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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Ab initio study of C + H3+ reactions

The reaction C + H3+ --> CH(+) + H2 is frequently used in models of dense interstellar cloud chemistry with the assumption that it is fast, i.e. there are no potential energy barriers inhibiting it. Ab initio molecular orbital study of the triplet CH3+ potential energy surface (triplet because the reactant carbon atom is a ground state triplet) supports this hypothesis. The reaction product is 3 pi CH+; the reaction is to exothermic even though the product is not in its electronic ground state. No path has been found on the potential energy surface for C + H3+ --> CH2(+) + H reaction.

NASA Discipline Exobiology↗
DOE OSTI2025

Site-specific surface reactivity on SnO 2 : Evaluating selective atomic layer deposition processes

Area selective atomic layer deposition (AS-ALD) is a bottom-up synthesis approach with potential for deposition with molecular level precision. Here, the site-specific hydration of metal oxide substrates, combined with surface H 2 O-selective ALD processes, provides a potentially powerful path to targeted synthesis. Density functional theory (DFT) calculations are used to predict the thermodynamics of ALD precursor reactivity and hydration for (001), (101), (110), and (100) rutile SnO 2 facets as a function of temperature. Trimethylaluminum (TMA) and dimethyl aluminum isopropoxide (DMAI) dimers are predicted to react with both dehydrated and hydrated SnO 2 (001), (101), and (110) facets at ALD-relevant temperatures, while the SnO 2 (100) facet is predicted to be uniquely unreactive with TMA and DMAI monomers as well as dehydrate near 177 °C making this facet more amenable to targeted ALD. In situ ellipsometric studies of Al 2 O 3 ALD on polycrystalline SnO 2 at 150 °C are consistent with the computational predictions of rapid and unselective nucleation, in stark contrast to inhibited and selective ALD on isostructural rutile TiO 2 .

Atomic Layer Deposition↗
NASA NTRS2005

Origin of the Eumetazoa: testing ecological predictions of molecular clocks against the Proterozoic fossil record

Molecular clocks have the potential to shed light on the timing of early metazoan divergences, but differing algorithms and calibration points yield conspicuously discordant results. We argue here that competing molecular clock hypotheses should be testable in the fossil record, on the principle that fundamentally new grades of animal organization will have ecosystem-wide impacts. Using a set of seven nuclear-encoded protein sequences, we demonstrate the paraphyly of Porifera and calculate sponge/eumetazoan and cnidarian/bilaterian divergence times by using both distance [minimum evolution (ME)] and maximum likelihood (ML) molecular clocks; ME brackets the appearance of Eumetazoa between 634 and 604 Ma, whereas ML suggests it was between 867 and 748 Ma. Significantly, the ME, but not the ML, estimate is coincident with a major regime change in the Proterozoic acritarch record, including: (i) disappearance of low-diversity, evolutionarily static, pre-Ediacaran acanthomorphs; (ii) radiation of the high-diversity, short-lived Doushantuo-Pertatataka microbiota; and (iii) an order-of-magnitude increase in evolutionary turnover rate. We interpret this turnover as a consequence of the novel ecological challenges accompanying the evolution of the eumetazoan nervous system and gut. Thus, the more readily preserved microfossil record provides positive evidence for the absence of pre-Ediacaran eumetazoans and strongly supports the veracity, and therefore more general application, of the ME molecular clock.

NASA Discipline Evolutionary Biology↗
NASA NTRSDate not supplied

Quantum Hardware-Enabled Molecular Dynamics via Transfer Learning

The ability to perform ab initio molecular dynamics simulations using potential energy surfaces provided by quantum computers would open the door to virtually exact dynamics for a variety of chemical and biochemical systems, with impacts on catalysis and biophysics. Nonetheless, performing molecular dynamics on surfaces produced by quantum hardware has been hampered by the noisy energies typically produced by quantum computers and challenges associated with computing gradients and scaling to large systems interest. A recent set of advances in machine learning, known as transfer learning, provides a new path forward for molecular dynamics simulations on quantum hardware. Transfer learning offers a workaround, where one first trains models on larger, less accurate classical datasets and then refines them on smaller, more accurate quantum datasets. We explore this approach by training machine learning models to predict a molecule's potential energy based on its geometric structure using Behler-Parrinello neural networks. When successfully trained, the model enables energy gradient predictions necessary for dynamic simulations. To reduce the quantum resources needed, the model is initially trained with data derived from classical density functional theory and subsequently refined with a smaller dataset obtained from a variational quantum eigensolver optimization of the unitary coupled cluster ansatz. We show that this approach significantly reduces the size of the needed quantum training dataset while capturing the high accuracies needed within quantum chemistry simulations. The success of this two-step training method opens more opportunities to apply machine learning models on quantum data, a significant stride towards efficient quantum-classical hybrid computational models.

quantum computing↗
NASA NTRS2012

Surface, Water, and Air Biocharacterization (SWAB) Flight Experiment

The determination of risk from infectious disease during spaceflight missions is composed of several factors including both the concentration and characteristics of the microorganisms to which the crew are exposed. Thus, having a good understanding of the microbial ecology aboard spacecraft provides the necessary information to mitigate health risks to the crew. While preventive measures are taken to minimize the presence of pathogens on spacecraft, medically significant organisms have been isolated from both the Mir and International Space Station (ISS). Historically, the method for isolation and identification of microorganisms from spacecraft environmental samples depended upon their growth on culture media. Unfortunately, only a fraction of the organisms may grow on a specific culture medium, potentially omitting those microorganisms whose nutritional and physical requirements for growth are not met. To address this bias in our understanding of the ISS environment, the Surface, Water, and Air Biocharacterization (SWAB) Flight Experiment was designed to investigate and develop monitoring technology to provide better microbial characterization. For the SWAB flight experiment, we hypothesized that environmental analysis using non-culture-based technologies would reveal microorganisms, allergens, and microbial toxins not previously reported in spacecraft, allowing for a more complete health assessment. Key findings during this experiment included: a) Generally, advanced molecular techniques were able to reveal a few organisms not recovered using culture-based methods; however, there is no indication that current monitoring is "missing" any medically significant bacteria or fungi. b) Molecular techniques have tremendous potential for microbial monitoring, however, sample preparation and data analysis present challenges for spaceflight hardware. c) Analytical results indicate that some molecular techniques, such as denaturing gradient gel electrophoresis (DGGE), can be much less sensitive than culture-based methods. d) More sensitive molecular techniques, such as quantitative polymerase chain reaction (QPCR), were able to identify viral DNA from ISS environments, suggesting potential transfer of the organism between crewmembers. In addition, the hardware selected for this experiment represented advances for next-generation sample collection. The advanced nature of this collection hardware was noted, when the Sartorius MD8 Air Port air sampler from the SWAB experiment remained on board ISS at the request of JAXA investigators, who intend to use it in completion of their microbial ecology experiment.

Castro, V. A.↗
DOE OSTI2025

An atomic cluster expansion (ACE) potential for water under extreme conditions

We present a machine learning interatomic potential for water designed to capture its complex multiphase behavior, including both molecular and superionic ice phases. The potential is based on the atomic cluster expansion (ACE) formulation and has been parameterized to enable high-fidelity molecular dynamics simulations of water under extreme conditions, for pressures up to 100 GPa and for temperatures between 500 and 6000 K. A diverse range of configurations was generated through ab initio molecular dynamics (AI-MD) simulations, covering insulating and superionic ice phases, liquid water, and dissociated plasma phase. We demonstrate that the H 2 O ACE potential accurately reproduces experimental and DFT predicted isotherms and Hugoniots. Crucially, the potential is able to capture the intricate phase behavior of water, including the transition from molecular fluid to the appropriate solid ice phases, and the superionic ice phases. This work provides a robust interatomic potential that can be used for large-scale, accurate simulations of water under extreme thermodynamic conditions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1988

Surface potential of the water liquid-vapor interface

An analysis of an extended molecular dynamics calculation of the surface potential (SP) of the water liquid-vapor interface is presented. The SP predicted by the TIP4P model is -(130 + or - 50) mV. This value is of reasonable magnitude but of opposite sign to the expectations based on laboratory experiments. The electrostatic potential shows a nonmonotonic variation with depth into the liquid.

Wilson, Michael A.↗
DOE OSTI2025

Weighted active space protocol for multireference machine-learned potentials

Multireference methods such as multiconfiguration pair-density functional theory accurately capture electronic correlation in systems with strong multiconfigurational character, but their cost precludes direct use in molecular dynamics. Combining these methods with machine-learned interatomic potentials (MLPs) can extend their reach. However, the sensitivity of multireference calculations to the choice of the active space complicates the consistent evaluation of energies and gradients across structurally diverse nuclear configurations. To overcome this limitation, we introduce the weighted active space protocol (WASP), a systematic approach to assign a consistent active space for a given system across uncorrelated configurations. By integrating WASP with MLPs and enhanced sampling techniques, we propose a data-efficient active learning cycle that enables the training of an MLP on multireference data. We demonstrated the approach on the TiC + -catalyzed C–H activation of methane, a reaction that poses challenges for Kohn–Sham density functional theory due to its significant multireference character. This framework enables accurate and efficient modeling of catalytic dynamics, establishing a paradigm for simulating complex reactive processes beyond the limits of conventional electronic-structure methods.

enhanced sampling↗
NASA NTRS1996

Sulfur and Hydrogen Isotope Anomalies in Organic Compounds from the Murchison Meteorite

Isotopic measurements have been made on organic sulfur and phosphorus compounds recently discovered in the Murchison meteorite. Carbon, hydrogen and sulfur measurements were performed on individual members of the organic sulfur compounds, alkyl sulfonates; and carbon and hydrogen measurements were made on bulk alkyl phosphonates. Cooper and Chang reported the first carbon isotopic measurements of Murchison organic sulfonates, providing insight into the potential synthetic mechanisms of these and, possibly, other organic species. Hydrogen isotopic measurements of the sulforiates now reveal deuterium excesses ranging from +660 to +2730 %. The deuterium enrichments indicate formation of the hydrocarbon portion of these compounds in a low temperature astrophysical environment consistent with that of dense molecular clouds. Measurements of the sulfur isotopes provide further constraints on the origin and mechanism of formation of these organic molecules. Recently, there has been growing documentation of sulfur isotopic anomalies in meteoritic material. Thiemens and Jackson have shown that some bulk ureilites possess excess S-33 and Thiemens et al. have reported excess S-33 in an oldhamite separate from the Norton County meteorite. Rees and Thode reported a large S-33 excess in an Allende acid residue, however, attempts to verify this measurements have been unsuccessful, possibly due to the heterogeneous nature of the carrier phase. With the recognition that sulfur isotopes may reflect chemistry in the protosolar nebula or the precursor molecular cloud, identification of potential carriers is of considerable interest. In the present study, the stable isotopes of sulfur were measured in methane sulfonic acid extracted from the Murchison meteorite. The isotopic composition was found to be: (delta)S-33 = 2.48 %, (delta)S-34 = 2.49 % and (delta)S-36 = 6.76 %. Based upon analysis of more than 60 meteoritic and numerous terrestrial samples, the mass fractionation lines are defined by Delta-33 = (delta)S-33 -0.50(delta)S-34 and Delta-36 = (delta)s-36 - 1.97 (delta)S-34. From these relationships Delta-33 = 1.24 % and Delta-36 = 0.89 % are observed. These anomalies, particularly the Delta-33, lie well outside the range of analytical uncertainty. They are the largest observed in any meteoritic component and the first found in an organosulfur compound. As discussed by Thiemens and Jackson, due to it's position on the periodic chart, sulfur undergoes chemically induced mass independent isotopic fractionations as does oxygen. Experiments by Mauersberger et. al. show that in such processes, the magnitude of fractionation for the different isotopically substituted species varies with mass and angular momentum; thus, anomalies are expected for both S-33 and S-36, but not necessarily of the same magnitude. Laboratory experiments have also confirmed that chemically produced, mass independent fractionations are mediated by molecular symmetry factors. A chemical source of fractionation requires that the sulfur isotopic anomaly was established in the gas phase, probably in reactions involving symmetric CS2. The discovery of an anomalous sulfur isotopic composition in a specific molecule containing excess deuterium is an important advance in the understanding of the cosmochemistry of sulfur. This evidence suggests that methanesulfonic acid was synthesized by interstellar processes. Further measurements and details of possible synthesis and fractionation mechanisms will be presented.

Cooper, G. W.↗
DOE OSTI2024

Temperature and density dependent pair potential for deuterium under shock

Large-scale classical molecular dynamics (CMD) simulations naturally include the microscopic physics necessary for atomistic modeling of shock release at the ablator-fuel interface in an inertial confinement fusion (ICF) capsule. Here, the multi-megabar shocks utilized in ICF experiments can drive the deuterium fuel from ambient to electron volt temperatures (T) and multi-fold compression. Modeling interatomic interactions over such an extreme range of conditions is challenging for empirical bond order potentials. We generate a pair potential for deuterium with explicit temperature and mass density dependence from ab initio density functional theory molecular dynamics using the iterative Boltzmann inversion method. This potential accurately reproduces the radial distribution functions and pressures from DFT in CMD equilibrium simulations across a wide range of thermodynamic conditions, yet fails to return the expected Hugoniot relations when used in direct CMD shock simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Neural network potentials with effective charge separation for non-equilibrium dynamics of ionic solids: a ZnO case study

Developing neural network potentials (NNPs) accurate under non-equilibrium dynamics is challenging, as such systems require extensive sampling beyond equilibrium phases. Here we construct high-fidelity NNPs for zinc oxide (ZnO), a polymorphic ionic solid, using density functional theory (DFT) reference data. To efficiently capture transitional configurations, we combine enhanced-sampling molecular dynamics with empirical potentials, data distillation, and pretraining on short-range atomic energies (A-Train), followed by transfer learning with DFT-relabeled datasets. This hierarchical approach improves transferability across polymorphs and stress states. We further introduce effective charge separation, treating long-range Coulombic terms analytically while short-range residual interactions are learned by the NNP. The optimal effective charges fall in the range 0.5–1.0 q e , consistent with dielectric-screened values derived from formal charges but distinct from Bader estimates. Motivated by this observation, we propose a simple data-driven protocol in which effective charges are optimized by comparing DFT reference energies with explicit Coulomb calculations, without additional NNP training. This strategy improves accuracy and transferability in DFT-level predictions of energies, forces, and stress. Together, these results provide a practical charge-selection framework for robust NNP development in ionic solids, enabling reliable simulation of polymorphic phase transformations and non-equilibrium dynamics.

Chemistry↗
DOE OSTI2024

Enhancing high-fidelity neural network potentials through low-fidelity sampling

The efficacy of neural network potentials (NNPs) critically depends on the quality of the configurational datasets used for training. Prior research using empirical potentials has shown that well-selected liquid–solid transitional configurations of a metallic system can be translated to other metallic systems. This study demonstrates that such validated configurations can be relabeled using density functional theory (DFT) calculations, thereby enhancing the development of high-fidelity NNPs. Training strategies and sampling approaches are efficiently assessed using empirical potentials and subsequently relabeled via DFT in a highly parallelized fashion for high-fidelity NNP training. Our results reveal that relying solely on energy and force for NNP training is inadequate to prevent overfitting, highlighting the necessity of incorporating stress terms into the loss functions. To optimize training involving force and stress terms, we propose employing transfer learning to fine-tune the weights, ensuring that the potential surface is smooth for these quantities composed of energy derivatives. This approach markedly improves the accuracy of elastic constants derived from simulations in both empirical potential-based NNPs and relabeled DFT-based NNPs. Overall, this study offers significant insights into leveraging empirical potentials to expedite the development of reliable and robust NNPs at the DFT level.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Full‐dimensional coupled‐channel statistical approach to atom‐triatom systems and applications to H/D + O 3 reaction

Abstract The statistical quantum model (SQM), which assumes that the reactivity is controlled by entrance/exit channel quantum capture probabilities, is well suited for chemical reactions with a long‐lived intermediate complex. In this work, a time‐independent coupled‐channel implementation of the SQM approach is developed for atom‐triatom systems in full dimensionality. As SQM treats the capture dynamics quantum mechanically, it is capable of handling quantum effects such as tunneling. A detailed study of the H/D + O 3 capture dynamics was performed by applying the newly developed SQM method on an accurate global potential energy surface. Agreement with previous ring polymer molecular dynamics (RPMD) results on the same potential energy surface is excellent except for very low temperatures. The SQM results are also in reasonably good agreement with available experimental rate coefficients. The strong H/D kinetic isotope effect underscores the dominant role of quantum tunneling under an entrance channel barrier at low temperatures.

Yang, Dongzheng↗
DOE OSTI2025

Bridging material models across scales: An integrated approach to equation of state and molecular dynamics modeling of copper

New uncertainty-aware equation of state (EOS) and electrical conductivity (EC) models for copper have been developed. The multiphase EOS/EC models are fit to experimental solid/liquid EC isobar measurements as well as density-functional theory molecular dynamics (DFT-MD) EC calculations in both expanded and compressed regimes (0.1–16 g/ cm 3 ⁠). The liquid and solid EOS phases were fit to available experimental data along with additional DFT-MD data over the same range as the EC. Leveraging the DFT-MD data, a corresponding machine-learned interatomic potential (MLIAP) for copper was trained using genetic-algorithm optimization. The copper MLIAP was constrained by EOS shock points at high compressions. The final EOS bounded MLIAP proves to be stable over a large density range (approximately 0.1–20 g/ cm 3 ) with good agreement to an isothermal compression curve, shock Hugoniot, and liquid speed of sound measurements at high pressures (100s of GPa).

Acoustic measurements and instrumentation↗
NASA NTRS1986

Space station molecular sieve development

An essential function of a space environmental control system is the removal of carbon dioxide (CO2) from the atmosphere to control the partial pressure of this gas at levels lower than 3 mm Hg. The use of regenerable solid adsorbents for this purpose was demonstrated effectively during the Skylab mission. Earlier sorbent systems used zeolite molecular sieves. The carbon molecular sieve is a hydrophobic adsorbent with excellent potential for space station application. Although carbon molecular sieves were synthesized and investigated, these sieves were designed to simulate the sieving properties of 5A zeolite and for O2/N2 separation. This program was designed to develop hydrophobic carbon molecular sieves for CO2 removal from a space station crew environment. It is a first phase effort involved in sorbent material development and in demonstrating the utility of such a material for CO2 removal on space stations. The sieve must incorporate the following requirements: it must be hydrophobic; it must have high dynamic capacity for carbon dioxide at the low partial pressure of the space station atmosphere; and it must be chemiclly stable and will not generate contaminants.

Chang, C.↗
DOE OSTI2024

Ultrafast Formation of Charge Transfer Trions at Molecular‐Functionalized 2D MoS 2 Interfaces

Abstract In this work, we investigate trion dynamics occurring at the heterojunction between organometallic molecules and a monolayer transition metal dichalcogenide (TMD) with transient electronic sum frequency generation (tr‐ESFG) spectroscopy. By pumping at 2.4 eV with laser pulses, we have observed an ultrafast hole transfer, succeeded by the emergence of charge‐transfer trions. This observation is facilitated by the cancellation of ground state bleach and stimulated emission signals due to their opposite phases, making tr‐ESFG especially sensitive to the trion formation dynamics. The presence of charge‐transfer trion at molecular functionalized TMD monolayers suggests the potential for engineering the local electronic structures and dynamics of specific locations on TMDs and offers a potential for transferring unique electronic attributes of TMD to the molecular layers.

Jing, Yuancheng↗
DOE OSTI2024

Ultrafast Formation of Charge Transfer Trions at Molecular‐Functionalized 2D MoS 2 Interfaces

In this work, we investigate trion dynamics occurring at the heterojunction between organometallic molecules and a monolayer transition metal dichalcogenide (TMD) with transient electronic sum frequency generation (tr-ESFG) spectroscopy. By pumping at 2.4 eV with laser pulses, we have observed an ultrafast hole transfer, succeeded by the emergence of charge-transfer trions. This observation is facilitated by the cancellation of ground state bleach and stimulated emission signals due to their opposite phases, making tr-ESFG especially sensitive to the trion formation dynamics. The presence of charge-transfer trion at molecular functionalized TMD monolayers suggests the potential for engineering the local electronic structures and dynamics of specific locations on TMDs and offers a potential for transferring unique electronic attributes of TMD to the molecular layers.

Time-resolved↗