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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

How to determine limiting velocities of dislocations in anisotropic crystals

In the continuum limit, the theory of dislocations in crystals predicts a divergence in the elastic energy of the host material at a crystal geometry dependent limiting (or critical) velocity vc. Explicit expressions for vc are scattered throughout the literature and are available in analytic form only for special cases with a high degree of symmetry. The fact that in some cases (like pure edge dislocations in fcc) v c happens to coincide with the lowest shear wave speed of a sound wave traveling parallel to the dislocation's gliding direction has led to further confusion in the more recent literature. The aim of this short review therefore is to provide a concise overview of the limiting velocities for dislocations of arbitrary character in general anisotropic crystals, and how to efficiently compute them, either analytically or numerically.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Modeling Single and Two-Phase Transport in Thin Porous Layers Using a Composite Continuum-Pore Network Formulation

In this work, a composite continuum-pore network formulation is presented to model single and two-phase transport thin porous layers, such as gas diffusion layers in polymer electrolyte fuel cells (PEFCs) and active electrodes in redox flow batteries (RFBs). The formulation can be integrated into CFD codes, thus combining the ease of implementation of continuum-based modeling and the computational power of pore-network modeling. The composite model includes a control volume (CV) mesh at the layer scale, which embeds a cubic pore network [1,2]. The pore-network model is used to determine analytically local anisotropic effective transport properties (local effective diffusivity and permeability), which are mapped onto the CV mesh to simulate transport in the porous transport layer [3,4]. Good agreement is found between the predicted global effective transport properties (global effective diffusivity and permeability) under dry and wet conditions and previous experimental data reported in the literature for Toray TGP-H series carbon paper. Water saturation distributions are also compared with results obtained using X-ray computed tomography [4]. [1] P.A. García-Salaberri, I.V. Zenyuk, J.T. Gostick, A.Z. Weber, Modeling Gas Diffusion Layer in Polymer Electrolyte Fuel Cells Using a Continuum-Based Pore-Network Formulation, ECS Trans. 97 (2020) 615. [2] P.A. García-Salaberri, Modeling diffusion and convection in thin porous transport layers using a composite continuum-network model: Application to gas diffusion layers in polymer electrolyte fuel cells, Int J. Heat Mass Transf. (2020), submitted. [3] P.A. García-Salaberri, J.T. Gostick, G. Hwang, A.Z. Weber, M. Vera, Effective diffusivity in partially-saturated carbon-fiber gas diffusion layers: Effect of local saturation and application to macroscopic continuum models, J. Power Sources 296 (2015) 440–453. [4] P.A. García-Salaberri, G. Hwang, M. Vera, A.Z. Weber, J.T. Gostick, Effective diffusivity in partially-saturated carbon-fiber gas diffusion layers: Effect of through-plane saturation distribution, Int. J. Heat Mass Transf. 86 (2015) 319–333.

Garcia-Salaberri, Pablo↗
DOE OSTI2026

Historic climate, cosmogenic 10Be, denudation-rate, and geospatial datasets from the Pikes Peak region, Colorado, USA

This data package contains geographic information system (GIS) layers and tabular datasets associated with the study of elevation-dependent denudation rates on Pikes Peak in the Front Range of the Rocky Mountains, Colorado, USA. The package includes GIS layers used to produce the study-area map, including sample locations, sample watershed boundaries, the Pikes Peak batholith, Pleistocene glacier extent, weather station locations, and elevation and hillshade rasters, together with comma-separated value (CSV) tables and matching CSV data dictionaries. These mapped layers provide the geographic framework for interpreting denudation patterns across the Pikes Peak region and for relating sample locations to watershed geometry, bedrock setting, glacial history, and nearby climate stations. The first group of tables reports climate and geospatial context for the study area. These files include station-based temperature and precipitation data used to characterize elevational gradients in mean annual climate and monthly climate seasonality, sample locations, denudation-rate and topographic metrics, fixed frost-cracking model parameters, frost-cracking intensity and precipitation-frequency metrics, and stream-power inversion results. Together, these data provide the basis for evaluating how denudation varies with elevation, climate, and landscape form across sampled catchments on Pikes Peak. The second group of tables reports cosmogenic nuclide and erosion-model results used in the denudation analysis. Included files contain accelerator mass spectrometry (AMS) measurements for in situ-produced cosmogenic beryllium-10 (10Be), including sample identifiers, measured 10Be:9Be ratios, analytical uncertainties, carrier mass, quartz mass, blank corrections, blank-group statistics, and calculated 10Be concentrations and uncertainties. Additional tables summarize stream-power-law inversion results for sampled catchments, including optimized model parameters, predicted erosion rates, residual metrics, channel-pixel counts, and convergence status, as well as regression equations and summary statistics used to evaluate relationships among elevation, climate, frost cracking, precipitation forcing, and denudation rate. The package contains GIS files, comma-separated value files (.csv), Microsoft Excel files (.xlsx), CSV data dictionaries, a file-level metadata table, and a readme text file.

10Be cosmogenic nuclides↗
DOE OSTI2023

Fast and Thermal Neutron Spectrum Dosimetry Measurements in the Advanced Test Reactor large-B and small-I Positions Following the Sixth Core Internals Change-out [Slides]

The Advanced Test Reactor (ATR) has a wide variety of irradiation positions that have had experiments that were developed by users from around the world. Most experiment irradiations rely on thoroughly benchmarked numerical models. However, some irradiation positions in ATR are not as well- characterized and are complicated by spectral perturbations from control cylinder orientation. The “small I” and “large-B” irradiation positions are located nearby control cylinders and suffer from these flux perturbations from control cylinder orientations that change during an irradiation cycle to maintain the desired core power distribution. Models predicted that these types of position would exhibit both spectral shifts and amplitude changes in neutron flux, but few measurements have been conducted to benchmark these predictions. Recently, requalification testing was performed to confirm the operational readiness of the ATR following the completion of the Core Internals Change-out (CIC). These tests provided a unique opportunity to validate the analytical methods used to simulate the ATR because nearly all components in the reactor were in a clean as-built state, significantly reducing modelling uncertainties. One subset of the testing included characterization of the fast and thermal neutron flux in the “small-I” and “large-B” positions using silver, cobalt, and nickel neutron dosimetry. In contrast to typical irradiation cycles, the control cylinders were held in position during the post-CIC nuclear testing. The specific activity of these dosimeter wires was measured following two low-power tests with different control cylinder positions.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2024

A Self Consistent 2D Simulation of Coherent Synchrotron Radiation Effects on Beam Dynamics

An increasing interest in high quality and high current electron beams necessitates a thorough understanding and prediction of coherent synchrotron radiation effects. The self-interaction of charged particles in a beam undergoing synchrotron motion is a physically significant process that is all too often computationally intensive with very little analytical results to rely on for the general case. The coherent spectrum of this interaction is of utmost importance to the design of free electron lasers (FELs) and an accurate assessment is imperative for their design. This work presents a novel implementation to the numerical simulation of charged particle beams. The simulation is a self-consistent approach including the self-fields generated by the beam of which coherent synchrotron radiation effects are of primary interest. A particle-in-cell model is used where a planar beam sampled by point particles is deposited on an encompassing grid at each timestep. The electromagnetic fields are calculated on the grid using the retarded potentials according to causality. The electromagnetic forces from the fields are interpolated on each particle which in turn advance in time. The simulation is benchmarked against well-established results for coherent synchrotron radiation effects. In addition, studies are provided that show the convergence of simulation results for increasing resolution. A study into the transverse beam size effects on beam dynamics is performed as well as a proof of concept where the simulation is used by a genetic algorithm to optimize the design parameters of a beam lattice. The results of these studies in tandem verify the efficacy of the simulation for its practical use in accelerator design or the study of synchrotron radiation effects

Duffin, Dallan [Old Dominion Univ., Norfolk, VA (U↗
DOE OSTI2024

A317_Fast and Thermal Neutron Spectrum Dosimetry Measurements in the Advanced Test Reactor large-B and small-I Positions Following the Sixth Core Internals Change-out

The Advanced Test Reactor (ATR) has a wide variety of irradiation positions that have had experiments that were developed by users from around the world. Most experiment irradiations rely on thoroughly benchmarked numerical models. However, some irradiation positions in ATR are not as well- characterized and are complicated by spectral perturbations from control cylinder orientation. The “small I” and “large-B” irradiation positions are located nearby control cylinders and suffer from these flux perturbations from control cylinder orientations that change during an irradiation cycle to maintain the desired core power distribution. Models predicted that these types of position would exhibit both spectral shifts and amplitude changes in neutron flux, but few measurements have been conducted to benchmark these predictions. Recently, requalification testing was performed to confirm the operational readiness of the ATR following the completion of the Core Internals Change-out (CIC). These tests provided a unique opportunity to validate the analytical methods used to simulate the ATR because nearly all components in the reactor were in a clean as-built state, significantly reducing modelling uncertainties. One subset of the testing included characterization of the fast and thermal neutron flux in the “small-I” and “large-B” positions using silver, cobalt, and nickel neutron dosimetry. In contrast to typical irradiation cycles, the control cylinders were held in position during the post-CIC nuclear testing. The specific activity of these dosimeter wires was measured following two low-power tests with different control cylinder positions.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2021

How Snow Aggregate Ellipsoid Shape and Orientation Variability Affects Fall Speed and Self-Aggregation Rates

Snow aggregate shapes and orientations have long been known to exhibit substantial variability. Despite this observed variability, most weather and climate prediction models use fixed power-law functions that deterministically map particle size to mass and fall speed. As such, integrated quantities like precipitation and self-aggregation rates currently ignore nonlinear effects resulting from variation in shape and orientation for aggregates of the same size. This study therefore develops an analytic framework that couples an empirically based bivariate distribution of ellipsoid shapes to classical hydrodynamic theory so as to capture an appropriate dispersion of masses, projected areas, and fall speeds for an assumed size distribution. For a fixed aggregate size, shape variations produce approximately ±0.13 m s -1 standard deviation of fall speed which increases the mass flux fall speed dispersion by more than 100% over traditional microphysics models. This increased fall speed dispersion results predominantly from shape-induced mass dispersion whereas orientation and drag dispersion play a lesser role. Shape variations can increase mass- and reflectivity-weighted fall speeds by up to 60% of traditional models whereas self-aggregation rates can increase by a factor of 100 for very small slope parameters. This implies that aggregate shape variations effectively forestall the theorized onset of fall speed distribution narrowing and subsequent quenching of the aggregation process. As a result, it is likely that secondary ice formation is necessary to prevent an ever decreasing slope parameter. The mathematical theory presented in this study is used to develop simple correction factors for snow forecast and climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Ensemble methods for quantification of potassium oxide in ChemCam Mars and laboratory spectra

In this paper we test new approaches for predicting the amount of element oxides in rock samples from the ChemCam instrument suite onboard the NASA Curiosity rover by focusing on K 2 O. Using the expanded dataset compiled by Gasda et al. (2021) with and without the Earth to Mars (E2M and NoE2M) transformation discussed in Clegg et al. (2017) we trained blended submodels using the “double blending” technique and compared these to ensemble methods (Random Forest, ExtraTrees, and Gradient Boosting Regression). We found that ensemble methods performed similar to blended submodels when looking at RMSE-P on the laboratory spectra and provided significant advantages when looking at spectra coming from Mars. For the full model, blended submodels achieved an RMSE-P of 0.62 and 0.60 (E2M and NoE2M respectively) while Gradient Boosting Regression resulted in a slightly improved RMSE-P of 0.59 and 0.60. More importantly, by employing a local RMSE-P estimation technique where model performance is evaluated based on nearby test samples we found that using ensemble methods can lower the quantification limit for K 2 O from the current value of ≈0.6 wt% to ≈0.08 wt% using Extra Trees and Random Forest. This would allow for a much larger range of K 2 O values to be quantified on Mars with greater certainty given that most targets seen on Mars tend to have <1 wt% K2O. Finally, we used both Mean Decrease in Impurity (MDI) and permutation importance techniques to investigate the wavelengths used by the ensemble methods and found that they correspond to known potassium emission lines. This suggests that ensemble methods can provide an easier to train and improved alternative to blended submodels for predicting potassium compositions from Laser Induced Breakdown Spectroscopy (LIBS) data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Observation of an Unexpected n -Type Semiconducting Behavior in the New Ternary Zintl Phase Eu 3 InAs 3

The ternary arsenides Eu 3 InAs 3 and Sr 3 InAs 3 have been obtained by reactions of the elements in In flux at 1373 K. Structure elucidation by single-crystal X-ray diffraction reveals that Eu 3 InAs 3 and Sr 3 InAs 3 adopt the same orthorhombic structure (space group Pnma, Z = 4, Ca 3 AlAs 3 structure type) with unit cell parameters a = 12.9179(9) Å, b = 4.3990(3) Å, c = 13.9337(10) Å and a = 13.0218(11) Å, b = 4.4364(4) Å, c = 14.1339(12) Å, respectively. The structure consists of linear chains of corner-sharing InAs4 tetrahedra, [InAs 2 As 2/2 ] 6– , and Eu 2+ /Sr 2+ cations. Therefore, both Eu 3 InAs 3 and Sr 3 InAs 3 are valence-precise Zintl phases. As expected from the closed-shell electronic configurations, semiconducting behavior is confirmed by resistivity measurements on single crystals for both and by electronic band structure calculations for Sr 3 InAs 3 . The temperature dependence of resistivity and the computational work are in agreement that Eu 3 InAs 3 and Sr 3 InAs 3 are intrinsic semiconductors with narrow band gaps. Thermopower measurement on single-crystalline samples of Eu 3 InAs 3 shows that in the whole measured temperature range, from 300 to 700 K, the values for the Seebeck coefficient are negative. The observation of a negative Seebeck coefficient with very large absolute value (>400–500 μV K –1 at 700 K) is unexpected among the Zintl phases and suggestive that electrons are the majority charge carriers. Such a rare, n-type charge transport in an undoped compound such as Eu 3 InAs 3 , a material that has not been purposely optimized, could indicate native “defect” chemistry, and not extrinsic doping, as a reason for the unusual behavior. Here, a possible explanation involves a mixed-valent Eu 2+ /Eu 3+ state, which might be inferred from the measured effective paramagnetic moment of 7.2 μB per Eu atom, which is lower than the theoretically predicted value for free-ion moment of 7.9 μ B /Eu.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Dynamic Surface Incorporation of Pb 2+ Ions at the Actively Dissolving Calcite (104) Surface

The reaction of dissolved Pb 2+ with calcite surfaces at near-equilibrium conditions involves adsorption of Pb 2+ and precipitation of secondary heteroepitaxial Pb-carbonate minerals. A more complex behavior is observed under far-from-equilibrium conditions, including strong inhibition of calcite dissolution, development of microtopography, and near-surface incorporation of multiple monolayers (ML) of Pb 2+ without precipitation of secondary phases [where 1 ML ≡ 1 Ca/20.2 Å 2 , the crystallographic site density of the calcite (104) lattice plane]. However, the mechanistic controls governing far-from-equilibrium reactivity are not well understood. Here, in this study, we observe the interfacial incorporation of dissolved Pb 2+ during the dissolution of calcite (104) surfaces at pH ~3.7 in a flow-through reaction cell, revealing the formation of a ~1 nm thick Pb-rich calcite layer with a total Pb coverage of ~1.4 ML. These observations of the sorbed Pb distribution used resonant anomalous X-ray reflectivity, X-ray fluorescence, and nanoinfrared atomic force microscopy. We propose that this altered surface layer represents a novel sorption mode that is stabilized by conditions of sustained disequilibrium. This behavior may significantly impact the transport of dissolved metals during disequilibrium processes occurring in acid mine drainage and subsurface CO 2 injection and, if appropriately accounted for, could improve the predictive capability of geochemical reactive-transport models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

E min : A First-Principles Thermochemical Descriptor for Predicting Molecular Synthesizability

Predicting the synthesizability of a new molecule remains an unsolved challenge that chemists have long tackled with heuristic approaches. Here, in this study, we report a new method for predicting synthesizability using a simple yet accurate thermochemical descriptor. We introduce E min , the energy difference between a molecule and its lowest energy constitutional isomer, as a synthesizability predictor that is accurate, physically meaningful, and first-principles based. We apply E min to 134,000 molecules in the QM9 data set and find that E min is accurate when used alone and reduces incorrect predictions of "synthesizable" by up to 52% when used to augment commonly used prediction methods. Our work illustrates how first-principles thermochemistry and heuristic approximations for molecular stability are complementary, opening a new direction for synthesizability prediction methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Understanding Gas Solubility of Pure Component and Binary Mixtures within Multivalent Ionic Liquids from Molecular Simulations

Understanding the molecular-level solubility of CO 2 and its mixtures is essential to the progress of gas treating technologies. Herein, we use grand canonical Monte Carlo simulations to study the single component gas absorption of SO 2 , N 2 , CH 4 , and H 2 , and binary mixtures of CO 2 /SO 2 , CO 2 /N 2 , CO 2 /CH 4 , and CO 2 /H 2 of varying mole fractions within multivalent ionic liquids (ILs). Our results highlight the importance of the free volume effect and the anion effect when interpreting the absorption behavior of these mixtures, similar to the behavior of CO 2 found in our previous study. The deviation of the gas solubility between the pure component absorption versus the binary absorption, as well as the solubility selectivity, highlight the importance of the relative affinity of gas species within a mixture to the different anions. Further, the absorption selectivity within a specific IL system can be predicted based on the relative gas affinity to the anion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Adsorbate Partition Functions via Phase Space Integration: Quantifying the Effect of Translational Anharmonicity on Thermodynamic Properties

A new method for computing anharmonic thermophysical properties for adsorbates on metal surfaces is presented. Classical Monte Carlo phase space integration is performed to calculate the partition function for the motion of a hydrogen atom on Cu(111). Here, a minima-preserving neural network potential energy surface is used within the integration routine. Two different sampling schema for generating the training data are presented, and two different density functionals are used. The results are benchmarked against direct state counting results by using discrete variable representation. The phase space integration results are in excellent quantitative agreement with the benchmark results. Additionally, both the discrete variable representation and the phase space integration results confirm that the motion of H on Cu(111) is highly anharmonic. The results were applied to calculate the free energy of dissociative adsorption of H 2 and the resulting Langmuir isotherms at 400, 800, and 1200 K in a partial pressure range of 0–1 bar. It shows that the anharmonic effects lead to significantly higher predicted surface site fractions of hydrogen.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Solvent Isotherms and Structural Transitions in Nanoparticle Superlattice Assembly

Here, we introduce a Molecular Theory for Compressible Fluids (MOLT-CF) that enables us to compute free energies and other thermodynamic functions for nanoparticle superlattices with any solvent content, including the dry limit. Quantitative agreement is observed between MOLT-CF and united-atom molecular dynamics simulations performed to assess the reliability and precision of the theory. Among other predictions, MOLT-CF shows that the amount of solvent within the superlattice decreases approximately linearly with its vapor pressure and that in the late stages of drying, solvent-filled voids form at lattice interstitials. Applied to single-component superlattices, MOLT-CF predicts fcc-to-bcc Bain transitions for decreasing vapor pressure and for increasing ligand length, both in agreement with experimental results. We explore the stability of other single-component phases and show that the C14 Frank-Kasper phase, which has been reported in experiments, is not a global free-energy minimum. Implications for precise assembly and prediction of multicomponent nanoparticle systems are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Predictive control of selective secondary alcohol oxidation of glycerol on NiOOH

Abstract Many biomass intermediates are polyols and selectively oxidizing only a primary or secondary alcohol group is beneficial for the valorization of these intermediates. For example, production of 1,3-dihydroxyacetone, a highly valuable oxidation product of glycerol, requires selective secondary alcohol oxidation. However, selective secondary alcohol oxidation is challenging due to its steric disadvantage. This study demonstrates that NiOOH, which oxidizes alcohols via two dehydrogenation mechanisms, hydrogen atom transfer and hydride transfer, can convert glycerol to 1,3-dihydroxyacetone with high selectivity when the conditions are controlled to promote hydrogen atom transfer, favoring secondary alcohol oxidation. This rational production of 1,3-dihydroxyacetone achieved by selectively enabling one desired dehydrogenation pathway, without requiring alteration of catalyst composition, demonstrates how comprehensive mechanistic understanding can enable predictive control over selectivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Universal diamond edge Raman scale to 0.5 terapascal and implications for the metallization of hydrogen

The recent progress in generating static pressures up to terapascal values opens opportunities for studying novel materials with unusual properties, such as metallization of hydrogen and high-temperature superconductivity. However, an evaluation of pressure above ~0.3 terapascal is a challenge. We report a universal high-pressure scale up to ~0.5 terapascal, which is based on the shift of the Raman edge of stressed diamond anvils correlated with the equation of state of Au and does not require an additional pressure sensor. According to the new scale, the pressure values are substantially lower by 20% at ~0.5 terapascal compared to the extrapolation of the existing scales. We compare the available data of H 2 at the highest static pressures. We show that the onset of the proposed metallization of molecular hydrogen reported by different groups is consistent when corrected with the new scale and can be compared with various theoretical predictions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Ab initio thermodynamics reveals the nanocomposite structure of ferrihydrite

Ferrihydrite is a poorly crystalline iron oxyhydroxide nanomineral that serves a critical role as the most bioavailable form of ferric iron for living systems. However, its atomic structure and composition remain unclear due in part to ambiguities in interpretation of X-ray scattering results. Prevailing models so far have not considered the prospect that at the level of individual nanoparticles multiple X-ray indistinguishable phases could coexist. Using ab initio thermodynamics we show that ferrihydrite is likely a nanocomposite of distinct structure types whose distribution depends on particle size, temperature, and hydration. Nanoparticles of two contrasting single-phase ferrihydrite models of Michel and Manceau are here shown to be thermodynamically equivalent across a wide range of temperature and pressure conditions despite differences in their structural water content. Higher temperature and water pressure favor the formation of the former, while lower temperature and water pressure favor the latter. For aqueous suspensions at ambient conditions, their coexistence is maximal for particle sizes up to 12 nm. The predictions inform and help resolve different observations in various experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Artificial neural network prediction of self-diffusion in pure compounds over multiple phase regimes

Artificial neural networks (ANNs) were developed to accurately predict the self-diffusion constants for pure components in liquid, gas and super critical phases. The ANNs were tested on an experimental database of 6625 self-diffusion constants for 118 different chemical compounds. The presence of multiple phases results in a heavy skew in the distribution of diffusion constants and multiple approaches were used to address this challenge. First, an ANN was developed with the raw diffusion values to assess what the main drawbacks of this direct method were. The first approach for improving the predictions involved taking the log 10 of diffusion to provide a more uniform distribution and reduce the range of target output values used to develop the ANN. The second approach involved developing individual ANNs for each phase using the raw diffusion values. Results show that the log transformation leads to a model with the best self-diffusion constant predictions and an overall average absolute deviation (AAD) of 6.56%. The resultant ANN is a generalized model that can be used to predict diffusion across all three phases and over a diverse group of compounds. The importance of each input feature was ranked using a feature addition method revealing that the density of the compound has the largest impact on the ANN prediction of self-diffusion constants in pure compounds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗