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At least 577 records · Page 32

Results of an interlaboratory study on the working curve in vat photopolymerization II: Towards a standardized method

The working curve measurement in photopolymer additive manufacturing is a ubiquitous measure of the cure depth of a printing resin as a function of radiant exposure of light. The fit parameters from this measurement (the depth of light penetration D p and the critical exposure E c ) are used to evaluate and report a resin’s printability, optimize processing parameters, and inform print and resin quality control. Despite its widespread use, the working curve lacks a standard measurement method. Here, following up on our paper “Results of an Interlaboratory Study on the Working Curve in Vat Photopolymerization” from last year, an interlaboratory study on the working curve was performed using calibrated, reproducible, bandpass filtered light sources. With these light sources, the variability between labs in measured working curves was dramatically reduced from the initial interlaboratory study. Aggregate data from this experiment produced reliable D p and E c measurements at 385 nm of 39.2 ± 3.7 µm and 12.3 ± 3.0 mJ cm −2 , respectively. At 405 nm the values of D p and E c are 69.3 ± 3.8 µm and 17.9 ± 2.3 mJ cm −2 , respectively. The results are agnostic to the thickness measurement tool utilized by participants, ensuring broad applicability across laboratories. We also tested the generalizability of the proposed method of using a filtered light source by filtering a commercial 405 nm light source and obtaining a working curve in agreement with the aggregate data from the interlaboratory study. This interlaboratory study provides a basis for a documentary standard for the working curve, so that the entire photopolymer additive manufacturing industry can share reproducible and interoperable working curve data.

36 MATERIALS SCIENCE↗

Noise-aware optimization in nominally identical manufacturing and measuring systems for high-throughput parallel workflows

Device-to-device variability in experimental noise critically impacts reproducibility, especially in automated, high-throughput systems like additive manufacturing farms. While manageable in small labs, such variability can escalate into serious risks at larger scales, such as architectural 3D printing, where noise may cause structural or economic failures. This contribution presents a noise-aware decision-making algorithm that quantifies and models device-specific noise profiles to manage variability adaptively. It uses distributional analysis and pairwise divergence metrics with clustering to choose between single-device and robust multi-device Bayesian optimization strategies. Unlike conventional methods that assume homogeneous devices or enforce generic robustness, the proposed framework explicitly determines whether shared optimization across devices is appropriate based on the degree of inter-device noise heterogeneity. This enables improved performance, reproducibility, and efficiency. An experimental case study involving three nominally identical 3D printers (same brand, model, and close serial numbers) demonstrates reduced redundancy, lower resource usage, and improved reliability, along with improved convergence stability and solution quality through the selection of the appropriate optimization strategy based on the degree of inter-device noise heterogeneity. Overall, this framework establishes a general approach for precision- and resource-aware optimization in scalable, automated experimental platforms, demonstrated here on a representative multi-device 3D printing case study.

Schenk, Christina↗

Quantifying carbon budget, crop yields and their responses to environmental variability using the ecosys model for U.S. Midwestern agroecosystems

As one of the major agricultural production areas in the world, the United States (U.S.) Midwest plays a vital role in the global food supply and agricultural ecosystem services. Although significant efforts have been made in modeling the carbon cycle dynamics over this area, large uncertainty still exists in the previous simulations in terms of reproducing individual components of the carbon cycle and their responses to environmental variability. Here we evaluated the performance of an advanced agroecosystem model, ecosys, in simulating carbon budgets over the U.S. Midwest, considering both the magnitude of carbon flux/yield and its response to environmental (climate and soil) variability. We conducted model simulations and evaluations at 7 cropland eddy-covariance sites as well as over 293 counties of Illinois, Indiana, and Iowa in the U.S. Midwest. The site-level simulations showed that ecosys captured both the magnitude and seasonal patterns of carbon fluxes (i.e., net ecosystem carbon exchange (NEE), ecosystem gross primary production (GPP), and ecosystem respiration (Reco)), leaf area index (LAI), and dynamic plant carbon allocation processes, with R2 equal to 0.92, 0.87, 0.87, and 0.78 for GPP, NEE, Reco, and LAI, respectively across all the sites compared with the observations. For regional scale simulations, ecosys reproduced the spatial distribution and interannual variability of corn and soybean yields with the constraints of observed yields and a new remotely sensed GPP product, with R2 of multi-year averaged simulated and observed yield equal 0.83 and 0.80 for corn and soybean, respectively. The simulated responses of carbon cycle dynamics to environmental variability were consistent with that from the empirical observations at both site and regional scales. Furthermore, our results demonstrated the applicability of ecosys in simulating the carbon cycle and soil carbon dynamics of the U.S. Midwestern agroecosystems under different climate and soil conditions.

54 ENVIRONMENTAL SCIENCES↗

Hybrid super homogenization and discontinuity factor method for continuous finite element diffusion

This paper presents a novel homogenization equivalence technique aiming to simultaneously leveragethe simplicity of the Super Homogenization (SPH) method to reproduce reference reaction rates andthe ability to preserve reference leakage rates at desired surfaces through Discontinuity Factors (DF).The need for this new class of methods arises from the inability of the current state-of-the-art SPH technology to properly reproduce the reactor multiplication factor for problems with significant leakage. This work shows that this defect lies in the use of normalization factors in the SPH algorithm: while they are necessary with purely reflecting problems to ensure uniqueness of the solution, they introduce homogenization inconsistencies if at least one vacuum boundary condition is present. Two solutions to this problem are presented in this work: (i) to simply remove the normalization factor or (ii) to introduce additional degrees of freedom in the form of DFs in such a way that the normalization factors can still constrain the problem. While the former clearly offers unrivaled simplicity and can lead to very satisfactory results for leakage-dominated cores or if spatial restriction of the SPH regions is applied – as demonstrated for the High Temperature Test Reactor, the latter is more robust and does not require to scale the fission terms with the reference eigenvalue.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Advances in the calculation of optical properties in superlattices; novel insights derived from the theory of finite periodic systems

Highlights: • Truly quantum calculation of optical properties in superlattices. • An approach that goes beyond the abilities of the current approaches in the literature. • Accurate calculations based on bona fide superlattice eigenvalues and eigenfunctions. • Accurate calculation of optical-transition matrix elements and new selection rules. • Optical spectra of AlGaAs and InGaN superlattices agree with experimental results. • Optical spectra features of blue diodes faithfully reproduced and fully explained. • Unexplained lines in high-resolution spectra assigned to surface and edge states. - Abstract: Using the genuine superlattice eigenvalues and eigenfunctions, and their parity symmetries, new transition selection rules are derived, and a novel approach for the explicit calculation of the optical spectra of periodic structures presented. The optical response and infrared spectra published in the last 40 years for (In, Ga)N and (Al, Ga)As superlattices, with different number of unit cells n (varying from ∼10 to ∼400) and barrier and valley widths in the range of 2.5 nm to 40 nm, and different properties have been revisited. Among the various examples discussed here, we study the narrow peaks clustered in groups reported in high resolution spectra of blue-emitting devices, that could not be explained until now. These properties are faithfully reproduced and fully understood. We show that these effects are related to and depend on the surface energy levels and their tuneable detachment. We shown also that the optical transitions experimentally observed, but forbidden by the current optical physics, are really allowed transitions. Since the number of energy eigenvalues E{sub μ,ν}{sup r,v} and eigenfunctions Ψ{sub μ{sup ′},ν{sup ′r,v}}(z) is now much greater, the number of allowed matrix-elements can be extremely large (of the order of n{sup 2} n{sub c}n{sub v}∕2, with n{sub c} and n{sub v} the number of subbands in the conduction and valence bands). We show that this number can be reduced by using the eigenfunctions’ symmetries, which are behind the parity symmetry selection rules and the leading order selection rules. These rules reduce the number of matrix-elements evaluations from ∼n{sup 2}n{sub c}n{sub v}∕2 to ∼nn{sub c}n{sub v}∕2, i.e., depending on the superlattice, from about 1000 to 100. We discuss also a third rule, that collects the contributions of the surface and edge states, reducing the number of transitions even more to N{sub s}≤n{sub c}n{sub v}. With these rules, the main peaks are conserved and their number practically matches that of the real spectrum. Excellent agreements are found with experimental results.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Numerical analysis of experimental studies of methane hydrate dissociation induced by depressurization in a sandy porous medium

Methane Hydrates (MHs) are a promising energy source abundantly available in nature. Understanding the complex processes of MH formation and dissociation is critical for the development of safe and efficient technologies for energy recovery. Many laboratory and numerical studies have investigated these processes using synthesized MH-bearing sediments. A near-universal issue encountered in these studies is the spatial heterogeneous hydrate distribution in the testing apparatus. In the absence of direct observations (e.g. using X-ray computed tomography) coupled with real time production data, the common assumption made in almost all numerical studies is a homogeneous distribution of the various phases. In an earlier study (Yin et al., 2018) that involved the numerical description of a set of experiments on MH-formation in sandy medium using the excess water method, we showed that spatially heterogeneous phase distribution is inevitable and significant. In the present study, we use as a starting point the results and observations at the end of the MH formation and seek to numerically reproduce the laboratory experiments of depressurization-induced dissociation of the spatially-heterogeneous MH distribution. This numerical study faithfully reproduces the geometry of the laboratory apparatus, the initial and boundary conditions of the system, and the parameters of the dissociation stimulus, capturing accurately all stages of the experimental process. Using inverse modelling (history-matching) that minimized deviations between the experimental observations and numerical predictions, we determined the values of all the important flow, thermal, and kinetic parameters that control the system behaviour, which yielded simulation results that were in excellent agreement with the measurements of key monitored variables, i.e. pressure, temperature, cumulative production of gas and water over time. We determined that at the onset of depressurization (when the pressure drop – the driving force of dissociation – is at its maximum), the rate of MH dissociation approaches that of an equilibrium reaction and is limited by the heat transfer from the system surroundings. Furthermore, as the effect of depressurization declines over time, the dissociation reaction becomes kinetically limited despite significant heat inflows from the boundaries, which lead to localized temperature increases in the reactor.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Isospin symmetry holds beyond the proton drip line: First observation of excited states in 55Cu

Isospin symmetry, combined with shell-model description, has long been successful in reproducing nuclear structure and predicting mirror energy differences. However, these descriptions have been primarily limited to mirror nuclei with well-bound ground states. As one approaches the proton drip line, coupling to the continuum becomes important. Despite this, little is known about medium-mass nuclei at the drip line. Here we report the measurement of the excitation energies of several unbound states in a nucleus beyond the proton drip line, 55Cu, performed via γ-ray spectroscopy at the Radioactive Isotope Beam Factory (RIKEN). Several low-lying yrast states are observed to decay predominantly by γ-ray emission. In contrast, the state–predicted to be strongly populated in the one-proton knockout reaction–is notably absent, suggesting that it decays primarily via prompt proton emission. We show that even for such an unbound system, shell-model calculations based on a harmonic oscillator potential reproduce the observed mirror energy differences remarkably well in all the observed states. Based on this result, we propose that a general pattern might emerge where, in medium-mass systems at the proton drip line, the stronger Coulomb barrier together with the centrifugal barrier effectively confines the wave functions, so that the shell model is able to describe low-lying states, enabling accurate predictions of mirror energy differences between isobaric analogue states.

Pigliapoco, S [Dipartimento di Fisica e Astronomia↗

Exosomal proteome analysis of human plasma to monitor sepsis progression

Highlights: • As low as 300 μL human plasma is sufficient for exosome isolation using our one-step density gradient ultracentrifugation. • Protein profiling of septic plasma exosomes are closely related to immune responses. • SPTLC3 may play important roles in development of sepsis. Exosomes are cell-derived vesicles containing RNA, lipid, and protein, which act in body immune response, intercellular signaling and some other important biological processes. Exosomes have been extensively studied in the past several years on their disease related mechanisms and potential roles to monitor disease progression as biomarkers. Compared with analyzing exosome RNA, comprehensive proteome profiling of exosomes in clinical samples (e.g. blood) are highly demanded but limited mainly due to lack of a reproducible method for efficient exosome extraction. In this study, we evaluated and optimized an exosome preparation approach using one-step ultracentrifugation through an Optiprep™ cushion. Exosomes prepared via this method and analyzed by mass spectrometry using Q-Exactive plus, has led to reproducible identification and quantification of 200 + proteins from human plasma samples of as little as 300 μL. Therefore, such a straightforward exosome extract method has enable us to deeply profile exosome proteomes from human blood at a scale of clinical studies. As a proof of principal, we practiced this approach in analyzing the exosome proteomic profiles of blood samples collected from a sepsis patient during six time points after diagnosis. Among the 238 proteins identified and quantified across the 6 samples, protein SPTLC3 involved in the sphingolipid metabolism, shows a negative correlation (p = 0.02, correlation coefficient = −0.984) with disease progression indicated by body temperature (BD) and C-reactive protein (CRP). Therefore, SPTLC3 could be an interesting target for future study on molecular mechanism of sepsis development, as well as potential classifier to monitor clinical progression of sepsis.

60 APPLIED LIFE SCIENCES↗

A spherical aberration-free microscopy system for live brain imaging

Highlights: • Deep-C is an automatic spherical aberration compensation system for in vivo imaging. • Deep-C is composed of ZlinC and Peak-C. • ZlinC coordinates the correction collar rotation and the Z-position of an objective. • Peak-C is a scanning algorithm processor for calculation of image contrast. • Deep-C allows quantitative, reproducible analysis of fine GFP-labeled structures. The high-resolution in vivo imaging of mouse brain for quantitative analysis of fine structures, such as dendritic spines, requires objectives with high numerical apertures (NAs) and long working distances (WDs). However, this imaging approach is often hampered by spherical aberration (SA) that results from the mismatch of refractive indices in the optical path and becomes more severe with increasing depth of target from the brain surface. Whereas a revolving objective correction collar has been designed to compensate SA, its adjustment requires manual operation and is inevitably accompanied by considerable focal shift, making it difficult to acquire the best image of a given fluorescent object. To solve the problems, we have created an objective-attached device and formulated a fast iterative algorithm for the realization of an automatic SA compensation system. The device coordinates the collar rotation and the Z-position of an objective, enabling correction collar adjustment while stably focusing on a target. The algorithm provides the best adjustment on the basis of the calculated contrast of acquired images. Together, they enable the system to compensate SA at a given depth. As proof of concept, we applied the SA compensation system to in vivo two-photon imaging with a 25 × water-immersion objective (NA, 1.05; WD, 2 mm). It effectively reduced SA regardless of location, allowing quantitative and reproducible analysis of fine structures of YFP-labeled neurons in the mouse cerebral cortical layers. Interestingly, although the cortical structure was optically heterogeneous along the z-axis, the refractive index of each layer could be assessed on the basis of the compensation degree. It was also possible to make fully corrected three-dimensional reconstructions of YFP-labeled neurons in live brain samples. Our SA compensation system, called Deep-C, is expected to bring out the best in all correction-collar-equipped objectives for imaging deep regions of heterogeneous tissues.

60 APPLIED LIFE SCIENCES↗

MYPT1 is targeted by miR-145 inhibiting viability, migration and invasion in 2D and 3D HeLa cultures

Highlights: • miR-143/145 affect viability, migration and invasion on monolayer and spheroid cultures. • miR-145 produces a stronger inhibitory effect and increases pMLC levels through MYPT1 targeting. • MYPT1 silencing by siRNAs reproduces miR-145 effects. The miR-143/145 cluster is down-regulated in cervical tumor cells suggesting a role in tumorigenesis including cytoskeleton remodeling, a key event for tumor progression. The aim of the present work was to determine the role of miR-143/145 in the modulation of the myosin regulator phospho-myosin light chain (pMLC). HeLa monolayer and tridimensional cultures were transfected with miR-143 or miR-145 mimics inhibiting cell viability, proliferation, migration and invasion, mainly through miR-145. MiR-145 transfection increased pMLC levels by targeting the MYPT1 subunit of the regulatory myosin phosphatase. MYPT1 knockdown by siRNAs reproduced miR-145 effects suggesting miR-145 as a tumor suppressor through MYPT1 targeting, leading to a subsequent increase of pMLC levels with implications for cervical cell viability, migration and invasion.

60 APPLIED LIFE SCIENCES↗

Can classical DEM simultaneously capture compressibility and flowability of milled biomass?

Accurate prediction of the rheological behavior of biomass is essential for the design and operation of hoppers, feeders, and storage systems in biorefineries. This study examines whether the classical, coarse-grained discrete element method (DEM) formulation can simultaneously reproduce the compressibility and flowability of milled herbaceous biomass, using Miscanthus × giganteus as a representative material. The model represents particles as rigid spheres interacting through Hertz-Mindlin elastic-frictional contacts augmented with an area-dependent cohesion term. Laboratory cyclic compression and wedge-shaped hopper discharge experiments were used as calibration benchmarks. Although the model can independently reproduce each behavior by appropriately tuning particle Young's modulus E and cohesion energy density k, an extensive parametric investigation comprising more than 600 simulations reveals that the optimal parameter regions for compression and hopper flow are distinct and non-overlapping in (E, k) space. Surrogate surface analysis further shows that the corresponding objective-function valleys exhibit similar trends but are approximately parallel and spatially offset, precluding a unified calibration within the explored domain. Sensitivity analysis indicates that compressibility is governed predominantly by stiffness and cohesion, whereas the slope of the mass flow rate-opening relation in hopper discharge is primarily controlled by tangential friction. Extensions incorporating particle size distribution and clumped-sphere representations do not eliminate the incompatibility. These results systematically reveal, for the first time, the structural limitation of simplified DEM formulations in representing biomass rheological behavior, underscoring the necessity for models incorporating additional physical mechanisms, such as particle deformability or enhanced interlocking, to achieve unified predictive capability for biomass handling behavior.

09 BIOMASS FUELS↗

Hybrid geological modeling: Combining machine learning and multiple-point statistics

Accurately modeling and constructing a geologically realistic subsurface model remains an outstanding problem as the morphology controls the flow behaviors. Particularly, one of the pattern-based methods, namely cross-correlation based simulation, has been proved to be an effective way to reconstruct a realistic model, at both small and large scales. However, conditioning to point data in the large-scale problems is still a crucial issue in these algorithms, since there is always a trade-off between the quality of the realizations and the degree of point data reproduction. Specifically, it is not practical to build a training image (TI) which includes all the possibilities and variabilities. Therefore, finding a pattern that can represent the point data and, at the same time, preserving the connectivities is difficult. This leads to producing highly-connected realizations with a significant mismatch or poor models with a reasonable degree of point data reproduction. To accurately reproduce the densely distributed hard data, pixel-based methods can also produce some unrealistic artifacts around the hard data. In this paper, to overcome this challenge, however, we use pattern-based methods as they often produce more disconnected geobodies when dealing with dense hard data, and proposed a hybrid algorithm using the pattern-based methods and convolutional neural network (CNN). The trained CNN model is utilized to improve the quality of conditioning to point data for the original realizations generated by the pattern-based algorithm. As such, the mismatch locations are identified, and the same regions are used in the training of CNN to mimic the procedure through which a missing region can be filled. To evaluate the performance of the proposed hybrid algorithm, it is tested on cases with different dimensions and different numbers of facies. Then, the newly improved realizations are compared with the initial realizations generated by the pattern-based algorithm. The comparison is also conducted by the flow simulation test. And it indicates that the proposed hybrid algorithm can better reproduce the point data, while the connectivities are better preserved.

58 GEOSCIENCES↗

Genome-wide fetalization of enhancer architecture in heart disease

Heart disease is associated with re-expression of key transcription factors normally active only during prenatal development of the heart. However, the impact of this reactivation on the regulatory landscape in heart disease is unclear. Here, we use RNA-seq and ChIP-seq targeting a histone modification associated with active transcriptional enhancers to generate genome-wide enhancer maps from left ventricle tissue from up to 26 healthy controls, 18 individuals with idiopathic dilated cardiomyopathy (DCM), and five fetal hearts. Healthy individuals have a highly reproducible epigenomic landscape, consisting of more than 33,000 predicted heart enhancers. In contrast, we observe reproducible disease-associated changes in activity at 6,850 predicted heart enhancers. Combined analysis of adult and fetal samples reveals that the heart disease epigenome and transcriptome both acquire fetal-like characteristics, with 3,400 individual enhancers sharing fetal regulatory properties. We also provide a comprehensive data resource (http://heart.lbl.gov) for the mechanistic exploration of DCM etiology.

60 APPLIED LIFE SCIENCES↗

Hygro-thermo-mechanical modeling of partially saturated air-entrained concrete containing dissolved salt and exposed to freeze-thaw cycles

Highlights: • A model for cyclic freezing of air-entrained concrete containing salt is proposed. • The freeze-thaw hysteresis, also including the effect of dissolved salt, is modeled. • The diffusive and convective flux of salt is coupled to the freeze-thaw processes. • The freeze-thaw response of air-entrained concrete containing salt is reproduced. • Liquid absorption from reservoirs increases with an increased concentration of salt. In cold regions, understanding the freeze-thaw behavior of air-entrained concrete is important for designing durable structures and assessing the remaining service life of existing structures. This study presents a hygro-thermo-mechanical multiphase model that describes the cyclic freeze-thaw behavior of partially saturated air-entrained concrete containing dissolved salt. An equilibrium and a non-equilibrium approach are adopted to model the ice formation, including the freeze-thaw hysteresis, inside the porous network. The model also considers the diffusive and convective transport of the dissolved salt coupled to the freeze-thaw processes. Two examples are presented to verify and highlight the capabilities of the model. The first example shows that the model is capable of reproducing the experimentally observed mechanical response of specimens containing NaC1-solutions of different concentrations. In the second example, a larger absorption of liquid from an external reservoir is obtained with an increasing salt concentration in the reservoir, which is consistent with experimental observations.

36 MATERIALS SCIENCE↗

Experimental and modeling studies of PR and ND oxalate solubility to high ionic strengths: Insight into actinide(III) oxalates

Actinide oxalates are chemical compounds important to nuclear industry, ranging from actinide separation in waste reprocessing, to production of specialty actinides, and to disposal of high level nuclear waste (HLW) and spent nuclear fuel (SNF). In this study, the solubility constants for Pr 2 (C 2 O 4 ) 3 •10H 2 O and Nd 2 (C 2 O 4 ) 3 •10H 2 O by performing solubility experiments in HNO 3 and mixtures of HNO 3 and H 2 C 2 O 4 at 23.0 ± 0.2 °C have been determined. The targeted starting materials, Pr 2 (C 2 O 4 ) 3 •10H 2 O and Nd 2 (C 2 O 4 ) 3 •10H 2 O, were successfully synthesized at room temperature using PrCl 3 , NdCl 3 and oxalic acid as the source metrials. Then, we utilized the targeted solubility-controlling phases to conduct solubility measurements. There was no phase change over the entire periods of experiments, demonstrating that Pr 2 (C 2 O 4 ) 3 •10H 2 O and Nd 2 (C 2 O 4 ) 3 •10H 2 O were the solubility-controlling phases in our respective experiments. Based on our experimental data, we have developed a thermodynamic model for Pr 2 (C 2 O 4 ) 3 •10H 2 O and Nd 2 (C 2 O 4 ) 3 •10H 2 O in the mixtures of HNO 3 and H 2 C 2 O 4 to high ionic strengths. The model for Pr 2 (C 2 O 4 ) 3 •10H 2 O reproduces well the reported experimental data for Pu 2 (C 2 O 4 ) 3 •10H 2 O, which are not utilized for the model development, demonstrating that Pr(III) is an excellent analog for Pu(III). Similarly, the model for Nd 2 (C 2 O 4 ) 3 •10H 2 O reproduces the solubility of Am 2 (C 2 O 4 ) 3 •10H 2 O and Cm 2 (C 2 O 4 ) 3 •10H 2 O. The Pitzer model was used for the calculation of activity coefficients. Based on the published, well established model for dissociation constants for oxalic acid and stability constants for actinide-oxalate complexes [i.e., AmC 2 O 4 + , and Am(C 2 O 4 ) 2 - ] to high ionic strengths, we have obtained the solubility constants (log 10 K 0 ) for the following reactions at 25 °C, Pr 2 (C 2 O 4 ) 3 •10H 2 O ⇌ 2Pr 3+ + 3C 2 O 4 2- + 10H 2 O(l). Nd 2 (C 2 O 4 ) 3 •10H 2 O ⇌ 2Nd 3+ + 3C 2 O 4 2- + 10H 2 O(l). to be -30.82 ± 0.30 (2σ), and - 31.14 ± 0.35 (2σ), respectively. These values for can be directly applied to Pu 2 (C 2 O 4 ) 3 •10H 2 O, Am 2 (C 2 O 4 ) 3 •10H 2 O and Cm 2 (C 2 O 4 ) 3 •10H 2 O. The model established for actinide oxalates by this study provides the needed knowledge with regard to solubilities of actinide/REE oxalates at various ionic strengths, and is expected to find applications in many fields, including the geological disposal of nuclear waste and the mobility of REE under the surface conditions, as Pr 2 (C 2 O 4 ) 3 •10H 2 O and Nd 2 (C 2 O 4 ) 3 •10H 2 O can be regarded as the pure Pr and Nd end-members of deveroite, a recently discovered natural REE oxalate with the following stoichiometry, (Ce 1.01 Nd 0.33 La 0.32 Pr 0.11 Y 0.11 Sm 0.01 Pb 0.04 U 0.03 Th 0.01 Ca 0.04 ) 2.01 (C 2 O 4 ) 2.99 •9.99H 2 O. Regarding its importance in the geological disposal of nuclear waste, Am 2 (C 2 O 4 ) 3 •10H 2 O/Pu 2 (C 2 O 4 ) 3 •10H 2 O/Cm 2 (C 2 O 4 ) 3 •10H 2 O can be the source-term phase for actinides, as demonstrated by the instance in the disposal in clay/shale formations. This is exemplified by the stability of Am 2 (C 2 O 4 ) 3 •10H 2 O in comparison with Am(OH) 3 (am), Am(OH) 3 (s) and AmCO 3 (OH)(s) under the relevant geological repository conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Uniformity and volume-representativity of consecutive submillimetre wafers of shale for SANS and USANS investigations

(Ultra) Small Angle Neutron Scattering (SANS/USANS) is a non-destructive technique suitable for characterization of porous structures from nano- to micro-pore size (1 nm to 20 μm), which has been widely used to characterize accessible and inaccessible porosity in tight unconventional hydrocarbon reservoirs (e.g., shales). Here, in this study, SANS and USANS are used to examine the degree of nano- to micropore uniformity of the rock body on sub-millimetre to centimetre scale. This study presents a test of the hypothesis of volume representativity of pore structure information measured by SANS and USANS for shale wafers (0.22–1 mm) cut from six North American unconventional shale cores of different maturities (New Albany Shale and Marcellus Shale). Experimental reproducibility of USANS is further investigated for two wafers measured using various acquisition times. All samples show that fluctuations of the relative intensity generally decrease from the USANS Q-range (pore size from around 200 nm to 20 μm) to most of the SANS Q-range (pore size from around 5 nm to 700 nm), and peaks in the SANS large-Q region (for pores smaller than about 5 nm). There is a positive correlation between the spatial fluctuation of the relative SANS intensity and the scattering power of shales. In addition, the scattering intensity and its fluctuations is larger for the less mature shale cores. Shale is known to be highly heterogenous and the hypothesis of uniformity does not apply at sub-millimetre scale even for samples that appear homogeneous at visual inspection. This study presents an approach to minimise the variation through sample selection, data interpretation methodology and instrumental reproducibility tests. The best values of the microstructural spatial uniformity for the apparently homogeneous sections of a core (i.e., the SANS and USANS intensity variation) is less than ±10%.

01 COAL, LIGNITE, AND PEAT↗

Front propagation formulation for large eddy simulation of turbulent premixed flames

The front propagation formulation (FPF) for large eddy simulation (LES) of turbulent premixed flames is presented and discussed. The FPF method adopts a regularized Dirac delta function to minimize the spurious propagation of under-resolved filtered flame fronts in LES, while reproducing the reaction characteristics of premixed flame fronts. Here, the extension of the FPF method to LES and the relation to existing sub-filter combustion models are discussed. An algebraic model for the regularized Dirac delta function is presented and validated using direct numerical simulation (DNS) data for statistically planar premixed flames propagating in homogeneous isotropic turbulence. A posteriori validation for a filtered 1-D planar laminar flame is performed to demonstrate the characteristics of FPF in reproducing the propagation speed and the thickness of the under-resolved flame front. LES of a turbulent Bunsen flame is also performed to demonstrate the performance of the proposed method.

42 ENGINEERING↗