well to the lower temperatures where products are stored. Hence, class III compounds that have very high growth rates (Figure 1, compounds with blue symbols that populate the upper half of the figure) clearly have good glass forming ability because of a low tendency to form nuclei under the conditions of the experiment. However, it should be noted that, during the processing operations used to make amorphous formulations, residual or process-induced nuclei may be present in the system. In this instance, the system may have a high probability of undergoing crystallization over the shelf life of the product, since the crystal growth rate is relatively high. In contrast, class III compounds with inherently low growth rates (Figure 1, compounds with blue symbols that populate the lower half of the figure) will exhibit much slower crystallization kinetics, even if nuclei are present. Clearly, compounds with poor glass stability (class II and class I-b, compounds with red symbols) are already in the higher risk category with fast growth rates. Therefore, we can generate an extended classification that provides an improved picture of the crystallization tendency of a compound, taking into account both the nucleation and growth behavior. From a risk assessment perspective, the data shown in Figure 1 is very revealing, assuming that the relative magnitude of growth rates translates reasonably well to the lower temperatures where products are stored. Hence, class III compounds that have very high growth rates (Figure 1, compounds with blue symbols that populate the upper half of the figure) clearly have good glass forming ability because of a low tendency to form nuclei under the conditions of the experiment. However, it should be noted that, during the processing operations used to make amorphous formulations, residual or process-induced nuclei may be present in the system. In this instance, the system may have a high probability of undergoing crystallization over the shelf life of the product, since the crystal growth rate is relatively high. In contrast, class III compounds with inherently low growth rates (Figure 1, compounds with blue symbols that populate the lower half of the figure) will exhibit much slower crystallization kinetics, even if nuclei are present. Clearly, compounds with poor glass stability (class II and class I-b, compounds with red symbols) are already in the higher risk category with fast growth rates. Therefore, we can generate an extended classification that provides an improved picture of the crystallization tendency of a compound, taking into account both the nucleation and growth behavior. |
|
train_63 | What is described in this image? | | PDES II | Melts cooled at a rate 2.5℃/ | Fig.5, curves | | | a1 and B1 crystals; ad- | PDES II | Melts cooled at a rate 2.5℃/ | Fig.5, curves | | Additional crystalline | PDES II | Melt crystallized by cooling | Fig.5, curve for | |
|
train_64 | What is described in this image? | was placed in a plastic syringe. Fig. 1 shows the scheme for the melt coaxial electrospinning. PEG was put into a stainless steel syringe that was preheated to 70 °C. PEG melt and PVDF solution Fig. 1. Scheme for melt coaxial electrospinning setup. |
|
train_65 | What is described in this image? | Figure 1. The absolute C, of bulk PS is shown in Figure 1 for different sample weights to verify that the step-scan method gives reliable Cp results and to examine the Cp dependence on the sample weight. For the five samples tested, ranging from 1.93 to 12.99 mg, the standard deviation in C, is less than 0.6%, indicating that our methodology yields Co values independent of the sample size. |
|
train_66 | What is described in this image? | Fig. 9a depicts the variation of dynamic storage modulus (G) of neat TPU and TPU/CNF nanocomposites with frequency. The storage modulus monotonically increases with increase in frequency and also concentration of VGCNF. However, the rate of increase in modulus is less pronounced for the higher nanofiber content than that of lower CNF concentration. The significant enhancement of G' at lower CNF concentration is attributed to the stiffness imparted by the interconnected structures of anisometric nanofibers that allow sufficient apparent yield stress transfer, which is mainly controlled by the fiber-matrix and matrix-matrix interfacial interactions rather than by the reinforcing effect and dimensional rigidity of carbon nanofibers. Beyond certain concentration of nanofiber, improvement in C' is mainly attributed to the interconnected three dimensional network structures of nanofibers within the TPU matrix [34]. The slope of the logarithmic plots between G' and frequency is reduced with nanofiber loading, which indicates diminishing effect of frequency on modulus. The enhancement of G' with nanofiber loading is significantly higher at lower frequency region than that of higher frequency region because low frequency storage modulus increase is dominated by the more dimensionally Fig. 9b exhibits the curves of crossover points (Gc) of storage modulus (G) and loss modulus (Gr) of TPU/CNF nanocomposites at 145 °C as a function of angular frequency. The inverse of angular crossover frequency (@c) at the G' and G' crossover point is associated with a large characteristic dynamic relaxation time (t) [36]. |
|
train_67 | What is described in this image? | Figure 6 TEM morphology in the deformed zone of PLA/MBS blends: (a) 95/5, (b) 93/7, (c) 90/10, (d) 85/15, (e) 80/20, and (f) 75/25. important in notched specimens because it enables the blend to yield at moderate stresses under plane strain conditions 30,31 Deformed morphology inside the fracture zone of PLA/MBS blends was shown in Figure 6. The MBS |
|
train_68 | What is described in this image? | Figure 2. Reversing apparent specific heat capacity of PTFE as a function of temperature between 275 and 315 K obtained by TMDSC on continuous heating with an underlying heating rate of 0.4 K min-1; frequencies of 2m/240, 2m/120, and 2m/60 rad s-1; and modulation amplitudes of 0.1 and 1.0 K. Figure 2 depicts the reversing apparent specific heat capacity of PTFE as a function of temperature between 275 and 315 K. Data were taken on continuous heating with an underlying rate of (q) = 0.4 K min-1 and a sawtooth modulation of the program temperature. Measurements were performed at modulation periods of 240, 120, and 60 s and at modulation amplitudes of 0.1 and 1.0 K. The most striking observation is the decreasing magnitude of the reversing apparent specific heat capacity with increasing modulation amplitude for the phase transition at 292 K and its constancy versus the modulation amplitude for the phase transition at 303 K. Furthermore, the maximum of the low-temperature-transition peak at 292 K decreases with increasing frequency, whereas the transition at 303 K is not affected by the modulation frequency. frequency (Fig. 2),and no effect on the transition at 303 K. Quasi-isothermal TMDSC and a comparison with the standard DSC in Figures 3 and 4 confirm the different characters of the two transitions. For the low-temperature transition, the reversing apparent specific heat capacity decreases within the decreasing modulation amplitude (Fig. 4) and decreases with ongoing time with an underlying nonzero heating rate (Fig. 2) |
|
train_69 | What is described in this image? | (2A = (h(0-Ex(T)2 where w = 2nc/2, 2 is the wavelength of incident photons. The Eg(T) values of the PNC films were deduced from the A1/2/2, versus 1/2 plots as shown in Fig. 9. The intersection of the extrapolated linear portion of these curve gives the values of gap wavelength 2% from which the Eo(T) values of these materials were calculated using the following relation; Fig. 9. A1/2/2 versus 1/2. plots of (PVA-PVP)-x wt% ZnO polymer nanocomposite films |
|
train_70 | What is described in this image? | Fig. 6 summarizes the evolution of Ms and Mp temperatures with respect to the increase of energy density (Ev). The increase of Ev is achieved by decreasing scanning speed, increasing laser power, or decreasing hatch spacing, respectively, while keeping other SLM process parameters unchanged. It is clear that the MTTs increase monotonically with the increase of energy density, as frequently reported in previous studies [10,33,35,37,49-52]. However, the transformation temperature differs between the samples fabricated under the same energy density but different combination of SLM process parameters, especially under the higher energy density level. As shown in Fig. 6, the Mn temperature increases by 32 K from 262 to 294 K with the increase of Ey from 41 to 125 J mm-3 by reducing scanning speeds from 1200 to 400 mm s1, while the Mg temperature increases only for 18 K from 265 to 283 K with the increase of E, from 41 to 125 J mm 3 by increasing laser power from 60 to 180 W. Fig. 6 summarizes the evolution of Ms and Mp temperatures with respect to the increase of energy density (Ev). The increase of Ev is achieved by decreasing scanning speed, increasing laser power, or decreasing hatch spacing, respectively, while keeping other SLM process parameters unchanged. It is clear that the MTTs increase monotonically with the increase of energy density, as frequently reported in previous studies [10,33,35,37,49-52]. However, the transformation temperature differs between the samples fabricated under the same energy density but different combination of SLM process parameters, especially under the higher energy density level. As shown in Fig. 6, the Mn temperature increases by 32 K from 262 to 294 K with the increase of Ey from 41 to 125 J mm-3 by reducing scanning speeds from 1200 to 400 mm s1, while the Mg temperature increases only for 18 K from 265 to 283 K with the increase of E, from 41 to 125 J mm 3 by increasing laser power from 60 to 180 W. Fig. 6. Variation of martensite transformation start (M,) temperature and peak It is simple to assume that the Ni-loss increases with the increase of input energy density (i.e. E.), leading to the increase of MTTs. This has also been reported frequently in literature [10,33,35,37,49-52]. However, in our previous work [36,55], a large variation of martensite transformation temperature (Mp changes between 205 and 277 K) has been observed even under the same energy density (100 J mm -3), but different combination of laser power, scanning speed and hatch spacing. In this work, as shown in Fig. 7, different transformation behavior is also observed between the samples fabricated under the same energy density but different combination of SLM process parameters, especially under a high energy density (e.g. 125 J mm-3 in Fig. 7b). Moreover, as demonstrated in Fig. 6, with the increase of energy density from 41 to 125 J mm 3, the change of scanning speeds shows more pronounced influence on MTTs than the change of laser power. Fig. 13 also indicates that the Ni concentration is more sensitive to the change of scanning speed, as compared with the change of hatch spacing or laser power. |
|
train_71 | What is described in this image? | D974-12. In this method, the acid number is measured as the quantity of KOH (in mg) which is required to reach the equivalent point when titrating 1 g of the resin dissolved in xylene/isopropyl alcohol solvent. Figure 4 demonstrates the acid number of reaction mixture in the first step for FDCA/ Fig. 4 The acid number curves from acid-base titration for resins |
|
train_72 | What is described in this image? | Figure 1(a) shows the specific heat flow versus temperature curve while initially heating and subsequently cooling PLA in the "as-printed" state. The measurement starts at ambient temperature using a heating rate of 10 K/min. A (cold) crystallization is an exothermic process as the value of specific heat shows a dip-like feature. As melting is an endothermic process a peak feature develops. The melting/crystallization temperature can be determined in two different ways: firstly, the peak-temperature and, secondly, the onset temperature. The entropy of a transition is determined by dividing the integrated peak-area in the temperature dependent heat flow plot by the temperature rate. A glass transition causes a change in heat capacity leading to a steplike feature in the temperature dependent heat flow. The onset method and the half height of this step-like feature are both used frequently to determine the glass transition temperature Tg. In our case we focus on the onset temperatures but also providing To determined by the half-height method in Figure 1(a). Figure 1(b) shows DSC heating curves for "as-printed" double peak feature due to the melting of the polymer follows. The enthalpies of cold crystallization and melting (approx. 25 J/g for "as-printed" and 23 J/g for "amorphous" PLA) are nearly identical, allowing the conclusion that both samples are below To in a purely amorphous state. Compared to the DSC result of Figure 1(a) the enthalpy of "as-printed" PLA is about 1.5 times higher, which originates from an increased degree of crystalline phase (about 30%) during heating with a rate of 5 K/min. Also, the melting feature exhibits two distinct maxima, which arise from two melting processes. The reason for that can be the lower heating rate of 5 K/min, leading to a separation of two melting processes. These two processes are based on different crystalline structures, which arise again from the low heating or cooling rate through the (cold) |
|
train_73 | What is described in this image? | (David 1977). The introduction of Pb in Se-Te system reduces the effective bond energy of [(Se-Se) + (Se-Te)- ((Se-Pb) + (Te-Pb))] = 11-1 kcal/mol. Hence increase of Pb at.% in the Se-Te system causes the decrease of Tg in the system. A similar decreasing trend has also been shown (figure 3) by T. as the atomic wt.% of Pb increases in the Se-Te-Pb system. Figure 3. |
|
train_74 | What is described in this image? | (typically ca. 60 ℃). Below the crystallization temperature, the situation is different of course; but, we have chosen a very low molecular weight PEO to circumvent the interference of crystallization. Figure 5 shows a photograph of a piece of the 50:50 blend at room temperature; it is completely transparent. Figure 5. Photograph of a solvent-cast film of the 50/50 blend of PEO/PMMA. Wood) appreciates support of the Institute of Technology at the University of Minnesota for an Undergraduate Research Opportunity Scholarship. We thank Sahban Ozair for providing the photograph in Figure 5. |
|
train_75 | What is described in this image? | DSC curves (heat flow signal) for the low Figure 2 and high molecular weight PEO/PMMA blends at 40, 60, and 80 wt % PEO. Figure 2 shows the heat flow signals for the melting endotherms of the semicrystalline blends. |
|
train_76 | What is described in this image? | Figure 1 shows typical stress-strain curves for virgin PLA, PLA/PEG blend and their blend nanocomposites. It is observed from Fig. 1 that the virgin PLA shows brittleness behavior with a strain of 2.9%, whereas incorporation of PEG as a plasticizer into PLA renders ductile behavior in the virgin matrix. The significant increase in strain to 330.13% with the decreased strength and modulus of 23.24 MPa and 415 MPA was observed at 20 wt% Figure 1 shows typical stress-strain curves for virgin PLA, PLA/PEG blend and their blend nanocomposites. It is observed from Fig. 1 that the virgin PLA shows brittleness behavior with a strain of 2.9%, whereas incorporation of PEG as a plasticizer into PLA renders ductile behavior in the virgin matrix. The significant increase in strain to 330.13% with the decreased strength and modulus of 23.24 MPa and 415 MPA was observed at 20 wt% |
|
train_77 | What is described in this image? | The thermotropic behavior of mixtures of two PCs differing in the nature of their fatty acyl constituents has been investigated. Disaturated PCs differing by only two carbons in the length of their hydrocarbon chains exhibit almost ideal behavior in binary phospholipid-water dispersions (see Fig. 3). Although a difference in chain length of four carbons presents a system considerably removed from ideality, isothermal melting of the shorter-chain PC is not observed and a significant degree of lateral phase separation does not occur (but see Ref. 83). A difference in hydrocarbon chain length of six carbons results in monotectic behavior, with the chain-melting onset temperature remaining constant over most of the concentration |
|
train_78 | What is described in this image? | for constant O-acyl chain length (see Fig. 6, A and B). The incremental values and end contributions are 0.925 ± 0.041 kcal/mol/CH2, -2.65 ± 0.64 kcal/mol and 2.43 ± 0.14 cal/mol/K/CH2, -2.9 ± 2.2 cal/mol/K for the transition enthalpy and entropy, respectively. The "end contributions" For N-acyl DPPEs, by taking the transition temperature for N-16 DPPE together with those for other DPPE derivatives from N-10 to N-18 (Akoka et al., 1988; Lafrance et al., 1990), the dependence on the N-acyl chain length can also be fit by Eq. 4 (see Fig. 6 C). This yields values of T = 361.3 K, no - n' = 0.665 and n' = 6.003 (x2 = Figs. 4 and 6). It is assumed that the contribution from the 0-acyl chains is linearly dependent on nº with a constant end contribution, as for normal diacyl PEs (see Seddon et al., 1983a). It is further assumed that the contribution from the N-acyl chains is linearly dependent on n", but with an end contribution that is linearly dependent on the difference or mismatch, nº - nN, between the lengths of the O-acyl and N-acyl chains (see Fig. 6). This deficit arising from chain mismatch is similar to that introduced previously for mixed-chain diacyl phospholipids (Marsh, 1992). |
|
train_79 | What is described in this image? | In Fig. 1(a) and (b) are shown typical DSC It was mentioned earlier in the text that the glass transition of polystyrene carries with it a positive heat effect. In differential scanning calorimetry such heat effects can readily be determined by comparing endothermic areas in the DSC thermograms (Fig. 1) with corresponding areas obtained for the fusion of indium whose enthalpy of fusion per unit weight is very well known. The AH values (in cal g-1), |
|
train_80 | What is described in this image? | Figure 13. Deviation range of phase transition temperature for the hydrated salt-based PCM. |
|
train_81 | What is described in this image? | It is also considered a powerful method for studying the conformational changes in biopolymer systems [35]. The FTIR spectra of pure PVA and its blends at various PEG loadings in the wave number range of 4000-500 cm-1 are shown in Figure 1(a). Both polymers have good solubility in water. The characteristic absorption peaks of PVA/PEG blends that were observed at wavelengths 1330, 1421, 1100, 3300, and 851 cm-1 correspond respectively to C-O-C, CgHo, C- C, -OH, and C-H [39]. A strong absorption peak was also observed at 2900 cm-1 and linked to the stretching mode of the CH2 group [36]. The absorption band at 1650 cm-1 was due to C=O stretching of the ester group formed in the PVA polymer during its preparation process. At higher PEG loadings above 10%, this peak disappeared due to the presence of a high amount of PEG. The stretching vibrations of C-C and C-O-C were observed at 1100 and 1330 cm-1 in the spectra, and their intensity values were changed at different PEG loadings. From Figure 1(b), the absorption band of |
|
train_82 | What is described in this image? | addition, the thermal conductivity increases with temperature linearly especially at the low density samples. The profiles indicate that the thermal conductivity of the specimens are weak function of temperature since the maximum change percentage of thermal conductivity with temperature is 22.7, 22.4, 20.4 and 22.9 for specimens D, C, B and A, respectively. The ASTM standard for insulation material is also shown in Fig. 5 for comparison with the thermal conductivity of the specimens. The thermal conductivity variations with density at different temperatures are shown in Fig. 6. The figure indicates that at constant density, the thermal conductivity increases with temperature increase. It should be noted that Wei at el. [38] observed similar behavior of thermal conductivity variation with temperature and density for insulation material made from rice straw. Furthermore, similar trends of thermal conductivity profiles have been obtained by other authors [38,39]. Fig. 6. Thermal conductivity profiles at specified temperatures versus the density of the specimens. |
|
train_83 | What is described in this image? | For 0.92NBT-0.08BT, with the rise of temperature, the highfield polarization increases and the low-field polarization decreases (Fig. 5). Hence, the calculated AS and AT have opposite signs under high and low applied fields. 3.4. Discussion Previous ECE studies concern the entropy change between dipole-ordered ferroelectric phase and disordered paraelectric |
|
train_84 | What is described in this image? | were investigated by WAXD measurement and the results are illustrated in Fig. 3. Cellulose and pure PLLA show their typical crystallization peaks. PLLA showed the strongest diffraction peak at 20 = 17.0°, whereas cellulose showed the strongest diffraction peak at 20 = 22.4° . However, neither the crystallization peak of PLLA nor that of cellulose was observed on CE-g-PLLA polymers, only a dispersive broad peak around 20 = 16.5°-22.7° was obtained, which indicating that the introduction of acetyl and lactyl groups to cellulose backbone could destroy the original crystallization pattern of cellulose, and the grafted PLA side-chains were not long enough to form a new crystalline structure. Therefore, the amorphous of the grafts has been confirmed. Teramoto et al. [31] showed that CDA-g-PLLA polymers had a crystalline diffraction pattern, which could be caused by the relatively long PLLA side-chains. Fig. 3. WAXD spectra of cellulose, PLLA, and CE-g-PLLA (IA, L6, L8, and I.10). |
|
train_85 | What is described in this image? | The crystallization and melting behavior of PP has been investigated further using various cooling and heating rates. The cooling curves at various rates, from 5 up to 250 °C/min are plotted as a function of the temperature in Fig. 2, which curves are not corrected for the cooling rate. The curves, and by that the onset and peak temperatures, shift towards lower temperatures with increasing cooling rates as expected. The enthalpy of crystallization decreases with increasing cooling rate and by that also the crystallinity. The lowest cooling rates induce a rather narrow crystallization peak, while the highest cooling rates provoke broad crystallization curves. Though this broadening could be explained by the fast cooling rate overruling the increased overall crystallization rate (which is the result of the combined influence of increased nucleation and growth rates at increasing supercoolings), it could well be that also the temperature gradient within the sample is increasingly playing a role, see further on. Fig. 2. Crystallization of PP at various cooling rates, not corrected for the cooling rate. |
|
train_86 | What is described in this image? | with (1/7p), yields also the crystallization activation energy, Ec, as shown in Fig. 9. The calculated value of Ec giving by using this assumption is 73 kJ/mol. Fig. 9. (0) In[a/(Tp = To)] versus (1000/7,) for GasSe95 glass. (.) In(a/Tp) versus (1000/Tp) for GasSe95 glass. |
|
train_87 | What is described in this image? | (Peppas and Colombo, 1997). The swelling behavior of our co-polymeric hydrogels also depends upon the composition of the gels, particularly when at least one constituent monomer contains ionizable groups. In this case, the increase in ionic monomer within the polymer matrix causes an enhancement in its swelling capacity due to increased chain relaxation as well as osmotic swelling pressure. In the present study, as the monomer acrylic acid is ionic, variation in its concentration in the hydrogel may influence the swelling capacity or water uptake of hydrogel. Almost, the swelling of hydrogel samples was assessed by the measurement of liquid amount absorbed by the material as a function of time until saturation. As an example, the behavior of the hydrogel samples is shown in Fig. 6 for swelling in water and Fig. 7 for swelling in saline solution. Figure 7 Swelling behavior of the poly(AAm)-co-poly(AAc) |
|
train_88 | What is described in this image? | Figure 1 shows the chemical structure of the epoxy resin and the amine. Before being used, DGEBA was placed in a vacuum oven at 80 ℃ overnight to remove any water present and amine was used as received without purification. Figure 1. (a) DGEBA epoxy resin and (b) 4,4'-diaminodiphenylmethane (DDM) structures. |
|
train_89 | What is described in this image? | The glass transition of a system can be observed experimentally by studying the thermodynamic properties of the system. In Fig. 1 the results from the DSC scans obtained for hydrated myoglobin at the two different hydration levels h=0.33 (1A) and h=0.5 (1B), and for myoglobin in the water:glycerol 33:67 wt.% mixture at a total solvent level h = 1 (1C) are shown. It has earlier been shown that the onset temperature of the glass transition in hydrated proteins is almost independent of the hydration level whereas the width of the transition decreases with increased hydration level [25]. In accordance with this, it is obvious that the reduction of the hydration level from h=0.5 (Fig. 3B) to h=0.33 (Fig. 3A) only has a minor effect on the onset temperature, whereas a substantial broadening of the glass transition region occurs from a width (as taken from the onset to the end temperature of the transition) of 45 K to a width of about 85 K for the higher compared to the lower hydration level, respectively. From these figures it is also clear that the glass transition temperature To The glass transition of a system can be observed experimentally by studying the thermodynamic properties of the system. In Fig. 1 the results from the DSC scans obtained for hydrated myoglobin at the two different hydration levels h=0.33 (1A) and h=0.5 (1B), and for myoglobin in the water:glycerol 33:67 wt.% mixture at a total solvent level h = 1 (1C) are shown. It has earlier been shown that the onset temperature of the glass transition in hydrated proteins is almost independent of the hydration level whereas the width of the transition decreases with increased hydration level [25]. In accordance with this, it is obvious that the reduction of the hydration level from h=0.5 (Fig. 3B) to h=0.33 (Fig. 3A) only has a minor effect on the onset temperature, whereas a substantial broadening of the glass transition region occurs from a width (as taken from the onset to the end temperature of the transition) of 45 K to a width of about 85 K for the higher compared to the lower hydration level, respectively. From these figures it is also clear that the glass transition temperature To In Fig. 2 typical dielectric loss spectra are shown for some temperatures. From this figure it is clear that the spectra are complex, and that several relaxation processes are present in the data, but also that contributions from conductivity and electrode polarisation are suppressed due to the use of the teflon film between the sample and one of the electrodes. It should here be noted that some of these relaxation processes, i.e. the low frequency processes at higher temperatures, would not be visible without this teflon film, and thereby, much information about the relaxations in the sample had been lost. Hence, the teflon film made it possible to determine even processes that normally are hidden by the usually large contribution of conductivity and polarisation effects at low frequencies and high temperatures. The relaxation processes in the samples were determined by use of Eqs. (1) and (2), and in Fig. 3 the temperature dependences of all the obtained relaxation times 7 are shown for Fig. 3. Dielectric relaxation times obtained for myoglobin in water at the hydration level h=0.33 (A) h=0.5 (B), and in the 33:67 wt.% water:glycerol mixture at the solvent level h = 1 (C). From these figures it is clear that the relaxation scenario of the sample at the highest water content (h=0.5) is more complicated than the samples containing less water or a relatively large amount of glycerol. For these samples the fastest and second fastest relaxation processes (denoted process I and II) are due to the relaxation of the solvent, where process I is a weak local relaxation that appears to be universal for supercooled confined and hydration water. The universality of this process is supported by the fastest process shown in Fig. 4. The second fastest process II in Fig. 3, corresponds to the main relaxation of the solvent. In the case of pure water as solvent (Fig. 3A and B), as well as water rich solvents (>50 wt.% water, H. Jansson, R. Bergman, and J. Swenson, unpublished data), this process is also rather universal for water supercooled in confinements, on surfaces and in mixtures, as also shown in Fig. 4. Its anomalous temperature dependence, with a crossover from a high temperature non-Arrhenius behaviour to a low temperature Arrhenius dependence at typically 180±20 K, will be further discussed below. However, the data shown in Fig. 3B From these figures it is clear that the relaxation scenario of the sample at the highest water content (h=0.5) is more complicated than the samples containing less water or a relatively large amount of glycerol. For these samples the fastest and second fastest relaxation processes (denoted process I and II) are due to the relaxation of the solvent, where process I is a weak local relaxation that appears to be universal for supercooled confined and hydration water. The universality of this process is supported by the fastest process shown in Fig. 4. The second fastest process II in Fig. 3, corresponds to the main relaxation of the solvent. In the case of pure water as solvent (Fig. 3A and B), as well as water rich solvents (>50 wt.% water, H. Jansson, R. Bergman, and J. Swenson, unpublished data), this process is also rather universal for water supercooled in confinements, on surfaces and in mixtures, as also shown in Fig. 4. Its anomalous temperature dependence, with a crossover from a high temperature non-Arrhenius behaviour to a low temperature Arrhenius dependence at typically 180±20 K, will be further discussed below. However, the data shown in Fig. 3B From these figures it is clear that the relaxation scenario of the sample at the highest water content (h=0.5) is more complicated than the samples containing less water or a relatively large amount of glycerol. For these samples the fastest and second fastest relaxation processes (denoted process I and II) are due to the relaxation of the solvent, where process I is a weak local relaxation that appears to be universal for supercooled confined and hydration water. The universality of this process is supported by the fastest process shown in Fig. 4. The second fastest process II in Fig. 3, corresponds to the main relaxation of the solvent. In the case of pure water as solvent (Fig. 3A and B), as well as water rich solvents (>50 wt.% water, H. Jansson, R. Bergman, and J. Swenson, unpublished data), this process is also rather universal for water supercooled in confinements, on surfaces and in mixtures, as also shown in Fig. 4. Its anomalous temperature dependence, with a crossover from a high temperature non-Arrhenius behaviour to a low temperature Arrhenius dependence at typically 180±20 K, will be further discussed below. However, the data shown in Fig. 3B suggest that not all hydration water at higher hydrations undergo this crossover, but that a small fraction of it continues to relax by the secondary process (denoted process III in Fig. 3B) also above 180 K. Possible explanations for such a behaviour will also be discussed below. For the sample with 67 wt.% glycerol in the solvent the interpretation of this main solvent process (process II) is considerably easier since it is due to the o-relaxation of the mixed solvent In addition to the solvent processes (i.e. processes I and II) the samples exhibit one or more dielectric relaxation processes located at lower frequencies, see Fig. 3. In the case of the sample with 67 wt.% slowest process (process III, Fig. 3C) probably corresponds to process IV and process III in the myoglobin-water samples of the higher (h=0.5, Fig. 3B) and lower (h=0.33, Fig. 3A) hydration level, respectively. This relaxation process arises above the crossover temperature of the main water relaxation and it is most likely due to the relaxation of polar side groups based on earlier interpretations from measurements of hydrated proteins by time-domain reflectometry [35] and recent observations by quasielastic neutron scattering [36]. Whether these side chains move together with the possible secondary solvent relaxation (process III, Fig. 3B) is still not clear. In the myoglobin sample with the higher hydration level also two slower relaxation processes are observed, where the slowest one (process VI), slowest process (process III, Fig. 3C) probably corresponds to process IV and process III in the myoglobin-water samples of the higher (h=0.5, Fig. 3B) and lower (h=0.33, Fig. 3A) hydration level, respectively. This relaxation process arises above the crossover temperature of the main water relaxation and it is most likely due to the relaxation of polar side groups based on earlier interpretations from measurements of hydrated proteins by time-domain reflectometry [35] and recent observations by quasielastic neutron scattering [36]. Whether these side chains move together with the possible secondary solvent relaxation (process III, Fig. 3B) is still not clear. In the myoglobin sample with the higher hydration level also two slower relaxation processes are observed, where the slowest one (process VI), slowest process (process III, Fig. 3C) probably corresponds to process IV and process III in the myoglobin-water samples of the higher (h=0.5, Fig. 3B) and lower (h=0.33, Fig. 3A) hydration level, respectively. This relaxation process arises above the crossover temperature of the main water relaxation and it is most likely due to the relaxation of polar side groups based on earlier interpretations from measurements of hydrated proteins by time-domain reflectometry [35] and recent observations by quasielastic neutron scattering [36]. Whether these side chains move together with the possible secondary solvent relaxation (process III, Fig. 3B) is still not clear. In the myoglobin sample with the higher hydration level also two slower relaxation processes are observed, where the slowest one (process VI), slowest process (process III, Fig. 3C) probably corresponds to process IV and process III in the myoglobin-water samples of the higher (h=0.5, Fig. 3B) and lower (h=0.33, Fig. 3A) hydration level, respectively. This relaxation process arises above the crossover temperature of the main water relaxation and it is most likely due to the relaxation of polar side groups based on earlier interpretations from measurements of hydrated proteins by time-domain reflectometry [35] and recent observations by quasielastic neutron scattering [36]. Whether these side chains move together with the possible secondary solvent relaxation (process III, Fig. 3B) is still not clear. In the myoglobin sample with the higher hydration level also two slower relaxation processes are observed, where the slowest one (process VI), ²H NMR relaxation data shown in Fig. 4, which we concluded must be due to the dynamics of the interfacial water since it is basically universal and present also in solid systems with only water molecules moving on the given time-scale, has also been suggested [37] to mainly arise from protein dynamics. Although fast local protein dynamics occurs on a similar time-scale as the main water process the small dielectric constant of a protein (s~2~4) compared to that of water (s~80 at room temperature) should ensure that the protein contribution to the dielectric relaxation process is minor compared to that of water. Thus, the fastest and most local protein relaxations are submerged in the main solvent process and only the slower and more global motions may be observable in Fig. 3. As described above, the use of the teflon film made it easier to extract dynamical information of the systems that normally is hidden, or suppressed, by the contribution of conductivity and polarisation effects. In Fig. 3B, above the crossover temperature, a rather unexpected behaviour of the water relaxation is revealed. Whereas the main part of this relaxation seems to follow the, in general observed, VFT behaviour (process IIb), a smaller fraction of the water (h=0.33) is not observable, which may be due to that process III in Fig. 3B is directly or indirectly caused by the small amount of ice present in that sample. Thus, whether this process is due to ice or surface water on ice particles (as suggested in Ref. [38]) and/or protein molecules [14] is still not fully established. reaches a relaxation time of 100 s at about 115 K, which is far below the onset temperature of the broad T2 range. This observation further supports the assignment of this process to a secondary relaxation of the hydration water below the dynamic crossover temperature, since such a secondary solvent process is not expected to participate in the glass transition of the sample. The slowest process (process VI) shown in Fig. 3B, which most likely is due to large scale protein fluctuations since it is found very close to results obtained by hole-burning spectroscopy concerning conformational changes of the protein structure [34], should, however, be one of the main processes responsible for the glass transition of this sample, since this process reaches a relaxation time of 100 s at 185 K, which is close to the inflection point around 190 K shown in Fig. 1B. In the case of pure water as the solvent the crossover in the water dynamics observed at about 170 K in Fig. 3A and B is close to the onset temperature of the glass transition (see Fig. 1A and B). This fact is most likely not a coincidence since the α-relaxation of the hydration water vanish at the crossover temperature and no glass transition related conformational changes of the protein can occur without presence of the &- relaxation in the solvent [13]. Thus, the crossover in the water dynamics, and the associated vanishing of the α-relaxation, seems to cause the glass transition of the protein-solvent system and thereby have important implications for protein dynamics. However, since the interfacial water does not exhibit any clearly observable glass transition (due to this vanishing of the associated α-relaxation before the calorimetric glass transition temperature is reached) the glass transition of protein-water systems is observed as a "freezing-in" of only protein motions. Nevertheless, the surrounding water is responsible for the glass transition of the protein-water system, as discussed above. reaches a relaxation time of 100 s at about 115 K, which is far below the onset temperature of the broad T2 range. This observation further supports the assignment of this process to a secondary relaxation of the hydration water below the dynamic crossover temperature, since such a secondary solvent process is not expected to participate in the glass transition of the sample. The slowest process (process VI) shown in Fig. 3B, which most likely is due to large scale protein fluctuations since it is found very close to results obtained by hole-burning spectroscopy concerning conformational changes of the protein structure [34], should, however, be one of the main processes responsible for the glass transition of this sample, since this process reaches a relaxation time of 100 s at 185 K, which is close to the inflection point around 190 K shown in Fig. 1B. In the case of pure water as the solvent the crossover in the water dynamics observed at about 170 K in Fig. 3A and B is close to the onset temperature of the glass transition (see Fig. 1A and B). This fact is most likely not a coincidence since the α-relaxation of the hydration water vanish at the crossover temperature and no glass transition related conformational changes of the protein can occur without presence of the &- relaxation in the solvent [13]. Thus, the crossover in the water dynamics, and the associated vanishing of the α-relaxation, seems to cause the glass transition of the protein-solvent system and thereby have important implications for protein dynamics. However, since the interfacial water does not exhibit any clearly observable glass transition (due to this vanishing of the associated α-relaxation before the calorimetric glass transition temperature is reached) the glass transition of protein-water systems is observed as a "freezing-in" of only protein motions. Nevertheless, the surrounding water is responsible for the glass transition of the protein-water system, as discussed above. For the myoglobin sample in a mixed water-glycerol solvent, a somewhat different scenario for the glass transition is revealed. In this case the main solvent relaxation (process II in Fig. 3C), and the fastest clearly distinguishable protein process (process III in Fig. 3C) reach a relaxation time of 100 s (i.e. a dynamical glass transition) at about 160 K and 174 K, respectively, which is in almost perfect agreement with the onset temperature and the inflection point of the calorimetric Tg at 165 K and 175 K, respectively, shown in Fig. 1C. From a comparison of the DSC data on the myoglobin sample in the mixed water–glycerol solvent (Fig. 1C) with the corresponding data on the myoglobin samples in pure water (Fig. 1A and B) it is evident that the step in T2 is larger and the inflection point is considerably closer to the lower end of the To range for the glycerol containing sample. This suggests that the freezing-in of the α-relaxation in the water-glycerol solvent makes a major contribution to the calorimetric To of this sample, in contrast to the glass transition of the myoglobin samples in pure water where the main contribution, as discussed above, seems to arise from large scale conformational motions in the protein. For the myoglobin sample in a mixed water-glycerol solvent, a somewhat different scenario for the glass transition is revealed. In this case the main solvent relaxation (process II in Fig. 3C), and the fastest clearly distinguishable protein process (process III in Fig. 3C) reach a relaxation time of 100 s (i.e. a dynamical glass transition) at about 160 K and 174 K, respectively, which is in almost perfect agreement with the onset temperature and the inflection point of the calorimetric Tg at 165 K and 175 K, respectively, shown in Fig. 1C. From a comparison of the DSC data on the myoglobin sample in the mixed water–glycerol solvent (Fig. 1C) with the corresponding data on the myoglobin samples in pure water (Fig. 1A and B) it is evident that the step in T2 is larger and the inflection point is considerably closer to the lower end of the To range for the glycerol containing sample. This suggests that the freezing-in of the α-relaxation in the water-glycerol solvent makes a major contribution to the calorimetric To of this sample, in contrast to the glass transition of the myoglobin samples in pure water where the main contribution, as discussed above, seems to arise from large scale conformational motions in the protein. |
|
train_90 | What is described in this image? | Fig. 6(a, b) show the XRD scans of pure PVA/PVP (50/50) blend and PVA/PVP blend filled with various mass fractions of chitosan filler. The observed diffractograms exhibit an amorphous feature which is characterized by two halos centered at about 20=12.8° and 20.1° characteristic of the (101) and (020) planes of semicrystalline (crystalline and amorphous) nature of PVA/PVP blend films, respectively [27]. The present X-ray scans revealed no significant change in the position of two halos and after complexation with filler, the intensity of the blend diffraction peaks is further decreased. This is because the interactions between the blend and filler which leads to a decrease in the intermolecular interaction between the blend chains and as well as the crystalline degree [14]. From Fig. 6(b) the XRD diffractograms a crystalline peak is observed at 20=8.64° and 19.4° were observed for pure PVP. The XRD diffractograms in Fig. 6(b) shows a small sharp peak at about 20=19.7° and clear sharp peak at 32.8° resulting from the crystalline phase with the polymeric matrix, due to increasing of chitosan content. These scattering angles which may be associated with the reflections |
|
train_91 | What is described in this image? | First term represents the energy used for wall pore deformation, the second one represents the energy required for melting a volume fraction f" of salt, and the third one is the term of sensible heat accumulation. Such three terms are represented in Fig. 6. One notices that mechanical energy is negligible compared to the total Fig. 6. Evolution of the stored energy within the pore during melting. |
|
train_92 | What is described in this image? | 3.1 Crystallization of a and y-phase PVDF films using DMSO solvent Figure 1 shows the X-ray diffraction pattern of PVDF In figure 1(b), the maximum intensity peak is observed at 19-9 (20 values) along with peaks at 17-7 and 18-4 (20 values), which belong to a-phase. Therefore only aphase exists in PVDF films, cast at room temperature from solution at 50°C. Figure 1. X-ray diffraction pattern of PVDF films. Thin film cast at room temperature from 15 wt% DMSO solution at (a) |
|
train_93 | What is described in this image? | Figure 1. Change in swelling ratio of different silk/HA hydrogels with time. The swelling times are shown in a log scale. The number after SH means the weight percentage of silk fibroin in the silk/HA blends, e.g., SH80 is the sample with silk (wt)/HA (wt) = 80:20. Each data point is averaged from three samples with error bars as shown in the figure, when larger than the size of data symbols. where Wo is the initial weight of the dried hydrogel scaffold at time t = 0, and Wt is the weight of the hydrated hydrogel at selected time, t. Each data point (in Figure 1) was obtained by averaging values from three samples under the same conditions, with error bars shown. blend hydrogels was determined in aqueous solution. The swelling ratios of the silk/HA hydrogels with different swelling times (5, 20, 40, 100, 360 (6 h), 1140 (19 h), 7200 (120 h), and 11520 min (8 days)) are plotted in Figure 1. The trend of swelling ratio with time was plotted on a log scale to show long times for the swelling behavior. At short swelling times |
|
train_94 | What is described in this image? | PS film holding the PS nanorods were vacuum filtered using excess deionized (DI) water and then dried in vacuo at 50 °C for 24 h. For the Flash DSC sample, the PS nanorods are separated from the excess PS film by delicately cutting them with a scalpel. SEM images of unsupported PS nanorods are shown in Fig. 1. Images were captured using a Hitachi S-4300 high resolution SEM after removal of the AAO template and both before and after the separation of nanorods from the excess PS film substrate. |
|
train_95 | What is described in this image? | The glass transitions of fiber reinforced composites are primarily influenced by the matrix material. Polybenzoxazines generally show higher T2 because of hydrogen bonding arising when the strained ring structure is converted to an open chain structure containing phenolic OH groups. The hydroxyl protons can form hydrogen bonds with nitrogen of the Mannich bridge as well as with adjacent hydroxyl group causing both inter and intra molecular hydrogen bonding [19]. The tan & peak (Fig. 7) shifted to lower temperature with incorporation of jute fibers. The drifting of tan ô to lower temperature is akin to the plasticizing effect. Plasticizers normally reduce the attractive forces between the polymer |
|
train_96 | What is described in this image? | As shown in Fig. 4 and Table 2, according to ellipsometry the 50/ 50 wt% PPO/PS blend has the broadest glass transition region; this outcome differs from DSC results which show that the 85/15 wt% PPO/PS blend has the largest Tx breadth with ATg = 20.3 °C by the heat flow method and ATg = 35.6 °C by the first derivative method. Fig. 4. Thermal expansivity as a function of temperature, calculated through numerical differentiation of T-dependent ellipsometry thickness data for bulk PPO/PS blends with 40-60 wt% PPO. Smoothed data of thermal expansivity using a 12-point adjacentaverage method are shown as red lines. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) |
|
train_97 | What is described in this image? | Ti50Ni35Cu15 (22=0.995),125) and Ti50Ni39Pd11 (22=1.008) alloys were also prepared and characterized by the same methods as the quaternary Ti-Ni-Cu-Pd SMAs. Earlier measurements have established both Ti50Ni35Cu15 and Ti50Ni39Pd11 as the alloys with the lowest 22 values within the corresponding ternary system.[25] Figure 5a shows the normalized R(T) curves of the bulk alloys The characteristic shapes of the R(T) curves for ternary and quaternary bulk alloys closely resemble those observed for thin films (Fig. 3). The reversible phase transformation for the quaternary Ti502Ni34.4Cu12.3Pd3.1 alloy was confirmed by temperature-dependent X-ray diffraction (XRD(T)), as shown in Figure 5b. The XRD(T) spectra recorded during heating from 0 to 120℃ show a phase transformation from an orthorhombic martensite (B19cu) to austenite (B2) between 60 and 70℃ and no precipitates. Similarly, the reverse phase transformation was observed to occur during cooling (not shown here). Thus, we have demonstrated the ability to transfer the thinfilm results to bulk, based on the composition-structure-property relationship determined using the combinatorial thin film approach. Figure 5. Phase-transformation characteristics of bulk alloys. a) Temperature-dependent ACPD measurements of TigNigNigو Tisa2Ni34.4Cu123Pdx1, and b) XRD pattern of Ti92Ni34Cu12.9Pd3.1 upon heating from 0 to 120 ℃. R(T) curves and spectra are offset for clarity. |
|
train_98 | What is described in this image? | The dynamic temperature program and the corresponding heat flow curve can be seen in Figure 4a. Generally, it is accompanied with two isothermal periods at the starting and ending temperatures with a heating ramp in between. The difference between the two temperatures could be up to 150 ℃. One can adjust the isothermal period and heating rate according to the test. In the dynamic mode, the enthalpy is determined by integrating the area under the heat flow curve. Isostep or stepwise method is a combination of short dynamic stages and short isothermal stages. Generally, the temperature increase between two heating stages is small (1-3 ℃) and the heating rate is about 1-2 ℃/min. Thus, the sample has more time to reach a certain temperature compared to the dynamic mode. When the signal goes back to zero, the sample is in an isothermal state. After an isothermal period, the sample experiences a heating ramp. The temperature evolution in the step mode and the corresponding heat flow curve can be seen in Figure 4b. In the step mode, the storage capacity is calculated by adding the value of each step. Ferrer et al. [43] introduced another heating mode suitable for measuring the heat capacity of PCM, named areas method, that consists of consecutive isothermal periods without a heating segment in between. Castellon et al. [45] found that the heating or cooling rate has little influence on the step mode contrary to what is found for the dynamic mode. Therefore, by using the step mode, more accurate results can be obtained. The size of the steps should be long enough to ensure thermal equilibrium within the sample (when the signal goes back to the baseline). Moreover, the authors found out that the results obtained with slow heating rates (0.2 or 0.5 °C/min) are in good agreement with the step mode. Commonly, measurements under the step mode conditions lead to less uncertainty compared to the dynamic mode. However, measuring in the dynamic mode is much closer to the real application of a PCM [46]. Barreneche et al. [1] conducted DSC measurements on two types of common PCMs to determine a suitable operating mode for organic and inorganic PCMs characterization. The drawback of the step mode is the complexity of programming and measurement, plus time-consuming analysis [22,47]. However, in the step mode heating, results dependency to heating rate and sample mass is far lower than that of dynamic mode. In both heating modes, a better temperature resolution can be achieved by lowering heating rate in the dynamic mode and decreasing the step size in the step mode. However, by doing so, the signal to noise ratio increases and affects the accuracy of enthalpy measurement. The dynamic temperature program and the corresponding heat flow curve can be seen in Figure 4a. Generally, it is accompanied with two isothermal periods at the starting and ending temperatures with a heating ramp in between. The difference between the two temperatures could be up to 150 ℃. One can adjust the isothermal period and heating rate according to the test. In the dynamic mode, the enthalpy is determined by integrating the area under the heat flow curve. Isostep or stepwise method is a combination of short dynamic stages and short isothermal stages. Generally, the temperature increase between two heating stages is small (1-3 ℃) and the heating rate is about 1-2 ℃/min. Thus, the sample has more time to reach a certain temperature compared to the dynamic mode. When the signal goes back to zero, the sample is in an isothermal state. After an isothermal period, the sample experiences a heating ramp. The temperature evolution in the step mode and the corresponding heat flow curve can be seen in Figure 4b. In the step mode, the storage capacity is calculated by adding the value of each step. Ferrer et al. [43] introduced another heating mode suitable for measuring the heat capacity of PCM, named areas method, that consists of consecutive isothermal periods without a heating segment in between. Castellon et al. [45] found that the heating or cooling rate has little influence on the step mode contrary to what is found for the dynamic mode. Therefore, by using the step mode, more accurate results can be obtained. The size of the steps should be long enough to ensure thermal equilibrium within the sample (when the signal goes back to the baseline). Moreover, the authors found out that the results obtained with slow heating rates (0.2 or 0.5 °C/min) are in good agreement with the step mode. Commonly, measurements under the step mode conditions lead to less uncertainty compared to the dynamic mode. However, measuring in the dynamic mode is much closer to the real application of a PCM [46]. Barreneche et al. [1] conducted DSC measurements on two types of common PCMs to determine a suitable operating mode for organic and inorganic PCMs characterization. The drawback of the step mode is the complexity of programming and measurement, plus time-consuming analysis [22,47]. However, in the step mode heating, results dependency to heating rate and sample mass is far lower than that of dynamic mode. In both heating modes, a better temperature resolution can be achieved by lowering heating rate in the dynamic mode and decreasing the step size in the step mode. However, by doing so, the signal to noise ratio increases and affects the accuracy of enthalpy measurement. Figure 4. Modes of heating and the corresponding DSC signals: (a) dynamic mode and (b) step mode after [1]. |
|
train_99 | What is described in this image? | The C-C carbon distances in all structures whose intensity data were collected at room and higher temperatures, did not have normal carbon distances as a result of thermal motion of the carbon chains. All carbon distances were then restrained in SHELX to reasonable molecular geometries and the anisotropic displacement parameters restrained to be equal in the direction of the bonds. The crystal structures of the phases stable at room temperature, which are those that did not undergo any phase transitions (1b, 2b, 3b and 4d), are of good quality. The process of transition from one phase to another often resulted in fracturing of the crystals, resulting in high R-factors and R(int) for the remaining structures, necessitating twin laws to be obeyed. The detailed geometric values calculated for these structures should be seen as estimates and viewed qualitatively due to the large thermal motion inherent in long alkyl ammonium cations. Further details of restraints are found in the cif files in the ESI. + Diagrams and publication material were generated using ORTEP,15 PLATON16 and DIAMOND.17 Experimental details of the X-Ray analyses are provided in Table 2. The atomic numbering scheme and anisotropic displacement parameters are shown in Fig. 4 and 5. Crystallographic data are available in the ESI.+ Fig. 4 The asymmetric unit and atomic numbering scheme of the phases of compounds 1-3. The anisotropic displacement parameters are drawn at the 50% probability level for all compounds except for 2c and 3b (30%). The thermal displacement parameters were left isotropic for 1e (30% probability level). The disorder of the alkylammonium chain was omitted in 2c. discussions. In fact, the structure at room temperature, 1c, has the highest interlayer spacing between the inorganic layers, indicative of the structure already being in its highest temperature phase II, even though the temperature is in fact still at room temperature. The conformation of the heptylammonium chain is not planar and considerable thermal motion is evident (Fig. 4 and 11). The torsion angles range from 113(16)° to -179(19)°. The position of the Pb atom and the I atoms were determined in this phase and adjacent inorganic layers are found to be staggered. |
End of preview. Expand
in Dataset Viewer.
README.md exists but content is empty.
- Downloads last month
- 32