10 Cemented paste backfill (CPB) comprising mineral tailing s, binders and mixing waters i s an important potential 11 support material in the mining industry. As the mechanical propertie s of CPB are significantly influence d by its 12 microstructural characteristics the development of measurement tools to better understand its pore structure 13 evolution is important for its increased utilisation. This study reports the application of low -field nuclear 14 magnetic resonance (NMR) relaxation time measurements to characterise the microstructural evolution of CPB 15 materials over 56 days of hydration , contrasting common tap water and hypersaline water (~22 wt% salt) as 16 mixing waters. Distinct NMR relaxation time populations were evidenced within each CPB sample, revealing 17 the presence of both capillary ( T1,2 ≈ 10 ms) and gel pore water (T1,2 ≈ 300 – 500 µs), with time -dependent 18 relaxation measurements facilitating characterisation of capillary pore structure evolution over the hydration 19 period assessed . Hypersaline samples demonstrated a time -lag in th is measured capillary pore evolution , relative 20 to those h ydrated with tap water , while pore structure evolution rates were observed to increase with increased 21 CPB binder content . Further, b oth T1 and T2 NMR relaxation times were found to correlate with the uniaxial 22 compressive strength of the CPB materials investigated , facilitating the formulation of a predictive correlation 23 function between NMR relaxation characteristics and mechanical properties. 24 Keywords 25 Cemented paste backfill; Tailing s Management; Nuclear Magnetic Resonance ; Microstructure 26 27 2 Highlights 1 ▪ Microstructural evolution of CPB, prepared with tap and hypersaline water, is monitored using low -field 2 NMR relaxometry. 3 ▪ T1 and T2 NMR relax ation measurements compared with mechanical strength via UCS tests. 4 ▪ Hypersaline mixing water results in slower structural evolution and lower mechanical strength. 5 6 Introduction 7 It is estimated that the production rate of mine tailings ranges between 5 and 7 billion tonnes per year worldwide 8 [1]. While mine tailings are often discharged into tailings ponds , the emergence of cemented paste backfill 9 (CPB) technology has the potential to substantially alter and enhance the role of tailings in the mining industry 10 [2]. CPB comprises three main components, namely dewatered mine tailings (70 -85 % solids by weight), 11 mixing water and hydraulic binders (3-7 % by paste weight ), which may include Ordinary Portland Cement 12 (OPC), fly ash, and ground granulated blast furnace slag ; these components combine via hydration reaction s to 13 form a complex porous structure which may be utilised as a passive support material within underground mining 14 operations [3]. 15 It is well-known that mixing water chemistry , including acidity and ionic co ncentrations , can impact the 16 mechanical properties of hydrated CPB materials [2,4] . As access to low -salinity water i n many mining 17 operations is limi ted, and the local source water typically hypersaline , it is therefore of significant interest to 18 determine the influence of hypersaline mixing water on the evolution of hydrated CPB materials . As such, i n 19 the present study we compare the effect s of hypersaline water (~22 wt% salt) obtained from a Western 20 Australian mine site, combined with mine tailing s from the same site, against the effects of tap water on both 21 the microstructural and mechanical strength evolution o f the resultant CPB. 22 A number of recent studies have investigated the relationship between the microstructure of next-generation 23 cementitious materials and th e resulting mechanical properties. For example, Burciaga -Diaz et al. contrasted 24 the compressive st rength of alkali -activated slag pastes with solid state 29Si and 27Al NMR spectroscopy, 25 facilitating quantification of the hydration products formed and their association with material strength [5]. Ma 26 3 et al. applied a similar approach to fly ash cement pastes , evidencing compressive strength enhancements which 1 accompany Si/Al substitution reactions within the hydration products in the presence of an organic activator 2 [6]. Fridjonsson et al. were the first to monitor the pore size evolution of CPB samples during their hydration 3 using NMR, revealing through the application of nuclear spin relaxation measurements both a reduction in pore 4 size during the hydration process, and a scaling relationship between pore size and material permeability [7]. 5 Sun et al. studied the evolution of CPB porosity under uniaxial compression via X-ray CT analysis [8]. This 6 study sequenced CPB failure into four stages, namely (i) a no microcrack region; (ii) initiation and aggregation 7 of microcracks; (iii) connection of microcracks; and (iv) formation of a macroscopic fracture region, and further 8 showed that the CPB materials investigated displayed tensile and shear failures during early and middle -to-late 9 stages of uniaxial compression, respectivel y. Furthermore Liu et al. studied CPB using both NMR and SEM to 10 investigate the relationship between uniaxial compressive strength (UCS ) and CPB pore characteristics , 11 observing an exponential decrease in UCS with increasing porosity [9]. 12 In the current study the results of low-field nuclear magnetic resonance (NMR) rela xation measurements are 13 contrasted with UCS analysis to monitor th e compressive strength and pore size evolution of CPB samples 14 prepared with both tap and hypersaline mixing waters. A significant advantage of using low -field NMR is that 15 it provides a non-destructive method for the character isation of porous media [10]. As such , it offers 16 opportunities for the development of robust approaches for monitoring CPB samples under early hydration 17 conditions without the requirements for sample modification s, such as solvent exchange or oven drying, which 18 may damage the material microstructure [11,12] . Indeed, a s the longitudinal and transverse NMR relaxation 19 times T1 and T2 are both inherently sensitive to molecular dynamics [13], the relaxation characteristics of fluids 20 confined to porous structures can provide unique insight into material structural properties including pore size 21 distributions and pore network connecti vity [7,14 –21]. 22 4 Theory 1 Utilising 1H (proton) relaxation measurements this study considered the dynamics of water confined to the p ore 2 structure s of the CPB materials. Such systems are assumed to exist under the conditions of biphasic fast 3 exchange, wherein the rates of mixing between water molecules adsorbed at the pore surface and those towards 4 the centre of the pore is considered t o be rapid relative to the ir intrinsic rates of NMR relaxation [22]. Under 5 such conditions the measured relaxation rates 𝑇𝑖−1 (with 𝑖= 1 or 2 for longitudinal or transverse NMR 6 relaxation, respectively ) are given by a combination of unrestricted (bulk) , surface (adsorbed) and confinement 7 contributions according to [23] 8 1 𝑇𝑖≈1 𝑇𝑖,𝑏𝑢𝑙𝑘+2𝛼𝜌𝑖 𝑑𝑝𝑜𝑟𝑒+8𝛼𝐷 𝑑𝑝𝑜𝑟𝑒2. (1) Here 𝑇𝑖,𝑏𝑢𝑙𝑘 are the relaxation time constants of the unrestricted fluid, α is a shape parameter which takes values 9 of 1, 2 or 3 for planar, cylindrical or spherical pores, respectively [24], D is the self -diffusion coefficient of the 10 confined fluid, and ρi are the longitudinal ( 𝑖= 1) and transverse ( 𝑖= 2) surface relaxivities , which define the 11 rates of enhanced NMR relaxation which occurs at the pore surface [17,18,25] . Importantly, 𝑑𝑝𝑜𝑟𝑒 is the pore 12 diameter of the confining pore structure ; Equation (1) therefore provides a direct lin k between the observed 13 NMR relaxation time constants and the microstructural characteristics of the material s under investigation . This 14 relationship is further resolved through the assumption of so-called surface -limited relaxation , a regularly - 15 applied ass umption for cementitious materials and other heterogeneous porous media , wherein 4𝐷𝑑𝑝𝑜𝑟𝑒⁄ ≫𝜌𝑖 16 [18,19,26,27] . In this case Equation (1) simplifies to [23] 17 1 𝑇𝑖≈1 𝑇𝑖,𝑏𝑢𝑙𝑘+2𝛼𝜌𝑖 𝑑𝑝𝑜𝑟𝑒, (2) such that the observed relaxation time constants 𝑇𝑖 are proportional to 𝑑𝑝𝑜𝑟𝑒. It follows that the measurement 18 of these time constants throughout the CPB hydration process can provide valuable information on the rates and 19 extent of pore structure ev olution , and the influence of different mixing waters on hydration behaviour . Herein 20 we apply this approach to study the pore structure evolution of CPB samples over the first 56 days of hydration, 21 contrast ing the behaviour of tap water and hypersaline wat er hydrated mixtures. We then further investigate the 22 relationship between apparent pore size and material strength characteristics through the comparison of these 23 NMR relaxation times with the results of UCS measurements . 24 5 Materials and Methods 1 Material preparation 2 Minerals tailings were acquired from the Frog’s Leg Gold Mine , located ~19 km west of Kalgoorlie, Western 3 Australia. The tailings were sieved to < 4.75 mm before use to remove any coagulated particles , and dehydrated 4 by drying in air at 110 °C for 24 hours. Figure 1 illustrates the particle size distribution o f both the tailings and 5 commercially available slag (sourced from BGC Cement , Australia) used in this study, which were found to 6 exhibit mean (d50) particle sizes of 60 µm and 10 µm, respec tively. The chemical composition of the tailings is 7 reported in Table 1 and was assessed by Inductively Coupled Plasma -Optical Emission Spectroscopy (ICP - 8 OES) ; the tailings were first dried and finely ground , then fused with 12:22 Norrish Flux (Lithium metaborate 9 / Lithium tetraborate) in platinum crucibles at 1050 °C to form glass beads. The beads were then dis solved in 1 10 M hydrochloric acid, with the resulting solution analysed using an Optima 5300 DV ICP -OES. The detected 11 elemental concentrat ions were converted to oxide wt% values based on the corresponding atomic weights . 12 The CPB binder s comprised a mixture of slag and OP C in a 2:1 ratio by mass . As cement concentration s used 13 in typical mine sites vary between 1 and 10 wt% we opted here to explore two different binder concentrations 14 exhibiting 5 and 9 wt% binder content, respectively , relative to the total tailings and binder mass ; a total solids 15 content of 76 wt% was maintain ed across all CPB sample s investigated. Common tap water and hyper saline 16 water were used as mixing waters, with the hypersaline water obtained from the same site as the mineral tailings. 17 Chemical analysis of these waters was conducted via ICP-OES and anion chromatography , with the resulting 18 ionic composition data reported in Table 2. Anion chromatography tests were conducted using a Thermo 19 Scientific Dionex IonPac AS23 instrument while cation concentrations were obtained using an Optima 5300 20 DV ICP -OES. 21 To form the CPB samples the dehydrated tailings and hydraulic binders were mixed with either tap water or 22 hypersaline water for 3 minutes at 90 rpm using a stand mixer. The resultant CPB pastes were subsequently 23 transferred to cylindrical plastic moulds (diameter = 50 mm, height = 100 mm) for UCS analysis , and to 24 cylindrical plastic containers (diameter = 44 mm, height = 108 mm) for NMR analysis ; the samples were each 25 cured at 20 ± 2 °C with a relative humidity of 95 % until the appropriate hydration time was attained. 26 6 1 Figure 1: Particle size distributions of tailings and slag. Tailings exhibit d60 ~ 90 μm, d 50 ~ 60 μm and d 10 ~ 5 2 μm, while the slag exhibits d60 ~ 13 μm, d 50 ~ 10 μm, and d 10 ~ 0.6 μm. Prior to analysis b oth the tailings and 3 slag were pre -screened to remove large rocks and agglomerates. 4 5 Table 1. Chemical composition of the mine tailings used in this study obtained from ICP-OES analysis. 6 Chemical composition Content (wt%) Chemical composition Content (wt%) SiO 2 68.49 K2O 1.34 Al2O3 9.55 SO 3 1.13 Na2O 3.31 TiO 2 0.54 Fe2O3 3.18 MnO 0.08 CaO 3.16 P2O5 0.05 MgO 1.56 7 Table 2. Chemical compositional analysis of the mixing waters used in this study obtained from ICP -OES and 8 anion chromatography. 9 Hypersaline water / mg L-1 Tap water / mg L-1 Ca2+ 955 Cl- 620 Fe <0.002 SO 42- 6 K+ 230 Br- 1 Mg2+ 7790 Na+ 61900 Cl- 115000 SO 42- 4480 Br- 199 10 11 12 7 Uniaxial compressive strength tests 1 UCS is a key mechanical property in CPB analysis. The UCS of our CPB samples was measured using an 2 Electro -hydraulic Servo-controlled universal testing machine (GDS LF -50) with a maximum load capacity of 3 50 kN. Tests were conduct ed once the CPB samples had been cured for 7, 14, 28 and 56 days. Following each 4 curing process the CPB samples were placed between two parallel plates and were loaded under constant 5 displacement conditions with a displacement rate of 1 mm min-1. UCS readi ngs were recorded every second and 6 the axial loading terminated when the sample developed an obvious shearing plane . Tests were performed in 7 triplicate with the average of the three values reported here; a maximum 10% standard deviation from the mean 8 stren gth was observed across all samples. 9 High resolution X -ray computed tomography 10 X-ray µ -CT was performed to obtain an estimate of the (capillary) pore size distribution of CPB materials. A 11 single material sample comprising 5 wt% binder was prepared in a gl ass vial (diameter = 5 mm, height = 25 12 mm) and scanned using a Zeiss XRM520 3D X -ray microscope with a 1 µm voxel resolution. A total of 1600 13 projections were recorded over 360° (i.e. 0.225° rotation of the sample between each projection). Artefacts were 14 either reduced during acquisition or corrected during the reconstruction procedure, and i mage filtering was 15 performed using a non-local mean algorithm which acted to enhance the image by reducing noise and improving 16 phase discrimination. Segmentation into d ifferent phases (pores and solids ) was achieved using a modified 17 version of the 3D gradient watershed algorithm , attributing a range of grayscale values to a given phase, with 18 phase boundaries being located at the point of maximum gradient in grayscale , as described elsewhere [28]. 19 Each reconstructed dataset was processed using Avizo 9.5 (ThermoFisher) and MATLAB (MathWorks Inc.) 20 according to the workflow described in [28]. 21 Nuclear magnetic resonance relaxation measurements 22 NMR relaxation experiments were conducted using a benchtop Magritek Rock Core Analyser equipped with a 23 0.05 T cylindrical Halbach magnet array, providing a 1H NMR frequency of 2 MHz. The radio frequency (RF) 24 pulse lengths were fixed at 20 µs with the pulse amplitudes for 90° and 180° RF pulses set to -12.5 dB and -6.5 25 dB, respectively. Both the longitudinal ( T1) and transverse ( T2) nuclear spin relaxation characteristics of our 26 CPB materials were measured, with the RF pulse sequences used illustrated in Figure 2. Measurem ents were 27 8 performed on each day for two weeks (days 1 – 14) followed by further analysis on days 28, 30, 31 and 56. All 1 NMR measurements were performed with a constant magnet bore temperature of 30 °C. Both 𝑇1 and 𝑇2 2 measurements were performed using a r ecycle delay of 10 s and 4 repeat scans , result ing in acquisition times 3 of 15 minutes and 1 minute, respectively, and signal -to-noise ratios > 200. 4 Longitudinal relaxation times were measured using the standard inversion -recovery (IR) pulse sequence shown 5 in Figure 2a [29]. Starting from thermal equilibrium wherein the sample magnetisation lies parallel to the 6 external magnetic field (conventionally the z -axis), the IR measurement is initiated by a 180° RF pulse which 7 rotates the sample magnetisation onto the -z axis. Lo ngitudinal relaxation processes are then permitted for a 8 variable recovery period τ 1 during which the sample magnetisation recovers towards equilibrium. Following 9 each recovery period a 90° RF pulse acts to rotate the magnetisation into the transverse plan e, allowing the 10 magnitude of the sample magnetisation to be measured [30]. In this work 20 logarithmically -spaced τ1 recovery 11 times between 0.5 ms and 500 ms were used. The resulting longitudinal relaxation data are described according 12 to a Fredholm integral equation of the first kind [31], 13 𝑆(𝜏1) 𝑆(𝜏1→∞)=∫𝐾1(𝜏1,𝑇1) 𝑓(𝑇1) 𝑑log 10(𝑇1)+𝜀(𝜏1). (3) Here 𝑆(𝜏1)𝑆(𝜏1→∞) ⁄ is the normalised NMR signal intensity following each τ1 delay, the Kernel function 14 𝐾1(𝜏1,𝑇1)=1−2exp(−𝜏1𝑇1⁄) describes the expected form of 𝑇1 relaxation following the IR experiment 15 [29], and 𝑓(𝑇1) represents the distribution of 𝑇1 time constants present; 𝜀(𝜏1) is the experimental noise, assumed 16 Gaussian in shape with zero mean. 17 Transverse relaxation times were measured using t he standard CPMG (Carr -Purcell -Meiboom -Gill) experiment 18 shown in Figure 2b [32,33] . Starting again from thermal equilibrium the sample magnetisation is excited into 19 the transverse plane via a 90° RF pulse, which initiates transverse dephasing of the system’s magnetic moments. 20 A series of 𝑛 180° RF pulses refocusses dephasing arising from inhomogeneity of the static magnetic field , 21 generating a train of 𝑛 spin echoes which decay according to 𝑇2. In this work we employed 𝑛= 500 echoes 22 separated by an echo time of 𝑡𝑒= 100 µs; this short echo time, together with the low static magnetic field 23 strength employed in this study, aimed to limit the influence of undesired transverse relaxation phenom ena due 24 9 to magnetic susceptibility contrast effects at the solid -liquid interface [21,34] . The resulting relaxation data are 1 again described by a Fredholm integral equation of the first kind [31], 2 𝑆(𝑛𝑡𝑒) 𝑆(0)=∫𝐾2(𝑛𝑡𝑒,𝑇2)𝑓(𝑇2) 𝑑log 10(𝑇2)+𝜀(𝑛𝑡𝑒). (4) Here 𝑆(𝑛𝑡𝑒)𝑆(0) ⁄ is the normalised NMR signal intensity acquired during each echo, the Kernel function 3 𝐾2(𝑛𝑡𝑒,𝑇2)=exp(−𝑛𝑡𝑒𝑇2⁄) describes the expected form of 𝑇2 relaxation [33] and 𝜀(𝑛𝑡𝑒) again represents the 4 experimental noise. 5 The desired time constant distributions 𝑓(𝑇1) and 𝑓(𝑇2) were obtained via a numerical inversion of our acquired 6 experimental data according to Equations (3) and (4) ; as this is an ill -posed problem it was necessary to employ 7 Tikhonov regularisation [35] to ensure the stability of the resulting 𝑇1 and 𝑇2 distributions in the presence of 8 experimental noise, with the sm oothing parameter chosen according to the generalised cross -validation method 9 [36]. This robust mathematical inversion technique makes no assumptions about the shape of the resultant 10 probability distributions, and has been successfully implemented across a rang e of NMR data analysis protocols , 11 including relaxation time distributions in porous media [7,37,38] and droplet sizing methods [39]. The inversion 12 algorithm used in this work was written in MATLAB (MathWorks Inc.) and first used by Griffith et al.. [40] 13 As indicated by Equations (3) and (4), as the NMR relaxation time constants exhibited by fluids confined to 14 heterogeneous porous materials are regularly found to vary across multiple decades within the µs – s range , 15 such expression ar e typically inverted on a logarithmic – rather than a linear – scale [41]. 16 17 10 1 2 Figure 2. Radio frequency (RF) pulse sequence diagrams for a) 𝑇1 relaxation time measurements via the 3 inversion recovery experiment, and b) 𝑇2 relaxation time measurements via the CPMG experiment. Vertical 4 bars represent RF pulses of constant length ; 𝜏1 represents the variable recovery delays used in the inversion 5 recover y experiment while the CPMG echo time is 𝑡𝑒=2𝜏2. 6 7 τ1a)180 90° b) τ2180° 180° 90°Echo timen-1τ2 τ2 11 Results and Discussion 1 Initial characterisation 2 Figure 3 illustrates the influence of bi nders (cement and slag) on the observed 𝑇1 relaxation time distributions 3 of water -saturated tailings. Clearly , when tailings are mixed with either tap or hypersaline water the 𝑇1 4 distribution s appear similar , with dominant peaks located at approximately 15 – 20 ms ; this 𝑇1 population is 5 readily assigned to water constricted within the inter -particulate region of th e tailings. The addition of 5 wt% 6 binder has a perceivable effect on the observed 𝑇1 distribution, however, and in the case of tap water reduc es 7 the dominant 𝑇1 population to ~10 ms . This value is consistent with previous low -field relaxation studies of 8 cementitious systems , which observed 𝑇1 times of this order to correlate with the water population of capillary 9 pore spaces [18,42] . Figure 4 demonstrates CPB por e structur e characterisation via high-resolution X-ray µ - 10 CT analysis of a sample containing 5 wt% solids hydrated with tap water for 21 days. This data demonstrates 11 the typical pore size distribution exhibited by such structures, wherein the observed pore spaces are largely 12 present across the length scale 5 – 25 µm. Given the resolution of this µ -CT analysis and the resultant pore size 13 distribution , these structures are readily identified as capillary -type pores. 14 15 12 1 Figure 3. 𝑇1 relaxation time distributions for tap water and hypersaline water saturated tailings samples, and tap 2 water saturated tailings with 5 wt% binder content. A shift to lower 𝑇1 values is evident upon the addition of 3 cement to the sample. 4 5 6 Figure 4 . a) X-ray µ-CT image of cemented paste backfill comprising 5 wt% binder content and 76 wt% solids 7 content following hydrat ion with tap water for 21 days . b) Example s egmented X-ray µ -CT data identifying the 8 solids (black) and pore space (blue). c) Equivalent pore diameter distribution obtained from the segmentation 9 of image data in a), indicating that observable pore s are dominant at the 𝑑𝑝𝑜𝑟𝑒 = 5 – 25 µm length scale ; these 10 are assigned to capillary pore structures. 11 (a) (b) 2 mm(c) 13 Pore structure evolution 1 Figure s 5 and 6 report the acquired NMR relaxation data from our CPB materials. Figure 5 illustrates the 𝑇1 and 2 𝑇2 relaxation time distribution evolution of CPB samples with 5 wt% binder content; Figure 5a and 5b reports 3 the evolution of hypersaline water hydrate d CPB, while Figure 5c and 5d reports the evolution following 4 hydration with tap water. In all cases a dominant relaxation peak is observed, which decreases in value over the 5 hydration time scale. In our 𝑇1 data these dominant peaks are initially observed at 𝑇1≈ 10 ms and decrease to 6 𝑇1≈ 2 ms after 56 days of hydration. As introduced previously, this initial dominant 𝑇1 population can be 7 assigned to water confined within the capillary pore space of the cementitious matrices , [42] which for o ur CPB 8 materials is expected to occur over the 5 – 25 µm size range (Figure 4). The corresponding 𝑇2 data is displayed 9 in Figure 5b and 5d, wherein the dominant peaks decrease from 𝑇2≈6 ms to 𝑇2≈ 2 ms after 56 days . The 10 observation of reduced 𝑇2 values , relative to the 𝑇1 characteristics exhibited by the same porous structure , is in 11 accordance with the known surface relaxation behaviour of fluids confined to cement -based materials [18]. 12 Three distinct 𝑇2 populations are evident at the onset of the hydration process in both the hypersaline water and 13 tap water systems; given our knowledge of the relationship between material pore size and NMR relaxation 14 times (Equation (2)) these peaks may be assigned to di stinct water populations occupying pore structures of 15 different sizes. In particular, given the established pore hierarchy of cementitious materials , we assign these 16 populations to capillary pore ( 𝑇2 ~ 3-100 ms), interhydrate pore ( 𝑇2 ~ 0.8-2 ms) and gel pore ( 𝑇2 ~ 300-500 17 µs) structures, in order of decreasing 𝑇2. This expected pore hierarchy is illustrated in Figure 7 [42–44]. No 18 clear relaxation contributions are observed from solid 1H-bearing hydration products [45], or from water within 19 the associated interlayer spaces [46]; we attribute th is absence to the very short 𝑇2 characteristics expected from 20 such features, the measurement of which is likely beyond the echo time limitations of our NMR hardware . 21 As the hydration processes progress, the interhydrate and capillary pore 𝑇2 populations ca n be seen to merge, 22 indicating that the capillary and interhydrate pore structures become indistinguishable in the latter stages of 23 CPB hydration. This observation, together with the clear decrease in modal 𝑇1 and 𝑇2 relaxation times within 24 increasing hy dration period, is consistent with the known physical mechanisms of cement hydration, whereby 25 hydration products forming at the surface of cement particles ingress into the capillary pore space [47]. 26 14 No interhydrate water population is observed within the 𝑇1 data presented in Figures 4a and 4b, suggesting such 1 measurements are unable to distinguish between water within capillary and interhydrate pores, even at short 2 hydration times . This observation is co nsistent with the temporally averaged nature of 𝑇1 measurements, relative 3 to 𝑇2 analysis [48]; this phenomena facili tates a greater degree of diffusive pore -to-pore exchange during 4 relaxation measurement s, resulting in greater 𝑇1 averaging between pores of difference size , and hence reduced 5 pore structure resolution. Notwithstanding these observations, the relative 𝑇2 populations assigned to 6 interhydrate and capillary pores demonstrate that the major peak s within our 𝑇1 and 𝑇2 distributions are 7 dominated by water within the capillary pore structures of the CPB materials under investigation . 8 Similar to Figure 5, Figure 6 illustrates the 𝑇1 and 𝑇2 relaxation time distribution evolution of CPB samples 9 with 9 wt% binder content; Figure 6a and 6b reports the evolution of hypersaline water -hydrated CPB, while 10 Figure 6c and 6d reports the evolution following hydration with tap water. These distributions again illustrate a 11 major peak which we assign as dominate d by water within the capillary pore spaces of the CPB materials, and 12 which tends to shorter relaxation times with increasing hydration period. Our 𝑇1 data again shows two separate 13 populations, with the dominant population decreasing from 𝑇1≈ 10 ms to be tween 1 ms (tap water) and 2 ms 14 (hypersaline water) , depending on the mixing water employed. The 𝑇2 data illustrated in Figure 6b and 6d again 15 shows three separate water populations at short hydration time s, which we again assign to capillary, inter - 16 hydra te and gel pore structures within the CPB materials. The capillary and inter -hydrate populations are again 17 observed to merge with increasing hydration time; however , we note that this process occur s at a much earlier 18 stage within the hydration process than observed in the 5 wt% binder CPB data shown in Figure 5. This 19 observation therefore indicates that an increase in cement content facilitates more rapid overall structural 20 evolution of the CPB pore hierarchy . 21 15 1 Figure 5. 𝑇1 and 𝑇2 relaxation time distributions for CPB samples comprising 5 wt% binder content and 76 wt% 2 solids. a) and b) illustrate the relaxation distribution evolution when hydrated with hypersaline water, while c) 3 and d) illustrate the corresponding data when hydrat ed with tap water. Data was acquired on days 1 -14, 28, 30, 4 31 and 56. Colour bars indicate the probability density of the relaxation distributions. 5 6 Figure 6 . 𝑇1 and 𝑇2 relaxation time distributions for CPB samples comprising 9 wt% binder content and 76 wt% 7 solids. a) and b) illustrate the relaxation distribution evolution when hydrated with hypersaline water, while c) 8 and d) illustrate the correspond ing data when hydrated with tap water. Data was acquired on days 1 -14, 28, 30, 9 31 and 56. Colour bars ind icate the probability density of the relaxation distributions. 10 16 1 Figure 7: Schematic relating NMR relaxation times T1 and T2 to unique water -saturated pore environments in 2 cementitious system. Water in capillary pore s exhibit T1 or T2 relaxation times of ~ 10 ms , inter-hydrate water 3 display observable T2 relaxation time of ~ 1 ms , while rapid T1 and T2 relaxation times of ~ 300 µs correlate to 4 water in gel pore s [42–44]. The abbreviation C -S-H stands for calcium silicate hydrate. 5 6 Capillary pore water T1or T2~ 10 ms dpore~ µm Inter-hydrate water T2~ 1 ms length scale ~ nm Gel pore water T1or T2~ 300 µs length scale ~ nm Cement grainC-S-H P1P2P3P1 P2 P3 17 Clearly qualitatively similar trends are exhibited by the eight data sets presented in Figures 5 and 6 . This is 1 accentuated in Figure 8 where we consider a quantitative analysis of the modal 𝑇1 and 𝑇2 relaxation times (from 2 here on in referred to as 〈𝑇1〉 and 〈𝑇2〉, respectively) from these distributions as a function of CPB hydration 3 time. As detailed in Figure 8, hypersaline water CPB samples exhibit delayed hydration in terms of 〈𝑇1〉 and 4 〈𝑇2〉 (suggestive of delayed pore size evolution ), relative to the tap w ater CPB samples. This delay was evaluated 5 by fitting th e modal relaxation data to an empirical exponential function of the form 6 〈𝑇𝑖〉=𝑎𝑖exp(−𝑏𝑖𝑡)+𝑐𝑖. (5) Here 𝑏𝑖 (with 𝑖=1 or 2 for 𝑇1 and 𝑇2 measurements, respectively) describes the observed decay rate which 7 characterises the size reduction of the dominant (most populous) pore structure of each sample across the 56 8 days of hydration assessed , 𝑡 is the hydration time, while 𝑎𝑖 and 𝑐𝑖 are a pre -exponential and offset parameters, 9 respectively. The offset parameter 𝑐𝑖 is necessary to describe the finite (i.e. non -zero) pore dimensions exhibited 10 by our CPB materials at long hydration times, while the apparent pore sizes at 𝑡=0 may be estima ted from 11 (𝑎𝑖+𝑐𝑖). 12 The results of th e above fitting are detailed in Table 3 . The fitted 𝑇1 data suggest that pore structure evolution 13 rates increase upon increasing the binder content from 5 wt% to 9 wt%, consistent with both the rates at which 14 capillary and interhydrate 𝑇2 populations are observed to merge in Figures 5 and 6 , and the concept that an 15 increase in binder content should lead to a greater degree of hydration product ingress into the capillary voids ; 16 no clear trend eme rges from our fitted 𝑇2 data. In terms of comparing the effect of different mixing water we 17 first consider samples containing 5 wt% binder content . Here a decrease in pore structure evolution rate is 18 observed upon moving from tap to hypersaline mixing water within both the 𝑇1 and 𝑇2 data sets, indicating that 19 the use of hypersaline water reduces the overall rate of hydration product ingress into the available capillary 20 voids. Contrasting the behaviour of tap and hypersaline water within samples containing 9 wt% binder content, 21 however, reveals similar decay rates across the two mixing waters; this behaviour is also visibly evident in 22 Figure 8. This finding, together with the above observations concerning incre ased rates of pore structure 23 evolution in the presence of increased binder content, suggests that the more rapidly developing pore structure 24 hierarchy of the materials containing 9 wt% binder may offset the retardation effects of hypersaline water. 25 18 Instead , a clear and persistent difference is observed between the tap water and hypersaline water hydrated CPB 1 data in Figure 8c and d, suggesting that the difference in pore structure (as evidenced via our relaxation 2 measurements) within these materials is domi nated by material properties at the initiation of the hydration 3 process. 4 5 Table 3: Exponential fitting data of the modal NMR relaxation data illustrated in Figure 8 according to Equation 6 (5). For brevity the rate constant 𝑏1,2 is given in units of of day-1. Uncertaintly bounds indicate the 95 % 7 confindence intevals obtained from the fitting process. 8 〈𝑇1〉 〈𝑇2〉 𝑎1 / ms 𝑏1 / day-1 𝑐1 / ms 𝑎1+𝑐1 / ms 𝑎2 / ms 𝑏2 / day-1 𝑐2 / ms 𝑎2+𝑐2 / ms Tap water 5 wt% binder 8.62 ± 0.84 0.20 ± 0.04 2.44 ± 0.3 11.06 ± 0.90 4.56 ± 0.41 0.18 ± 0.03 2.11 ± 0.19 6.67 ± 0.45 Hypersaline water 5 wt% binder 9.18 ± 0.94 0.12 ± 0.03 2.85 ± 0.60 12.03 ± 1.12 4.31 ± 0.56 0.08 ± 0.03 2.21 ± 0.53 6.52 ± 0.77 Tap water 9 wt% binder 8.26 ± 0.98 0.23 ± 0.05 1.67 ± 0.34 9.93 ± 1.02 4.29 ± 0.31 0.13 ± 0.02 1.14 ± 0.19 5.43 ± 0.36 Hypersaline water 9 wt% binder 9.61 ± 0.88 0.18 ± 0.03 1.98 ± 0.41 11.59 ± 0.97 5.04 ± 0.57 0.13 ± 0.03 1.61 ± 0.36 6.65 ± 0.67 9 19 1 Figure 8: Modal T1 and T2 relaxation time data for CPB samples comprising 5 wt% (a and b) and 9 wt% (c and 2 d) binder content and 76 wt% solids as a function of hydration time. Both common tap water (red) and 3 hypersaline water (blue) data is shown in each case. Model fits correspon d to Equation (5), with the resulting 4 parameters detailed within Table 3. 5 6 20 NMR relaxation – strength correlations 1 The mechanical properties of our CPB materials were assessed via uniaxial compressive strength (UCS) 2 analysis; these tests were performed on CPB samples following hydration for 7, 14, 28 and 56 days, providing 3 insight into the mechanical strength of these materials across the range of hydration times examin ed in our NMR 4 relaxation measurements. UCS analysis on CPB materials experiencing fewer than 7 days of hydration was not 5 possible due to the limited solidification found to have occurred before this time. 6 Figure 9 details a correlation between the observe d 〈𝑇1〉 and 〈𝑇2〉 relaxation times and the results of this UCS 7 analysis, overlaying contributions from both tap water and hypersaline water hydrated CPB materials 8 comprising 5 wt% and 9 wt% binder content. In both data sets there exists a clear trend, with sho rter relaxation 9 times correlating with increased mechanical strength. Recalling once again the relationship between NMR 10 relaxation time constants and pore size, these data clearly suggest that CPB materials exhibiting smaller 11 capillary pore structures disp lay comparatively increased mechanical strength characteristics. While there is no 12 clear difference in the UCS results of materials hydrated with tap or hypersaline mixing water at comparative 13 〈𝑇1〉 or 〈𝑇2〉 times, the lag behaviour of CPB materials hydrated w ith hypersaline water is clearly apparent within 14 these plots, wherein the hypersaline hydrated CPB is shown to exhibit noticeably reduced UCS load capacities, 15 relative to tap water hydrated CPB of the same age. 16 Importantly, the two data sets within Figure 9 are described well by an exponential relationship between 17 measured UCS and NMR relaxation characteristics; this relationship takes the form UCS =𝐴exp(−𝐵𝑖 〈𝑇𝑖〉) 18 (with 𝑖= 1 or 2). Here 𝐴= 1520 kPa is a pre -exponential load factor which was found to be independent of 19 both the NMR relaxation mechanism probed ( 𝑇1 or 𝑇2 relaxation) and the binder content of CPB, while the rate 20 constants take values of 𝐵1= 0.459 s-1 and 𝐵2= 0.558 s-1 for the 〈𝑇1〉 and 〈𝑇2〉 curves, respectively. The capacity 21 to fit such a si mple and predictive expression encompassing the relaxation and mechanical strength properties 22 of both tap water and hypersaline water hydrated CPB materials exhibiting variable binder content is clearly 23 highly desirable; indeed, this expression facilitates the prediction of CPB mechanical strength properties based 24 on the measurement of NMR relaxation times alone. It follows that such correlations provide a potential avenue 25 for the assessment of industrial site CPB formations using NMR logging tools or singl e sided magnet -based 26 spectrometers [26,49 –51]. 27 21 1 Figure 9 : Correlation of a) 〈𝑇1〉 and b) 〈𝑇2〉 NMR relaxation times against CPB UCS data. Data from materials 2 containing both 5 wt% and 9 wt% binder content are overlaid. A model exponential decay is detailed in each 3 case and discussed further in the main text . 4 22 Conclusions 1 Low-field 1H NMR relaxation measurements were utilised to investigate the microstructural characteristics of 2 CPB materials hydrated with both tap and hypersaline mixing waters. Distributions of the NMR relaxation time 3 constants 𝑇1 and 𝑇2 have been demonstrated to provide details o n the pore structure hierarchy of such mate rials, 4 with 𝑇2 data offering resolution between gel, interhydrate and capillary pore structures at short hydration times. 5 These distributions also evidenc e the time -evolution of CPB capillary pore structures across the first 56 days of 6 hydration. Contrast ing the modal NMR relaxation times associated with water confined within these capillary 7 pores provides a non -invasive route with which to quantify and compare the hydration rates of such materials; 8 we demonstrated this approach through both the considerat ion of different mixing waters and through the 9 comparison of varying binder contents. In general, t he use of hypersaline water was observed to reduce CPB 10 capillary pore hydration rates, relative to tap water . Through a direct comparison of NMR relaxation 11 measurements with UCS analysis a predictive correlation has been developed between capillary pore size and 12 mechanical strength , with small pore structures indicative of stronger CPB materials . This correlation is 13 independent of both the NMR rela xation time constant s considered and the CPB binder content employed. 14 Furthermore, it highlights a clear lag effect observed in the hydration behaviour of hypersaline hydrated CPB 15 samples, relative to tap water hydrated materials of the same age , resulting in comparatively weaker CPB 16 structures . Overall , this study provides new and unique insight into the microstructural evolution of CPB 17 materials , and highlights distinct relationships between NMR characteristics, pore structure and material 18 strength which may be further exploited in the field through the application of NMR logging tools and single - 19 sided magnets. 20 21 22 23 Acknowledgement 1 The authors acknowledge Dr Belinda Godel (CSIRO Minerals Resources) for the high resolution X -ray µCT 2 measurements at the Austra lian Resources Research Centre (ARRC). Razyq Nasharuddin acknowledges the 3 PhD financial support from the Australian Government Research Training Program (RTP) Scholarship. 4 Conflicts of Interest 5 The authors declare that they have no known competing financi al interests or personal relationships that could 6 have appeared to influence the work reported in this paper. 7 8 9 24