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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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Impact of inland boundary conditions on seawater intrusion modeling in stratified coastal aquifers under sea-level rise
This study systematically examines the impact of inland boundary conditions on seawater intrusion modeling in general stratified coastal aquifers under sea-level rise (SLR). We derived analytical solutions for seawater wedge toe positions in stratified aquifers with general head boundary (GHB) conditions and compiled solutions for constant head boundary (CHB), constant flux boundary (CFB), and GHB conditions in both homogeneous and stratified aquifers. Additionally, we introduced the concept of equivalent boundary conditions and developed equations to ensure consistent steady-state toe positions across different boundary types. Unlike previous studies focusing on specific layering configurations, we conducted a comprehensive sensitivity analysis of seawater intrusion in general stratified aquifers using transmissivity centroid elevation (TCE). Our results show that SLR generally exacerbates seawater intrusion, with unconfined aquifers exhibiting higher sensitivity across all boundary conditions. Among boundary types, CHB conditions were the most sensitive to SLR, CFB the least, and GHB showed an intermediate response depending on its distance from the model boundary. Furthermore, seawater intrusion increases with the TCE of the stratified aquifer under SLR, suggesting that high-permeability or preferential flow layers near the surface amplify the impact of SLR. These findings emphasize the importance of selecting appropriate boundary conditions when evaluating SLR-driven seawater intrusion in stratified coastal aquifers.
BIPSPI+: Mining Type-Specific Datasets of Protein Complexes to Improve Protein Binding Site Prediction
Computational approaches for predicting protein-protein interfaces are extremely useful for understanding and modelling the quaternary structure of protein assemblies. In particular, partner-specific binding site prediction methods allow delineating the specific residues that compose the interface of protein complexes. In recent years, new machine learning and other algorithmic approaches have been proposed to solve this problem. However, little effort has been made in finding better training datasets to improve the performance of these methods. With the aim of vindicating the importance of the training set compilation procedure, in this work we present BIPSPI+, a new version of our original server trained on carefully curated datasets that outperforms our original predictor. We show how prediction performance can be improved by selecting specific datasets that better describe particular types of protein interactions and interfaces (e.g. homo/hetero). In addition, our upgraded web server offers a new set of functionalities such as the sequence-structure prediction mode, hetero- or homo-complex specialization and the guided docking tool that allows to compute 3D quaternary structure poses using the predicted interfaces. BIPSPI+ is freely available at https://bipspi.cnb.csic.es.
An overview of the first principles studies of doped RE-TM5 systems for the development of hard magnetic properties
In this study, we compiled all the first principles calculations performed on RE-TM 5 (RE: rare earth, TM: transition metal) system to address the following question: Has everything been tried to improve the hard magnetic properties of this special intermetallic compound, and are there any venues that are worth pursuing? As it is the case with the first principles studies in any field, they are driven mainly by experimental work: (i) to validate their results, and (ii) to extend our understanding of the underlying physical phenomena so that the theory in hand can be used as a predictive tool to shed light on certain what-if scenarios. Our analysis indicates that three major compounds are investigated more than others: (1) YCo 5 , because it can potentially be an intermediate-performance hard magnet, and the presence of yttrium with no localized 4f electrons simplifies calculations significantly, (2) SmCo 5 , because it has the largest magnetic anisotropy energy among all RE hard magnets as well as very impressive high temperature performance, (3) CeCo 5 , because Ce is the most abundant rare earth element with a curious 4f electron behavior that gives rise to pronounced deviations in its structural and magnetic properties across the lanthanides series. This is followed by a brief analysis of several ab initio approaches that were developed to treat these rather complicated systems both at 0 K and at finite temperatures. Towards the end, we elucidate the role of exchange-correlation approximations such as local density approximations (LDA) and generalized gradient approximation (GGA) formulation in determining the MAE and M s by analyzing their corresponding density of states (DOS), and providing our results on a rather overlooked hard-magnetic material: LaCo 5 .
A snapshot of high-entropy alloy processing techniques and their effects on resulting mechanical properties
High-entropy alloys (HEAs) exhibit exceptional strength, corrosion resistance, and thermal stability, making them promising candidates for nuclear, aerospace, and other extreme applications. While most prior work has focused on compositional design, manufacturing techniques themselves can alter microstructure and mechanical properties as dramatically as alloy chemistry. This review compiles and compares the effects of processing routes—including arc melting, induction melting, mechanical alloying with spark plasma sintering, and additive manufacturing—on the structure and properties of HEAs. Quantitative comparisons highlight, for example, that SPS-processed alloys can achieve ∼20–45 % higher yield and tensile strength than arc-melted counterparts, while Bridgman solidification produces nearly single-crystal structures with elongation to failure exceeding 80 %. Additive manufacturing routes such as selective laser melting offer fine microstructures but also introduce anisotropy and porosity, leading to yield strengths spanning 100–600 MPa for the same composition. By synthesizing such results, this review provides actionable insight into how processing routes interact with HEA core effects (high entropy, lattice distortion, sluggish diffusion, and cocktail effect) to determine performance, thereby offering a practical guide for optimizing manufacturing strategies.
Predicting zeolites’ stability during the corrosion of nuclear waste immobilization glasses: Comparison with glass corrosion experiments
During the long-term corrosion of nuclear waste glasses under nuclear waste disposal conditions, the precipitation of zeolitic phases has been linked to a delayed acceleration in glass corrosion (known as “Stage III”). Hence, predicting the thermodynamic propensity for zeolites to form upon the dissolution of nuclear waste glasses is key to ensure their long-term performance. Here, we compile a unified, internally-consistent thermodynamic database “clay20” to estimate the stability of clay and feldspar phases relevant to nuclear waste immobilization glasses, including beidellite(Mg, Ca, Na, K), kaolinite, montmorillonite(Mg, Ca, Na, K), nontronite(Mg, Ca, Na, K), saponite(Ca, Na, K), and albite. Based on this, we report a geochemical modeling method allowing us to predict the stability of secondary phases (including zeolites, calcium–silicate–hydrate gels, and clays) upon the dissolution of nuclear waste immobilization glasses. We show that this approach offers a realistic description of the stability of the secondary phases forming during the dissolution of two archetypical model nuclear glasses (namely, the International Simple Glass, ISG, and WVUTh-203) under conditions relevant to nuclear waste disposal (T = 90°C, p = 1 bar) as a function of pH. We find that the formation of silica and clay secondary phases is thermodynamically favored at low pH (pH < 10), whereas, in contrast, zeolite (analcime) and calcium–silicate–hydrate phases are favored at high pH (pH > 10.5). This suggests that thermodynamics (i.e., not solely kinetics) plays a key role in determining the range of solution pH wherein stage III corrosion may occur, i.e., when zeolite formation is favored.
Kinetics and transport of hydrogen in graphite at high temperature and the effects of oxidation, irradiation and isotopics
The kinetics of uptake and desorption impact the performance of graphite as a vector for tritium in high-temperature fission reactors and in the blanket of fusion reactors. Graphite components in these reactors are exposed to temperatures > 500 °C and H 2 partial pressures of few Pa and desorption temperatures are limited to < 1600 °C; limited data is available at these conditions. Here we review the mechanisms for uptake in, transport and desorption of hydrogen from graphite at high temperature, compiling data on uptake rates, diffusion coefficients and activation energies and providing a discussion of the impact of irradiation, pre-oxidation and isotope. At FHR conditions, trapping impacts uptake rates, leading to a reduction in apparent diffusivity by 35 to 80% compared to higher partial-pressure uptake. Timelines for desorption are not clearly defined; extrapolating from available data, at 1150 °C desorbing 80% of tritium uptaken at FHR conditions may take from 100 to 10,000 h.
Uranium carbide properties for advanced fuel modeling – A review
Uranium carbides are receiving renewed interest as a preferred nuclear fuel composition for advanced reactors due to their numerous favorable properties. Like many other refractory and transition metal carbides these compounds exist in both hypo- and hyper-stoichiometric compositions which results in significant variations in physical, thermal, and mechanical properties. This manuscript surveys both historic and recent literature to compile important properties data mainly as a function of temperature and carbon content to support fuel performance modeling. Expressions and fits for such properties are also suggested when allowed by complete data sets. Finally, the manuscript also attempts to highlight gaps and discrepancies in the reported data to assist the nuclear fuels community identify key areas that may require further attention in terms of future research and development.
Deep learning of experimental electrochemistry for battery cathodes across diverse compositions
Artificial intelligence (AI) has emerged as a tool for discovering and optimizing novel battery materials. However, the adoption of AI in battery cathode representation and discovery is still limited due to the complexity of optimizing multiple performance properties and the scarcity of high-fidelity data. Here, we present a machine learning model (DRXNet) for battery informatics and demonstrate the application in the discovery and optimization of disordered rocksalt (DRX) cathode materials. We have compiled the electrochemistry data of DRX cathodes over the past 5 years, resulting in a dataset of more than 19,000 discharge voltage profiles on diverse chemistries spanning 14 different metal species. Learning from this extensive dataset, our DRXNet model can capture critical features in the cycling curves of DRX cathodes under various conditions. Our approach offers a data-driven solution to facilitate the rapid identification of novel cathode materials, accelerating the development of next-generation batteries for carbon neutralization.
OpenACC acceleration for the P N – P N - 2 algorithm in Nek5000
Due to its high performance and throughput capabilities, GPU-accelerated computing is becoming a popular technology in scientific computing, in particular using programming models such as CUDA and OpenACC. The main advantage with OpenACC is that it enables to simply port codes in their ‘‘original’’ form to GPU systems through compiler directives, thus allowing an incremental approach. An OpenACC implementation is applied to the CFD code Nek5000 for simulation of incompressible flows, based on the spectral-element method. The work follows up previous implementations and focuses now on the P N - P N-2 method for the spatial discretization of the Navier–Stokes equations. Performance results of the ported code show a speed-up of up to 3.1 on multi-GPU for a polynomial order N > 11.
Rovibronic molecular line list for the $N_2(C^3Π_u–B^3Π_g)$ second positive system
Here, a line list for the N second positive system, $B^3Π_g—C^3Π_u$, has been compiled using the PGOPHER spectral simulation software. The line list extends the number of vibrational states of the $B^3Π_g$ up to v=29 and a maximum rotational state of J=150 for simulation temperatures up to 7000 K. New electronic–vibrational transition moments were calculated using refined potential energy curves and a transition dipole moment with the DUO software. Comparisons to experimental data and the SPECAIR software have been used to validate the new line list. The results are available in ASCII ExoMol .state and .trans files and as a PGOPHER input file for use in spectral analysis.
Hydrogen bond network and bond valence analysis on uranyl sulfate compounds with organic-based interstitial cations
Seven new uranyl sulfate compounds with organic charge-balancing cations have been synthesized and structurally characterized. The structural unit topologies of the two chains and five sheets have been previously reported in uranyl sulfate crystal chemistry, although they were synthesized using different organic molecules. With the inclusion of six of these structures to the 48 previously published uranyl sulfate compounds, a total of 54 known uranyl sulfate compounds with organic charge-balancing cations were compiled and analyzed. A graphical approach was used to compare the structural unit topologies, and a bond valence approach was used to quantify the hydrogen bond networks that exist between the interstitial cationic and solvent species to the uranyl sulfate anionic structural units. Finally, this analysis helped elucidate which oxygen atoms in the structural unit receive hydrogen bonds and how the organic cations stabilize the overall crystal structures in this subclass of U(VI) materials.
Structural conserved moiety splitting of a stoichiometric matrix
Characterising biochemical reaction network structure in mathematical terms enables the inference of functional biochemical consequences from network structure with existing mathematical techniques and spurs the development of new mathematics that exploits the peculiarities of biochemical network structure. The structure of a biochemical network may be specified by reaction stoichiometry, that is, the relative quantities of each molecule produced and consumed in each reaction of the network. A biochemical network may also be specified at a higher level of resolution in terms of the internal structure of each molecule and how molecular structures are transformed by each reaction in a network. The stoichiometry for a set of reactions can be compiled into a stoichiometric matrix N ϵ Z mxn where each row corresponds to a molecule and each column corresponds to a reaction. We demonstrate that a stoichiometric matrix may be split into the sum of m - rank(N) moiety transition matrices, each of which corresponds to a subnetwork accessible to a structurally identifiable conserved moiety. The existence of this moiety matrix splitting is a property that distinguishes a stoichiometric matrix from an arbitrary rectangular matrix.
Revisiting group contribution theory for estimating fractional free volume of microporous polymer membranes
Fractional free volume (FFV) is a commonly used metric for the development of structure–property relationships for polymer membranes. The most common method to calculate FFV uses Bondi's group contribution method, first introduced in 1964. While updated in 1997, there has not been a significant compilation of new structural motifs since the advent of linear microporous polymers. Here, in this study, we critically examined the assumptions in Bondi's original method and provide four recommendations to streamline and improve the accuracy of calculating van der Waals volume (V W ) for any group. Using these recommendations, we created an updated list of (V W ) values for structural groups commonly present in microporous polymers. The (V W ) and FFV values were then calculated for a database of 123 microporous and high free volume polymers from the literature, showing an average 7% decrease in (V W ) and corresponding increase in FFV by a factor of 24% when compared to prior group contribution correlations in the literature. The significant apparent increase in estimated FFV provides a new perspective to understand and interpret the role of free volume on the separation performance of linear microporous polymers. Additionally, standardization of the group contribution method allows for the direct comparison of FFV values across studies.
The need for ion-exchange membranes with high charge densities
Ion-exchange membranes (IEMs) are essential for controlling ion transport in electrochemical membrane-based technologies for water purification, energy generation, and energy storage. In general, IEMs must exhibit high ionic conductivity and selectivity, both of which are significantly influenced by the charge and water content of the hydrated membrane. In this perspective, we compiled the charge and water contents of approximately 1,000 IEMs reported over the past several decades to assess their range and variability, as well as to reveal gaps and set clear targets for future membrane design. We compared the charge and water content of negatively and positively charged membranes, as well as membranes developed for desalination and energy applications. The majority of IEMs, regardless of structure or intended application, have volumetric charge densities below 3 mol/L[membrane]. This narrow range of charge densities limits the performance of IEMs and contributes to the observed tradeoff between ion throughput and selectivity. It is critical to develop IEMs with higher charge densities to overcome this performance limitation. Further, we highlighted several design strategies that yielded IEMs with fixed charge densities higher than 3 mol/L[membrane]. These strategies provide valuable insights and can guide the design of next-generation IEMs with high charge densities.
Strategies for Post-Synthetic Functionalization of Mesoporous Carbon Nanomaterial Surfaces
Most widely used carbon-based materials feature a bulk framework tolerant of extreme pH and temperature conditions while maintaining physical robustness, electrical conductivity, and biological relevance due to its inherent nontoxicity. At the nanoscale, the study of porous carbons has been of interest because of the enhanced accessible surface area relative to nonporous analogues. The evolution of synthetic techniques has developed structural allotropes with tunable internal pore diameter averages spanning from sub-nanometer to micron-plus sizes. Within the mesopore range, surface chemical phenomena abide by a kinetic-limited ruleset (ignoring the effects of bulk diffusion, as they do not pertain to this size regime). Further, mesopores provide sufficient volume and surface area for hosting guest species, including metal nanoparticles (MNP), polymers, small organics, and enzymes. These two unique features of mesoporous carbon (MC) drive interest in surface modifications to create new physicochemical functionality to these systems and their hosted species. As a result, the evolution of surface modification techniques has been scattered to disparate niches across the literature. This review compiles the array of elegant methods by which these carbon systems are topically engineered.
Optical spectroscopy of molten fluorides: Methods, electronic and vibrational data, structural interpretation, and relevance to radiative heat transfer
In this study, to help address the need for predicting radiative heat transfer (RHT) behavior of molten salts, we conducted a comprehensive review of methods and data from optical spectroscopic measurements on molten fluoride salts. Transmittance, reflectance, and trans-reflectance experimental methods are discussed, along with the corresponding data reduction methodology and the limitations of each technique. Optical spectroscopy is a convenient indirect probe for changes in structural parameters with temperature and composition. Electronic and vibrational absorption data for transition-metal, lanthanide, and actinide solutes and vibrational absorption data for alkali and alkaline earth fluoride solvents are compiled, and the corresponding structural interpretation is discussed and compared with other experimental and theoretical work. We find that solvent and solute vibrational absorption can be significant in the mid-infrared, resulting in near-infrared edges of significance to RHT. Extrapolation and averaging of existing edge data leads to estimated gray absorption coefficient values at 700 °C of 546 m —1 for FLiBe and 276 m —1 for FLiNaK, both within the range of 1 – 6000 m —1 identified to be of engineering relevance for radiative heat transfer analysis.