jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Guillem Vargas‐Nadal | Mariana Köber | Audrey Nsamela | Francesca Terenziani | Cristina Sissa | Silvia Pescina | Fabio Sonvico | Amirah Mohd Gazzali | Habibah A. Wahab | Luca Grisanti | Marı́a Eugenia Olivera | María Celeste Palena | María Laura Guzmán | Laura Carolina Luciani-Giacobbe | Alvaro F. Jimenez‐Kairuz | Nora Ventosa | Imma Ratera | Kevin D. Belfield | Ben M. Maoz
Source: Pharmaceutics (review, 2022-11-17)
Field: Materials Science — Materials Chemistry

Fluorescent Multifunctional Organic Nanoparticles for Drug Delivery and Bioimaging: A Tutorial Review Fluorescent organic nanoparticles (FONs) are a large family of nanostructures constituted by organic components that emit light in different spectral regions upon excitation, due to the presence of organic fluorophores. FONs are of great interest for numerous biological and medical applications, due to their high tunability in terms of composition, morphology, surface functionalization, and optical properties. Multifunctional FONs combine several functionalities in a single nanostructure (emission of light, carriers for drug-delivery, functionalization with targeting ligands, etc.), opening the possibility of using the same nanoparticle for diagnosis and therapy. The preparation, characterization, and application of these multifunctional FONs require a multidisciplinary approach. In this review, we present FONs following a tutorial approach, with the aim of providing a general overview of the different aspects of the design, preparation, and characterization of FONs. The review encompasses the most common FONs developed to date, the description of the most important features of fluorophores that determine the optical properties of FONs, an overview of the preparation methods and of the optical characterization techniques, and the description of the theoretical approaches that are currently adopted for modeling FONs. The last part of the review is devoted to a non-exhaustive selection of some recent biomedical applications of FONs. Characterization (materials science) ; Nanotechnology ; Surface modification ; Nanoparticle ; Fluorescence ; Drug delivery ; Nanostructure ; Materials science ; Computer science ; Chemistry ; Physics ; Optics Luminescence and Fluorescent Materials ; Nanoplatforms for cancer theranostics ; Dendrimers and Hyperbranched Polymers
Authors: Peng Xu | Wenbin Sun | Kang Xu | Yunpeng Zhang | Qian Tan | Yiren Qing | Ranbing Yang
Source: Foods (article, 2022-12-27)
Field: Chemistry — Analytical Chemistry

Identification of Defective Maize Seeds Using Hyperspectral Imaging Combined with Deep Learning Seed quality affects crop yield and the quality of agricultural products, and traditional identification methods are time-consuming, complex, and irreversibly destructive. This study aims to establish a fast, non-destructive, and effective approach for defect detection in maize seeds based on hyperspectral imaging (HSI) technology combined with deep learning. Raw spectra collected from maize seeds (200 each healthy and worm-eaten) were pre-processed using detrending (DE) and multiple scattering correction (MSC) to highlight the spectral differences between samples. A convolutional neural network architecture (CNN-FES) based on a feature selection mechanism was proposed according to the importance of wavelength in the target classification task. The results show that the subset of 24 feature wavelengths selected by the proposed CNN-FES can capture important feature information in the spectral data more effectively than the conventional successive projections algorithm (SPA) and competitive adaptive reweighted sampling (CARS) algorithms. In addition, a convolutional neural network architecture (CNN-ATM) based on an attentional classification mechanism was designed for one-dimensional spectral data classification and compared with three commonly used machine learning methods, linear discriminant analysis (LDA), random forest (RF), and support vector machine (SVM). The results show that the classification performance of the designed CNN-ATM on the full wavelength does not differ much from the above three methods, and the classification accuracy is above 90% on both the training and test sets. Meanwhile, the accuracy, sensitivity, and specificity of CNN-ATM based on feature wavelength modeling can reach up to 97.50%, 98.28%, and 96.77% at the highest, respectively. The study shows that hyperspectral imaging-based defect detection of maize seed is feasible and effective, and the proposed method has great potential for the processing and analysis of complex hyperspectral data. Hyperspectral imaging ; Artificial intelligence ; Pattern recognition (psychology) ; Convolutional neural network ; Computer science ; Support vector machine ; Random forest ; Feature (linguistics) ; Feature selection ; Linear discriminant analysis ; Feature extraction ; Deep learning ; Identification (biology) Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Dimitrios A. Koutsouras | Fabrizio Torricelli | Paul W. M. Blom
Source: Advanced Electronic Materials (article, 2022-11-22)
Field: Materials Science — Polymers and Plastics

Submicron Vertical Channel Organic Electrochemical Transistors with Ultrahigh Transconductance Abstract Organic electrochemical transistors (OECTs) belong to the class of electrolyte gated organic transistors (EGOTs) that offer a smooth interface with biology in combination with high transconductance values of typically a few mS. Fabrication‐wise, though, most of the up‐to‐date reported devices are limited to two dimensional structures, where the transistor channel is patterned on the same plane as the source and drain electrodes. Here, a method is introduced for the fabrication of integrated vertical channel OECTs (vOECTs) with submicron channel length. By employing electrodeposition, a vertical channel sandwiched between the source and drain electrodes is created. Channel lengths down to 60 nm are demonstrated, giving rise to ultrahigh transconductance of up to 275 mS. Accounting for the voltage loss on the device connection tracks, an intrinsic transconductance of vOECTs of 500 mS is found. The vOECTs are three‐dimensional transistors finding relevant application in “organ‐on‐a‐chip” and implantable devices, where high amplification and small footprint are demanded. Transconductance ; Materials science ; Transistor ; Optoelectronics ; Fabrication ; Electrode ; Channel (broadcasting) ; Footprint ; Nanotechnology ; Voltage ; Electrical engineering ; Chemistry ; Engineering Conducting polymers and applications ; Organic Electronics and Photovoltaics ; Advanced Memory and Neural Computing
Authors: Patryk Rybczyński | Manon H. E. Bousquet | Anna Kaczmarek‐Kędziera | Beata Jędrzejewska | Denis Jacquemin | Borys Ośmiałowski
Source: Chemical Science (article, 2022-01-01)
Field: Materials Science — Materials Chemistry

Controlling the fluorescence quantum yields of benzothiazole-difluoroborates by optimal substitution Precise tuning of the fluorescence quantum yield, vital for countless applications of fluorophores, remains exceptionally challenging due to numerous factors affecting energy dissipation phenomena often leading to its counterintuitive behavior. In contrast to the absorption and emission wavelength which can be precisely shifted to the desired range by simple structural changes, no general strategy exists for controllable modification of the fluorescence quantum yield. The rigidification of the molecular skeleton is known to usually enhance the emission and can be practically realized <i>via</i> the limiting molecular vibrations by aggregation. However, the subtle balance between the abundant possible radiative and non-radiative decay pathways makes the final picture exceptionally sophisticated. In the present study, a series of nine fluorophores obtained by peripheral substitution with two relatively mild electron donating and electron withdrawing groups are reported. The obtained fluorescence quantum yields range from dark to ultra-bright and the extreme values are obtained for the isomeric molecules. These severe changes in emission efficiency have been shown to arise from the complex relationship between the Franck-Condon excited state and conical intersection position. The experimental findings are rationalized by the advanced quantum chemical calculations delivering good correlation between the measured emission parameters and theoretical radiative and internal conversion rate constants. Therefore, the described substituent exchange provides a method to rigorously adjust the properties of molecular probes structurally similar to thioflavin T. Benzothiazole ; Substitution (logic) ; Fluorescence ; Quantum ; Chemistry ; Combinatorial chemistry ; Computer science ; Physics ; Organic chemistry ; Quantum mechanics Luminescence and Fluorescent Materials ; Molecular Sensors and Ion Detection ; Organic Light-Emitting Diodes Research
Authors: Taeyong Chang | Joonkyo Jung | Sang‐Hyeon Nam | Hyeonhee Kim | Jong Uk Kim | Nayoung Kim | Suwan Jeon | Minsung Heo | Jonghwa Shin
Source: Advanced Materials (article, 2022-09-05)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Universal Metasurfaces for Complete Linear Control of Coherent Light Transmission Recent advances in metasurfaces and optical nanostructures have enabled complex control of incident light with optically thin devices. However, it has thus far been unclear whether it is possible to achieve complete linear control of coherent light transmission, that is, independent control of polarization, amplitude, and phase for both input polarization states, with just a single, thin nanostructure array. Here, it is proved possible, and a universal metasurface is proposed, a bilayer array of high-index elliptic cylinders that possesses a complete degree of optical freedom with fully designable chirality and anisotropy. The completeness of achievable light control is mathematically shown with corresponding Jones matrices, new types of 3D holographic schemes that were formerly impossible are experimentally demonstrated, and a systematic way of realizing any input-state-sensitive vector linear optical device is presented. The results unlock previously inaccessible degrees of freedom in light transmission control. Polarization (electrochemistry) ; Materials science ; Optics ; Holography ; Coherent control ; Linear polarization ; Circular polarization ; Transmission (telecommunications) ; Phase control ; Optoelectronics ; Anisotropy ; Physics ; Phase (matter) ; Computer science ; Quantum mechanics ; Telecommunications ; Laser Metamaterials and Metasurfaces Applications ; Orbital Angular Momentum in Optics ; Optical Wireless Communication Technologies
Authors: Behzad Hasanzadeh | Yousef Abbaspour‐Gilandeh | Araz Soltani-Nazarloo | Mario Hernández-Hernández | Iván Gallardo-Bernal | José Luis Hernández-Hernández
Source: Horticulturae (article, 2022-07-04)
Field: Chemistry — Analytical Chemistry

Non-Destructive Detection of Fruit Quality Parameters Using Hyperspectral Imaging, Multiple Regression Analysis and Artificial Intelligence Currently, destructive methods are often used to measure the quality parameters of agricultural products. These methods are often complex, time consuming and costly. Recently, studying to find a solution to the disadvantages of destructive methods has become a major challenge for researchers. Non-destructive methods can be useful for the rapid detection of the quality parameters of agricultural products. In this study, hyperspectral imaging was used to evaluate the non-destructive quality parameters of Red Delicious (Red Delicious) and Golden Delicious (Golden Delicious) apples, including pH, soluble solids content (SSC), titratable acid (TA) and total phenol (TP). In order to predict the quality characteristics of apples, the partial least squares (PLS) method with different pre-processing was used. The developed models were evaluated using the root mean square parameters of RMSECV validation error, correlation coefficient (Rcv) and standard deviation ratio (SDR). The results showed that in Red Delicious, for pH, TA, SSC and TP the best forecasting methods were SNV, SNV, MSC and normalized pre-processing with the regression coefficient values of 0.9919, 0.9939, 0.9909 and 0.9899, respectively. In Golden Delicious (Golden Delicious), for pH, TA, SSC and TP, the first derivative, (smoothing and second derivative), normalize (and SNV and normalize) preprocessors were selected as the best prediction models, with values of 0.9989, 0.9989, 0.9999 and 0.9989, respectively. The results related to an artificial neural network also showed that in hyperspectral imaging, the best state of the feed-forward network structure with the LM training algorithm was R = 0.93, Performance = 0.005 and RMSE = 0.03 in 325 inputs, 5 outputs and 2 hidden layers. The results showed that hyperspectral imaging has different predictive capabilities for the qualitative characteristics studied in this study with high accuracy. Partial least squares regression ; Hyperspectral imaging ; Titratable acid ; Correlation coefficient ; Mathematics ; Coefficient of determination ; Artificial intelligence ; Mean squared error ; Linear regression ; Pattern recognition (psychology) ; Statistics ; Computer science ; Chemistry ; Food science Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Advanced Chemical Sensor Technologies
Authors: Alecio F. Lombardi | Yajun Ma | Hyungseok Jang | Saeed Jerban | Qingbo Tang | Adam C. Searleman | R. Scott Meyer | Jiang Du | Eric Y. Chang
Source: International Journal of Molecular Sciences (article, 2022-04-18)
Field: Materials Science — Materials Chemistry

AcidoCEST-UTE MRI Reveals an Acidic Microenvironment in Knee Osteoarthritis A relationship between an acidic pH in the joints, osteoarthritis (OA), and pain has been previously demonstrated. Acidosis Chemical Exchange Saturation Transfer (acidoCEST) indirectly measures the extracellular pH through the assessment of the exchange of protons between amide groups on iodinated contrast agents and bulk water. It is possible to estimate the extracellular pH in the osteoarthritic joint using acidoCEST MRI. However, conventional MR sequences cannot image deep layers of cartilage, meniscus, ligaments, and other musculoskeletal tissues that present with short echo time and fast signal decay. Ultrashort echo time (UTE) MRI, on the other hand, has been used successfully to image those joint tissues. Here, our goal is to compare the pH measured in the knee joints of volunteers without OA and patients with severe OA using acidoCEST-UTE MRI. Patients without knee OA and patients with severe OA were examined using acidoCEST-UTE MRI and the mean pH of cartilage, meniscus, and fluid was calculated. Additionally, the relationship between the pH measurements and the Knee Injury and Osteoarthritis Outcome Score (KOOS) was investigated. AcidoCEST-UTE MRI can detect significant differences in the pH of knee cartilage, meniscus, and fluid between joints without and with OA, with OA showing lower pH values. In addition, symptoms and knee-joint function become worse at lower pH measurements. Osteoarthritis ; Cartilage ; Knee Joint ; Meniscus ; Magnetic resonance imaging ; Medicine ; Extracellular ; Medial meniscus ; Chemistry ; Extracellular fluid ; Nuclear medicine ; Anatomy ; Radiology ; Surgery ; Pathology ; Biochemistry Lanthanide and Transition Metal Complexes ; Advanced MRI Techniques and Applications ; Electron Spin Resonance Studies
Authors: Yue You | Junfeng Dou | Xue Yu | Naifu Jin | Kai Yang
Source: Sustainability (review, 2022-05-23)
Field: Chemistry — Inorganic Chemistry

Chelating Agents in Assisting Phytoremediation of Uranium-Contaminated Soils: A Review Massive stockpiles of uranium (U) mine tailings have resulted in soil contamination with U. Plants for soil remediation have low extraction efficiency of U. Chelating agents can mobilize U in soils and, hence, enhance phytoextraction of U from the soil. However, the rapid mobilization rate of soil U by chelating agents in a short period than plant uptake rate could increase the risk of groundwater contamination with soluble U leaching down the soil profile. This review summarizes recent progresses in synthesis and application of chelating agents for assisting phytoremediation of U-contaminated soils. In detail, the interactions between chelating agents and U ions are initially elucidated. Subsequently, the mechanisms of phytoextraction and effectiveness of different chelating agents for phytoremediation of U-contaminated soils are given. Moreover, the potential risks associated with chelating agents are discussed. Finally, the synthesis and application of slow-release chelating agents for slowing down metal mobilization in soils are presented. The application of slow-release chelating agents for enhancing phytoextraction of soil U is still scarce. Hence, we propose the preparation of slow-release biodegradable chelating agents, which can control the release speed of chelating agent into the soil in order to match the mobilization rate of soil U with plant uptake rate, while diminishing the risk of residual chelating agent leaching to groundwater. Phytoremediation ; Chelation ; Environmental remediation ; Leaching (pedology) ; Soil water ; Soil contamination ; Tailings ; Chemistry ; Environmental chemistry ; Environmental science ; Uranium ; Contamination ; Soil science ; Materials science ; Metallurgy ; Inorganic chemistry ; Ecology ; Biology Radioactive element chemistry and processing ; Geochemistry and Elemental Analysis ; Coal and Its By-products
Authors: Xu Lu | Tom Depover | Roy Johnsen
Source: International Journal of Hydrogen Energy (article, 2022-08-01)
Field: Materials Science — Metals and Alloys

Evaluation of hydrogen diffusion and trapping in nickel Alloy 625 by thermal desorption spectroscopy This study presents hydrogen diffusion and trapping in the nickel Alloy 625 by employing the hot extraction test and the thermal desorption spectroscopy (TDS) analysis. Combined with electrochemical permeation test, the impact of grain size and grain boundary carbide on hydrogen diffusion are investigated. The results manifeste that the effective hydrogen diffusivity can be expressed as D=1.03×10−7exp(−46.44kJmolRT)m2/s for the sample with a grain size of ∼8 μm. The diffusion activation energy ED for hydrogen is determined as 42.05–48.10 kJ/mol. The activation energy E associated with interstitial sites/elastic field of dislocations and reversible traps is 17.92–20.73 kJ/mol and 24.87–27.13 kJ/mol, respectively. Moreover, the reduction in grain size and the presence of grain boundary carbide can lower hydrogen diffusivity by locally changing the diffusion and trapping behavior of hydrogen. Grain boundary diffusion coefficient ; Hydrogen ; Grain boundary ; Thermal diffusivity ; Activation energy ; Diffusion ; Materials science ; Analytical Chemistry (journal) ; Thermal desorption ; Carbide ; Nickel ; Grain size ; Desorption ; Thermal desorption spectroscopy ; Alloy ; Chemistry ; Metallurgy ; Physical chemistry ; Thermodynamics ; Microstructure ; Adsorption Hydrogen embrittlement and corrosion behaviors in metals ; Corrosion Behavior and Inhibition ; High Temperature Alloys and Creep
Authors: Golokesh Santra | Emmanouil Semidalas | Nisha Mehta | Amir Karton | Jan M. L. Martin
Source: Physical Chemistry Chemical Physics (article, 2022-01-01)
Field: Materials Science — Materials Chemistry

S66x8 noncovalent interactions revisited: new benchmark and performance of composite localized coupled-cluster methods The S66x8 noncovalent interactions benchmark has been re-evaluated at the "sterling silver" level, using explicitly correlated MP2-F12 near the complete basis set limit, CCSD(F12*)/aug-cc-pVTZ-F12, and a (T) correction from conventional CCSD(T)/sano-V{D,T}Z+ calculations. The revised reference values differ by 0.1 kcal mol<sup>-1</sup> RMS from the original Hobza benchmark and its revision by Brauer <i>et al.</i>, but by only 0.04 kcal mol<sup>-1</sup> RMS from the "bronze" level data in Kesharwani <i>et al.</i>, <i>Aust. J. Chem.</i>, 2018, <b>71</b>, 238-248. We then used these to assess the performance of localized-orbital coupled cluster approaches with and without counterpoise corrections, such as PNO-LCCSD(T) as implemented in MOLPRO, DLPNO-CCSD(T<sub>1</sub>) as implemented in ORCA, and LNO-CCSD(T) as implemented in MRCC, for their respective "Normal", "Tight", and "very Tight" settings. We also considered composite approaches combining different basis sets and cutoffs. Furthermore, in order to isolate basis set convergence from domain truncation error, for the aug-cc-pVTZ basis set we compared PNO, DLPNO, and LNO approaches with canonical CCSD(T). We conclude that LNO-CCSD(T) with veryTight criteria performs very well for "raw" (CP-uncorrected), but struggles to reproduce counterpoise-corrected numbers even for veryveryTight criteria: this means that accurate results can be obtained using either extrapolation from basis sets large enough to quench basis set superposition error (BSSE) such as aug-cc-pV{Q,5}Z, or using a composite scheme such as Tight{T,Q} + 1.11[vvTight(T) - Tight(T)]. In contrast, PNO-LCCSD(T) works best with counterpoise, while performance with and without counterpoise is comparable for DLPNO-CCSD(T<sub>1</sub>). Among more economical methods, the highest accuracies are seen for dRPA75-D3BJ, ωB97M-V, ωB97M(2), revDSD-PBEP86-D4, and DFT(SAPT) with a TDEXX or ATDEXX kernel. Counterpoise ; Extrapolation ; Coupled cluster ; Basis set ; Benchmark (surveying) ; Basis (linear algebra) ; Truncation (statistics) ; Physics ; Limit (mathematics) ; Statistical physics ; Atomic physics ; Mathematics ; Computational chemistry ; Chemistry ; Quantum mechanics ; Molecule ; Mathematical analysis ; Statistics ; Geometry Machine Learning in Materials Science ; Crystallography and molecular interactions ; X-ray Diffraction in Crystallography
Authors: Caterina Serafinelli | Alessandro Fantoni | Elisabete C. B. A. Alegria | M. Vieira
Source: Biosensors (review, 2022-04-09)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Plasmonic Metal Nanoparticles Hybridized with 2D Nanomaterials for SERS Detection: A Review In SERS analysis, the specificity of molecular fingerprints is combined with potential single-molecule sensitivity so that is an attractive tool to detect molecules in trace amounts. Although several substrates have been widely used from early on, there are still some problems such as the difficulties to bind some molecules to the substrate. With the development of nanotechnology, an increasing interest has been focused on plasmonic metal nanoparticles hybridized with (2D) nanomaterials due to their unique properties. More frequently, the excellent properties of the hybrids compounds have been used to improve the drawbacks of the SERS platforms in order to create a system with outstanding properties. In this review, the physics and working principles of SERS will be provided along with the properties of differently shaped metal nanoparticles. After that, an overview on how the hybrid compounds can be engineered to obtain the SERS platform with unique properties will be given. Nanotechnology ; Plasmon ; Nanomaterials ; Nanoparticle ; Materials science ; Plasmonic nanoparticles ; Substrate (aquarium) ; Molecule ; Chemistry ; Optoelectronics Gold and Silver Nanoparticles Synthesis and Applications ; Advanced biosensing and bioanalysis techniques ; Nanocluster Synthesis and Applications