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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

An Overview of the Materials Science Research at the Marshall Space Flight Center Electrostatic Levitator Facility and Recent CDDF Efforts

Containerless processing is an important tool for materials research. The freedom from a crucible allows processing of liquid materials in a metastable undercooled state, as well as allowing processing of high temperature and highly reactive melts. Electrostatic levitation (ESL) is a containerless method which provides a number of unique advantages, including the ability to process non-conducting materials, the ability to operate in ultra-high vacuum or at moderate gas pressure (approx. = 5 atm), and the decoupling of positioning force from sample heating. ESL also has the potential to reduce internal flow velocities below those possible with electromagnetic, acoustic, or aero-acoustic techniques. In electrostatic levitation, the acceleration of gravity (or residual acceleration in reduced gravity) is opposed by the action of an applied electric field on a charged sample. Microgravity allows electrostatic levitation to work even more effectively. The ESL facility at NASA s Marshall Space Flight Center is in use for materials research and thermophysical property measurement by a number of different internal and external investigators. Results from the recent CDDF studies on the high energy X-ray beamline at the Advanced Photon Source of Argonne National Laboratory will be presented. The Microgravity Research Program supports the facility.

Source record↗
DOE OSTI2026

From bulk to surface: Structure and dynamics of amorphous alumina from deep potential molecular dynamics

Understanding the atomic-scale structure and dynamics of amorphous oxide surfaces is essential for interpreting their chemical reactivity, mechanical stability, and interfacial behavior, yet direct experimental characterization remains challenging. We employ Deep Potential (DP) molecular dynamics to generate large-scale, ab initio -quality models of amorphous Al 2 O 3 bulk glasses and melt-quenched free surfaces, enabling a quantitative analysis of both structure and relaxation dynamics with statistical confidence inaccessible to direct ab initio simulation. The trained DP model reproduces experimental liquid and glass structure, captures the cooling-rate dependence of the bulk glass transition, and corrects systematic biases in the polyhedral populations predicted by widely used classical force fields. At the free surface, mass density recovers to bulk values over ~10 Å, while local coordination requires a slightly wider subsurface region to fully converge. The outermost layer is oxygen-enriched, exhibits altered polyhedral connectivity with contracted Al–O bonds, and hosts a broad population of under-coordinated motifs (notably AlO 3 and OAl 2 ) whose abundances are governed by glass stability. These under-coordinated surface motifs exhibit distinct vibrational signatures and occur as locally paired Lewis acid and Brønsted base sites consistent with bond-valence compensation, yet remain spatially dispersed rather than aggregating into extended clusters. Despite this pronounced structural heterogeneity, surface relaxation and the glass-transition temperature remain comparable to their bulk counterparts, suggesting that the disordered surface is kinetically stable once formed. Together, these results establish a molecular-level picture of amorphous alumina surfaces and demonstrate the capability of machine-learned potentials to resolve structure–property relationships in disordered oxide interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

ReaxFF molecular dynamics simulations on the structure and dynamics of electrolyte water systems at ambient temperature

Here, ReaxFF molecular dynamics simulations have been performed to study the effect of cations Li + , Na+ and K + and anion Cl - on the structural and dynamical properties of water, using the force field recently developed by Fedkin and co-workers. The structural relationship of ion and water has been analyzed from the radial distribution function and angular distribution. Comparisons of ReaxFF angle variation of ions and water within the first solvation shell were made and found to be in good agreement with literature. The disruption of hydrogen bond network of water by ions is elucidated by ion-water residence times, water-water hydrogen bond dynamics and reorientational dynamics. ReaxFF diffusion coefficient and residence times of electrolyte water system were compared with ab initio and non-reactive potentials to analyze the difference in dynamics. We gained insight into the ion interaction with water and how it can accelerate or decelerate water dynamics. ReaxFF outlines the formation and dissolution of metal hydroxides and metal chlorides over the course of simulation to explain the diffusion dynamics of water in salt solutions, allowing us to elucidate the impact of concentration on the self-diffusivity of water and ions in solutions, and to reveal that this effect always decreases the mobility and is not at all ion-specific. The obtained findings have opened new opportunities to extend the ReaxFF methodology towards systems involving electrolytes.

42 ENGINEERING↗
DOE OSTI2022

Removable, Sequestration Coatings for Mitigating Hazardous Contaminants Related to Deactivation and Decommissioning Activities

This project is a collaborative effort between InnoSense LLC (ISL) and Oak Ridge National Laboratory (ORNL) aimed at mitigating the mercury (Hg) contamination problem at the Y-12 National Security Complex (NSC). The report summarizes the research and technology development work of the Phase IIB Project, led by Dr. Uma Sampathkumaran at ISL for the period of July 31, 2017–October 31, 2021. The Y-12 site cleanup includes technologies for safe and cost-effective facility demolition, soil remediation, and on-site treatment and disposal of mercury bearing wastes. One of the technology demonstration goals was a reactive strippable coating for targeted pre-demolition and de-contamination to limit Hg mobilization and the volume of debris requiring treatment for disposal. Toward this, ISL has developed a water-based reactive strippable coating (Trap & See-Hg™) to sequester elemental Hg(0) and mercuric Hg(II) species in the coating. The coating provides multiple benefits including (1) Hg vapor suppression, (2) sealing in the hazardous contaminants, (3) visually locating the contaminant through color changes, and (4) remediating the contaminated surfaces upon coating removal. Through collaboration between ORNL and ISL in Phase II work, the team successfully demonstrated the Trap & See-Hg technology to (1) visually locate the presence of Hg on concrete, soil and drywall surfaces, (2) effectively sequester all mercury species (elemental, soluble and insoluble Hg) from lab-generated and ex-situ soil and brick/rubble samples collected from the Y 12 site with 80 to 95% efficiency to capture/reduce Hg vapor concentration, (3) be applied by manual and robotic spray applicators and cure at room ambient, (4) remain a cohesive and peelable coating upon drying, and (5) sequester Hg0 from walls in the alpha-2 building basement at Y-12 during a small scale in-situ field trial. In Phase IIB, ISL’s effort was focused on refining the coating formulations with additives containing passive and reactive sorbents, colorimetric indicator, and thixotropic agents to achieve the desired performance. The paints were then evaluated at ORNL for applicability to metal and concrete surfaces of different sizes and shapes, and soil rubble, Hg-sorption capacity and achieving sag-free coating on surfaces when applied by a manual spray applicator. Ambient cure of the coating resulted in a dry thickness of 16–20 mil. The coatings were removed from smooth or rough surfaces with low to moderate force. Both lab-generated Hg-contaminated samples and soil and brick/rubble samples containing a range of Hg concentrations (collected from the Y-12 site by UCOR) were used in this project. Optimized formulations were applied to these samples and evaluated for ability to suppress Hg vapors, sequester Hg 0 and Hg(II) species and color mapping of mercury species on the test surface. The ORNL team initially identified three to four potential sites at Y-12 and ORNL for potential demonstration. However, the pandemic closed any possible avenues for on-site demonstration of the robotic spray applicator. The metal and concrete samples with low to high Hg content provided by UCOR from an ongoing demolition were subsequently used for ex-situ sample characterization and analysis at ORNL over a period of 25 days. The coatings suppressed Hg vapors with an efficiency of 95–99% from heavily contaminated metal and 60% from concrete substrate. Analysis of total Hg in the peeled paints indicates sorption capacities ranging from 12 µg Hg/g of paint from concrete to 1.2 mg Hg/g of paint from the metal substrates while peeled paints from soil samples could capture a total Hg from 2.3 mg Hg/g to 66 mg/g paint. Toxicity characteristic leaching procedure (TCLP) tests recovered total mercury leached at 0.15±0.0008 µg/L for concrete to 126.81±0.67 µg/L and 377.25±5.67 µg/L for the two metal substrates, to allow for informed decisions on downstream disposal considerations. Together, this Phase IIB demonstrated the potential value of the Trap & See-Hg for Hg uptake, vapor suppression, and color mapping, and may thus be used to enhance worker safety during site cleanup, facility demolition, and downstream waste disposal at Y-12 NSC.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Navigating Transition-Metal Chemical Space: Artificial Intelligence for First-Principles Design

Conspectus The variability of chemical bonding in open-shell transition-metal complexes not only motivates their study as functional materials and catalysts but also challenges conventional computational modeling tools. Here, tailoring ligand chemistry can alter preferred spin or oxidation states as well as electronic structure properties and reactivity, creating vast regions of chemical space to explore when designing new materials atom by atom. Although first-principles density functional theory (DFT) remains the workhorse of computational chemistry in mechanism deduction and property prediction, it is of limited use here. DFT is both far too computationally costly for widespread exploration of transition-metal chemical space and also prone to inaccuracies that limit its predictive performance for localized d electrons in transition-metal complexes. These challenges starkly contrast with the well-trodden regions of small-organic-molecule chemical space, where the analytical forms of molecular mechanics force fields and semiempirical theories have for decades accelerated the discovery of new molecules, accurate DFT functional performance has been demonstrated, and gold-standard methods from correlated wavefunction theory can predict experimental results to chemical accuracy. The combined promise of transition-metal chemical space exploration and lack of established tools has mandated a distinct approach. In this Account, we outline the path we charted in exploration of transition-metal chemical space starting from the first machine learning (ML) models (i.e., artificial neural network and kernel ridge regression) and representations for the prediction of open-shell transition-metal complex properties. The distinct importance of the immediate coordination environment of the metal center as well as the lack of low-level methods to accurately predict structural properties in this coordination environment first motivated and then benefited from these ML models and representations. Once developed, the recipe for prediction of geometric, spin state, and redox potential properties was straightforwardly extended to a diverse range of other properties, including in catalysis, computational “feasibility”, and the gas separation properties of periodic metal–organic frameworks. Interpretation of selected features most important for model prediction revealed new ways to encapsulate design rules and confirmed that models were robustly mapping essential structure–property relationships. Encountering the special challenge of ensuring that good model performance could generalize to new discovery targets motivated investigation of how to best carry out model uncertainty quantification. Distance-based approaches, whether in model latent space or in carefully engineered feature space, provided intuitive measures of the domain of applicability. With all of these pieces together, ML can be harnessed as an engine to tackle the large-scale exploration of transition-metal chemical space needed to satisfy multiple objectives using efficient global optimization methods. In practical terms, bringing these artificial intelligence tools to bear on the problems of transition-metal chemical space exploration has resulted in ML-model assessments of large, multimillion compound spaces in minutes and validated new design leads in weeks instead of decades.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Mineral solubility and free energy controls on microbial reaction kinetics: Application to contaminant transport in the subsurface

Recent developments in the theoretical treatment of geomicrobial reaction processes have resulted in the formulation of kinetic models that directly link the rates of microbial respiration and growth to the corresponding thermodynamic driving forces. The overall objective of this project was to verify and calibrate these kinetic models for the microbial reduction of uranium(VI) in geochemical conditions that mimic as much as possible field conditions. The approach combined modeling of bacterial processes using new bioenergetic rate laws, laboratory experiments to determine the bioavailability of uranium during uranium bioreduction, evaluation of microbial growth yield under energy-limited conditions using bioreactor experiments, competition experiments between metabolic processes in environmentally relevant conditions, and model applications at the field scale. The new kinetic descriptions of microbial U(VI) and Fe(III) reduction should replace those currently used in reactive transport models that couple catabolic energy generation and growth of microbial populations to the rates of biogeochemical redox processes. The above work was carried out in collaboration between the groups of Taillefert (batch reactor experiments and reaction modeling) at Georgia Tech and Van Cappellen (retentostat experiments and reactive transport modeling) at University of Waterloo (Canada).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Designing Physicochemically‐Ordered Interphases for High‐Performance Composites

To enhance the mechanical properties of carbon fiber‐reinforced polymer composites, a physicochemical scaffold is designed incorporating microscopically architected chemically reactive nanofibers that act as a multiscale bridge between the carbon fibers and the matrix. Thermally activated nanofibers leverage their morphologically driven mechanochemical properties to form covalent bonds with adjacent polymer molecules, creating a co‐continuous network that dramatically enhances fiber‐matrix load transfer. By meticulously controlling the nanofiber architecture through variable surface area, functional group availability, and polymer chain alignment effects, the extent of covalent bonding between nanofibers and the matrix is manipulated ultimately resulting in improved carbon fiber‐matrix adhesion. Further, the concept was validated using polyacrylonitrile nanofibers within an acrylonitrile butadiene styrene matrix in a discontinuous carbon fiber‐reinforced composite system. Nanomechanical studies using atomic force microscopy and low‐field nuclear magnetic resonance spectroscopy confirmed immobilized, chemically transferred, and ordered nanostructures at the interphase. The resulting composites demonstrated ≈56% and ≈175% improvements in tensile strength and toughness, respectively, compared to composites without nanofiber. Comprehensive thermal, rheological, and X‐ray scattering analyses, along side all‐atomic molecular dynamics simulations, revealed the fundamental mechanisms behind these improvements in mechanical behavior. The versatility and efficacy of the approach have the potential to address longstanding interphase challenges in the composite industry.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Fluoride-Cooled High-Temperature Pebble-Bed Reactor Reference Plant Model Updates

This work presents the latest improvements to, and investigations performed with, the Fluoride-Cooled High-Temperature Pebble-Bed Reactor reference plant models for the United States Nuclear Regulatory Commission. These models, developed with the Comprehensive Reactor Analysis Bundle, or BlueCRAB, serve as the foundation for the future development of detailed design evaluation models based on license applications. BlueCRAB is the code suite proposed for non-light-water reactor systems safety analyses, and it incorporates various simulation tools developed by the Nuclear Energy Advance Modeling and Simulation program, including the Griffin code for reactor physics, the Pronghorn and SAM codes for core thermal fluids, the BISON code for solid conduction and fuel performance, and the SAM code for system analysis. The primary objective of this work is to assess the level of readiness of BlueCRAB for modeling fluoride-cooled high-temperature pebble-bed reactors. We first developed numerical models in BlueCRAB that include the key physics for this technology, ensuring an adequate level of fidelity for modeling the core performance during accident scenarios. This was followed by simulation of transient scenarios, two loss-of-forced-cooling events (one protected and one unprotected), and two control rod withdrawal events (one delayed and one prompt supercritical reactivity insertion). The analysis includes comparisons between the 2-D thermal fluid porous media models in Pronghorn and SAM, comparisons between coupled Pronghorn-Griffin and coupled SAM-Griffin models for two loss-of-forced cooling events and one control rod withdrawal event, and comparisons between SAM single-solve and domain-overlapping approaches for multi-scale thermal fluid coupling. In addition, we performed comparisons between 3-D, 2-D, and 0-D neutronic models for the two control rod withdrawal scenarios with Pronghorn-Griffin. The results show that the BlueCRAB models led to physically intuitive solutions for the scenarios examined. The changes in the various scalar and vector fields such as the neutron flux, power, temperatures, densities, pressures, and velocities are all within the expected ranges, and their distributions can be explained from the system response of the transients and the geometric and material variations. Several comparisons suggest that the porous media models in Pronghorn and SAM can lead to similar solutions, even though they are based on different methodologies. The simulations demonstrate that there are differences between the various levels of fidelity, and it is advisable to have flexible tools that can cover the breadth and depth of needs that may arise in future technical evaluations. We believe that BlueCRAB’s capabilities represent a significant asset for confirmatory analyses aimed at resolving important safety questions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Reliable computational design of biological-inorganic materials to the large nanometer scale using Interface-FF

The function of nanomaterials and biomaterials greatly depends on understanding nanoscale recognition mechanisms, crystal growth and surface reactions. The Interface Force Field (IFF) and surface model database are the first collection of transferable parameters for inorganic and organic compounds that can be universally applied to all materials. IFF uses common energy expressions and achieves best accuracy among classical force fields due to rigorous validation of structural and energetic properties of all compounds in comparison to perpetually valid experimental data. This paper summarises key aspects of parameterisation, including atomic charges and transferability of parameters and current coverage. Examples of biomolecular recognition at metal and mineral interfaces, surface reactions of alloys, as well as new models for graphitic materials and pi-conjugated molecules are described. For several metal–organic interfaces, a match in accuracy of computed binding energies between of IFF and DFT results is demonstrated at ten million times lower computational cost. Predictive simulations of biomolecular recognition of peptides on phosphate and silicate surfaces are described as a function of pH. The use of IFF for reactive molecular dynamics is illustrated for the oxidation of Mo3Si alloys at high temperature, showing the development of specific porous silica protective layers. The introduction of virtual pi electrons in graphite and pi-conjugated molecules enables improvements in property predictions by orders of magnitude. The inclusion of such molecule-internal polarity in IFF can reproduce cation–pi interactions, pi-stacking in graphite, DNA bases, organic semiconductors and the dynamics of aqueous and biological interfaces for the first time.

Chemistry↗
DOE OSTI2020

Vanadium oxide coatings to self-regulate current sharing in high-temperature superconducting cables and magnets

High-temperature superconductors such as REBa 2 Cu 3 O 7-δ (REBCO, RE = rare earth) enable high-current cables and high-field magnets. By removing the turn-to-turn insulation in a magnet application, recent experiments demonstrated that REBCO magnets can self-protect against catastrophic damage during a superconducting-to-normal transition (quench), i.e., when the stored magnetic energy rapidly converts to heat. The current can bypass the hot spot during a quench, thereby reducing the localized heat dissipation. The removal of the insulation between turns, however, leads to excessive eddy currents during current ramping, thereby forcing a much-prolonged magnet charging time. To address this issue, we investigate vanadium oxide (VO x ) coatings as a temperature-dependent self-switching medium that automatically manages current sharing. VO x coatings (with 1.70 ≤ × ≤ to 2.07) were deposited by reactive cathodic arc deposition, initially on insulating glass to determine the electrical properties, and later on commercial REBCO tapes. The coatings are x-ray amorphous but with a short-range crystalline ordering according to Raman spectrometry. The resistivity of VO x decreased by at least three orders of magnitude when the temperature increased from 80 to 300 K. The coating process is compatible with commercial REBCO tapes as evidenced by the negligible change in the critical current caused by the coating process. Here, the results from current sharing experiments and circuit analysis suggest that the VO x coating can effectively self-regulate current sharing in REBCO magnets, suppress excessive eddy currents, and enable self-protection during quenches.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Substituent Effects in Mechanochemical Allowed and Forbidden Cyclobutene Ring-Opening Reactions

Woodward and Hoffman once jested that a very powerful Maxwell demon could seize a molecule of cyclobutene at its methylene groups and tear it open in a disrotatory fashion to obtain butadiene (Woodward, R. B.; Hoffmann, R. The Conservation of Orbital Symmetry. Angew. Chem., Int. Ed. 1969, 8, 781–853). Nearly 40 years later, that demon was discovered, and the field of covalent polymer mechanochemistry was born. In the decade since our demon was befriended, many fundamental investigations have been undertaken to build up our understanding of force-modified pathways for electrocyclic ring-opening reactions. In this work, we seek to extend that fundamental understanding by exploring substituent effects in allowed and forbidden ring-opening reactions of cyclobutene (CBE) and benzocyclobutene (BCB) using a combination of single-molecule force spectroscopy (SMFS) and computation. We show that, while the forbidden ring-opening of cis-BCB occurs at a lower force than the allowed ring-opening of trans-BCB on the time scale of the SMFS experiment, the opposite is true for cis- and trans-CBE. Such a reactivity flip is explained through computational analysis and discussion of the so-called allowed/forbidden gap.

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

Model simulations of Plum Island Ecosystems LTER low marsh site using ELM-PFLOTRAN

Model simulations using the E3SM Land Model (ELM) coupled to the PFLOTRAN reactive transport model via the Alquimia interface. The simulations were conducted for a tidal salt marsh at the Plum Island Ecosystems LTER near Rowley, Massachusetts, USA. Model simulations were forced using site-specific tidal cycles and salinity, and the simulations used a biogeochemical reaction network including aerobic decomposition, sulfate reduction, iron reduction, and methanogenesis. Model outputs include simulated carbon stocks, carbon dioxide and methane fluxes, and porewater concentrations of key solutes related to sulfur, iron, and carbon cycling. The model simulations included a saline simulation (with tidal sulfate inputs), a fresh simulation (with low salinity and low sulfate inputs), and a saline simulation with lower vegetation productivity to represent the effect of salinity on vegetation. These simulations were conducted to demonstrate that a new model framework incorporating subsurface redox and biogeochemical interactions into a land surface model could reproduce measured surface greenhouse gas fluxes and biogeochemical dynamics in tidal marsh ecosystems, and to test whether including redox interactions in a land surface model would allow the model to resolve contrasts in biogeochemical cycling and greenhouse gas production between saline and freshwater wetlands.The data package includes gzipped tar archives (which can be expanded using standard tar and gzip utilities) of model outputs from three model configurations: saline subsurface and reduced vegetation productivity related to salinity; saline subsurface with vegetation productivity not reduced; and freshwater. Also included are code for the modified E3SM model, Alquimia interface, and PFLOTRAN reactive transport simulator in gzipped tar format; plain text parameter and configuration files; python code files for visualizing model output and defining model configurations; and model output, tide and salinity forcing, and configuration files in netCDF format. See the README.md file in the data package for a detailed description of all files contained in the package. All files are in netCDF (.nc), gzipped tar archive (.tar.gz or .tgz), or text (all other files).Updated: May 13, 2024. Model output, E3SM code, PFLOTRAN input files, and python codes for visualizing results were updated to reflect changes made for the manuscript revision. The updated archive reflects the code and model output from the final accepted manuscript. Changes included updated reaction parameters reflecting improved parameterization and additional comparisons with field measurements. E3SM code changes included better support for multiple grid cells and improved flow and transport parameterization.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Influence of Surface and Bulk Water Ice on the Reactivity of a Water-forming Reaction

On the surface of icy dust grains in the dense regions of the interstellar medium, a rich chemistry can take place. Due to the low temperature, reactions that proceed via a barrier can only take place through tunneling. The reaction H+H{sub 2}O{sub 2}⟶H{sub 2}O+OH is such a case with a gas-phase barrier of ∼26.5 kJ mol{sup −1}. Still, the reaction is known to be involved in water formation on interstellar grains. Here, we investigate the influence of a water ice surface and of bulk ice on the reaction rate constant. Rate constants are calculated using instanton theory down to 74 K. The ice is taken into account via multiscale modeling, describing the reactants and the direct surrounding at the quantum mechanical level with density functional theory (DFT), while the rest of the ice is modeled on the molecular mechanical level with a force field. We find that H{sub 2}O{sub 2} binding energies cannot be captured by a single value, but rather they depend on the number of hydrogen bonds with surface molecules. In highly amorphous surroundings, the binding site can block the routes of attack and impede the reaction. Furthermore, the activation energies do not correlate with the binding energies of the same sites. The unimolecular rate constants related to the Langmuir–Hinshelwood mechanism increase as the activation energy decreases. Thus, we provide a lower limit for the rate constant and argue that rate constants can have values up to two order of magnitude larger than this limit.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Modeling prebiotic chemistries with quantum accuracy at classical costs

Molecular Dynamics (MD) simulations using classical force-fields are commonly employed in numerous scientific investigations. However, many natural processes involve bond breaking and quantum forces. This complexity is compounded by the presence of multiple competing length and timescales. For example, accurately modeling the thermodynamics and dynamics of a chemical reaction requires accounting for the concerted movements of numerous solvent molecules and ions with their own fast or slow timescales. While widely used static Density Functional Theory (DFT) calculations at 0 temperature can be beneficial for such investigations, they do not account for dynamics, and lack precision in describing the molecular environments. They particularly fail at correct, rigorous treatments of finite-temperature fluctuations, and thus generalization to experimentally relevant conditions. In PNAS Benayad et al develop a scalable, generalizable approach for designing Neural Network Potentials (NNPs) that can handle chemical reactivity in solvated systems with quantum accuracy at classical costs. Specifically, they study phosphoester bond formation and rupture, which is fundamentally relevant to the Phosphorus-Oxygen bond formation central to life, and especially for the RNA world hypothesis. The framework developed here has the potential to generalize to different chemical reactions of energy and biological relevance.

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

Liquid-to-gas transfer of sodium in a liquid cathode glow discharge

Abstract Plasma-liquid interactions have been extensively studied with a focus on the transport of reactive species from the plasma to the liquid phase and their induced liquid phase chemistry and resulting applications. While solute transfer from the liquid to the gas phase in plasmas has been widely used in analytical chemistry, the underlying processes remain relatively unexplored. We report spatially and temporally resolved absolute density measurements of sodium in a plasma with a NaCl solution cathode using two-photon absorption laser induced fluorescence (TaLIF). The observed non-linear increase in sodium density with solution conductivity is shown to correlate with droplet generation as visualized by Mie scattering. The findings are explained by droplet generation by electrospray induced by Taylor cone formation as underpinning mechanism for the introduction of sodium in the plasma. An analytical sheath model combined with a scaling law shows an increase in electric field force with solution conductivity that is consistent with the observed non-linear increase in sodium density in the plasma with solution conductivity.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Teaching a neural network to attach and detach electrons from molecules

Abstract Interatomic potentials derived with Machine Learning algorithms such as Deep-Neural Networks (DNNs), achieve the accuracy of high-fidelity quantum mechanical (QM) methods in areas traditionally dominated by empirical force fields and allow performing massive simulations. Most DNN potentials were parametrized for neutral molecules or closed-shell ions due to architectural limitations. In this work, we propose an improved machine learning framework for simulating open-shell anions and cations. We introduce the AIMNet-NSE (Neural Spin Equilibration) architecture, which can predict molecular energies for an arbitrary combination of molecular charge and spin multiplicity with errors of about 2–3 kcal/mol and spin-charges with error errors ~0.01e for small and medium-sized organic molecules, compared to the reference QM simulations. The AIMNet-NSE model allows to fully bypass QM calculations and derive the ionization potential, electron affinity, and conceptual Density Functional Theory quantities like electronegativity, hardness, and condensed Fukui functions. We show that these descriptors, along with learned atomic representations, could be used to model chemical reactivity through an example of regioselectivity in electrophilic aromatic substitution reactions.

36 MATERIALS SCIENCE↗
NASA NTRS2000

Thermophysical Property Measurement and Materials Research in the NASA/MSFC Electrostatic Levitator

Containerless processing is an important tool for thermophysical property measurements and materials research. The freedom from a crucible allows processing of liquid materials in a metastable undercooled state, as well as allowing processing of high temperature and highly reactive melts. Electrostatic levitation (ESL) is a containerless method which provides a number of unique advantages, including the decoupling of positioning force from sample heating, the ability to operate in ultra-high vacuum or at moderate gas pressure (approximately 3 atm), and the ability to process non-conducting materials. ESL also has the potential to reduce internal flow velocities below those possible with electromagnetic, acoustic, or aero-acoustic techniques. The ESL facility at NASA's Marshall Space Flight Center (MSFC) is in use for thermophysical property measurements and materials research by a number of different internal and external investigators. The methods for obtaining access to the facility, as well as a summary of current capabilities and some future directions will be discussed. In electrostatic levitation, the acceleration of gravity (or residual acceleration in reduced gravity) is opposed by the action of an applied electric field on a charged sample. This positioning method is applicable to any material which can be electrically charged, whether solid or liquid, conducting, or insulating. Because the position of the sample is unstable, a 3-dimensional active control loop rapidly adjusts the applied field to maintain levitation and minimize motion of the sample. Heating lasers melt the sample, and may be adjusted to maintain specified thermal profiles. Microgravity allows electrostatic levitation to work even more effectively. With the need to cancel less than 1 milli-g, the applied field required is reduced from approximately 10 MV/m to approximately 10 kV/m. Alternatively, a microgravity ESL can position larger samples than is possible on the ground, or it can position samples which maintain their charge poorly. Microgravity also reduces the effects of buoyant convection and sedimentation. In the MSFC ESL, many different classes of experiments and measurements have been demonstrated in collaboration with many investigators. These capabilities include heat capacity measurement, phase diagram determination, and nucleation and growth experiments including nucleation rate, TTT curves, and phase selection. We have demonstrated the capability of triggering recalescence of an undercooled liquid sample without loss of levitation. Currently under development are techniques for measuring the surface tension, viscosity, and density of levitated samples, as well as other thermophysical properties. Expanded levitation capabilities including various gas environments for sample processing, sample rotation control and management of thermal gradients are under development for the MSFC ESL. Containerless processing allows research on materials which may not be processed any other way. Electrostatic levitation extends the range of containerless processing to include many materials and classes of materials which cannot be processed by conventional electromagnetic, acoustic, or aerodynamic levitation techniques.

Rogers, Jan↗