Search NASA⌕ Search

SEARCH · Search NASA

Results for “molecular processes”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Molecular property prediction for very large databases with natural language processing: a case study in ionic liquid design

The prospect of using artificial intelligence (AI) to accurately screen very large databases of compounds for multiple properties has yet to be realized. Here, we explore this possibility using ionic liquids (ILs) which offer unique physicochemical properties and excellent tunability, making them highly versatile solvents for various research applications. Screening millions of potential ILs for the best perfomance for use in specific tasks with experimental methods alone however, is impractical. Further, traditional’ physics-based computational chemistry is hindered by high computational cost. To address this challenge, we leverage a natural language processing (NLP)-based molecular embedding technique with advanced machine learning (ML) models to predict seven key IL properties: viscosity, density, ionic conductivity, surface tension, melting temperature, toxicity, and water solubility. Comprehensive datasets for these properties are obtained, then NLP featurization with Mol2vec is compared with other featurization techniques such as 2D Morgan fingerprints, and 3D quantum chemistry-derived sigma profiles. NLP-based featurization exhibited the best predictive performance, achieving the highest R 2 and lowest RMSE values for all the studied IL properties. Further, we present case studies of how ILs might be screened using combined property criteria for practical cases – lignocellulosic biomass processing, CO 2 capture, and optimal electrolytes for batteries – screening a novel database of ∼10.6 million generated feasible ILs. The results introduce NLP as a powerful tool for engineering many designer solvents with desirable properties for task specific applications.

Mohan, Mood [Oak Ridge National Laboratory (ORNL),↗
NASA NTRS1991

A space ultra-vacuum experiment - Application to material processing

An experiment to create and characterize an ultra-vacuum environment in low earth orbit is being developed. A wake region is known to form behind a satellite in low earth orbit. Limited theoretical and experimental results for flowfields around spacecraft are available and a brief discussion of these results is presented. The space experiment package to create an ultra-vacuum condition in the wake region is referred to as the Wake Shield Facility (WSF), manifested for flight on the Space Shuttle in 1993. In the vacuum region, epitaxial thin-films will be processed by molecular and chemical beam epitaxial growth techniques. Various particle flowfield and materials processing considerations for this experiment are presented.

Sega, R. M.↗
NASA NTRS1984

Vertical transport in the atmosphere: Measurement capabilities and requirements of VHF radars, part 1.6A

Mass exchange, mixing on transport in the atmosphere involves reversible processes, i.e., any kind of organized motions such as wave and large scale flows, and nonreversible processes, i.e., molecular and turbulent diffusion. Without evaluating in detail the relative efficiency of these processes, an attempt is made to summarize those phenomena which can be qualitatively (and eventually also quantitatively) observed with VHF radars. Only mixing in the vertical direction is considered, since this appears to be the essential part of transport processes to which VHF radars can contribute better understanding. Mixing processes in the troposphere are discussed. Possible contributions of VHF radars to the study the mass exchange processes between the troposphere and stratosphere are studied. Transport in the middle atmosphere is briefly summarized, since it is in principle similar to transport in the lower atmosphere.

Rottger, J.↗
NASA NTRS1996

Formation of Ordered Arrays of Proteins on Surfaces

Van der Waals (dispersion) forces contribute to interactions of proteins with other molecules or with surfaces, but because of the structural complexity of protein molecules, the magnitude of these effects is usually estimated based on idealized models of the molecular geometry, e.g., spheres or spheroids. The calculations reported here seek to account for both the geometric irregularity of protein molecules and the material properties of the interacting media. While the latter are found to fall in the generally accepted range, the molecular shape is shown to cause the magnitudes of the interactions to differ significantly from those calculated using idealized models, with important consequences. First, the roughness of the molecular surface leads to much lower average interaction energies for both protein-protein and protein-surface cases relative to calculations in which the protein molecule is approximated as a sphere. These results indicate that a form of steric stabilization may be an important effect in protein solutions. Underlying this behavior is appreciable orientational dependence, one reflection of which is that molecules of complementary shape are found to exhibit very strong attractive dispersion interactions. Although this has been widely discussed previously in the context of molecular recognition processes, the broader implications of these phenomena may also be important at larger molecular separations, e.g., in the dynamics of aggregation, precipitation and crystal growth.

Lenhoff, A. M.↗
NASA NTRS1996

Van der Waals Interactions Involving Proteins

Van der Waals (dispersion) forces contribute to interactions of proteins with other molecules or with surfaces, but because of the structural complexity of protein molecules, the magnitude of these effects is usually estimated based on idealized models of the molecular geometry, e.g., spheres or spheroids. The calculations reported here seek to account for both the geometric irregularity of protein molecules and the material properties of the interacting media. Whereas the latter are found to fall in the generally accepted range, the molecular shape is shown to cause the magnitudes of the interactions to differ significantly from those calculated using idealized models. with important consequences. First, the roughness of the molecular surface leads to much lower average interaction energies for both protein-protein and protein-surface cases relative to calculations in which the protein molecule is approximated as a sphere. These results indicate that a form of steric stabilization may be an important effect in protein solutions. Underlying this behavior is appreciable orientational dependence, one reflection of which is that molecules of complementary shape are found to exhibit very strong attractive dispersion interactions. Although this has been widely discussed previously in the context of molecular recognition processes, the broader implications of these phenomena may also be important at larger molecular separations, e.g., in the dynamics of aggregation, precipitation, and crystal growth.

Roth, Charles M.↗
DOE OSTI2026

Understanding Adsorption and Reactions at Aqueous Oxide Interfaces with Neural Network Potential Molecular Dynamics

Chemical processes at metal oxide−water interfaces are of central importance in geochemistry, biology, and energy technologies. A better understanding of these processes would allow us to make a significant step toward optimizing and controlling them, which could in turn lead to broader impacts. Computational modeling is indispensable to accomplishing this task because complexity and disorder often make it difficult to extract atomistic information from experiments. Balancing computational cost and accuracy, simulation schemes based on efficient machine learning representations of the potential energy surface (PES) predicted by ab initio calculations have become increasingly popular over the past decade. In particular, several studies have demonstrated the ability of machine learning models to accurately reproduce the complex ab initio PESs of aqueous oxide interfaces, allowing simulations of systems and processes that are not accessible with ab initio methods. In this Account, we review our recent efforts to understand adsorption processes and reactions at aqueous oxide interfaces using deep potential molecular dynamics (DPMD), a simulation scheme employing deep neural networks (DNNs), which has proven to be quite successful in accurately describing many different systems in the condensed phase. After summarizing the DPMD methodology, we first review our work on the acid−base chemistry of oxide surfaces in contact with water, a fundamental characteristic that controls proton transfer and surface charge at the interface. We focus on the aqueous interface of rutile IrO 2 , an oxide material thus far considered the best catalyst for the oxygen evolution reaction (OER). We show that this interface is characterized by a large fraction of dissociated water and a strong Brønsted acidity of the surface sites, in good agreement with the experimentally measured value of the point of zero proton charge. In our second example, we investigate how the adsorption of organic species from ambient air or water affects the structure and wettability of the aqueous interfaces of TiO 2 , a prototypical photocatalytic material. This is a question that is relevant to understanding the UV-induced hydrophilicity of TiO 2 surfaces, a property at the basis of self-cleaning windows and related applications. Specifically focusing on formic and acetic acids, the two most common atmospheric organic acids, our simulations reveal that these acids control the wettability of TiO 2 largely through acid−base chemistry at the interface rather than chemisorption on the oxide surface, a finding that could help improve the design of self-cleaning surfaces and photocatalytic devices. Finally, we review our recent study of methanol at TiO 2 −water interfaces, a system whose interest is largely motivated by the role of methanol in enhancing photocatalytic hydrogen evolution on TiO 2 . Our simulations provide mechanistic insights into the coupled roles of the organic adsorbate and water at the TiO 2 interface, with implications for how methanol enhances the activity of H 2 evolution.

adsorption↗
DOE OSTI2025

Probing specific ion effects at air-aqueous dibutyl phosphate interfaces using vibrational sum frequency generation spectroscopy

Molecular properties at air–liquid and liquid–liquid interface hold the key to many processes involving molecular transport across phase boundaries from aerosol formation to carbon cycling and material separation using solvent extraction techniques. Using dibutyl phosphate (DBP) as a representative for partially aqueous soluble surfactants, the specific ion effect (SIE) of the Hofmeister series cations Cs + , Na + , Li + , and Mg 2+ on the partition and interaction between surfactant molecules and water molecules in the air–aqueous interface are investigated using vibrational sum frequency generation spectroscopy and surface tension measurements. In the presence of 1 mM and 1M bulk aqueous phase ionic strength salt concentrations, fundamental qualitative relationships are observed for the salting out of DBP relative to bulk aqueous phase nitrate salt concentrations and the specific cations species. At 1 mM ionic strength, the interfacial charge and hence the interfacial potential modulates the electrostatic interactions; in particular, the counter cations partially screen the negatively charged interface induced by the DBP in a direct Hofmeister order. At 1M ionic strength, the electric field at the interface or interfacial potential is effectively neutralized, and the counter cations promote the partitioning of DBP to the interface depending on their specific interaction with the DBP head group and metal ion hydration properties. The present results lay a foundation to study SIEs of heavier metals on hydrophobic-aqueous DBP interfaces.

Louie, Christina [Washington State University, Pul↗
DOE OSTI2025

Screening green solvents for multilayer plastic film recycling processes

Multilayer (ML) plastic films are essential packaging materials that help protect products from diverse external factors; however, only 5% of all ML films are recycled in the United States. Solvent-based technologies are a promising alternative for recycling ML films because they enable recovery of constituent polymer resins. For example, the Solvent Targeted Recovery and Precipitation (STRAPTM) process sequentially dissolves and separates polymer components using a series of targeted solvent washes. A crucial design aspect of this process is the impact of selected solvents on human health and on the environment. Here, this work introduces a computational framework that integrates molecular modeling, process modeling, techno-economic analysis (TEA), and life-cycle analysis (LCA) to quickly screen green solvents for solvent-based ML recycling processes. Initial screening for solvents based on selectivity is performed by estimating temperature-dependent solubilities using molecular-scale models. Subsequent screening uses basic estimates of energy use and octanol-water partition coefficients (logP) as key measures of health, safety, and environmental hazards. Detailed process modeling, TEA, and LCA are used on a reduced set of promising solvents identified in early screening steps to more accurately determine how solvent selection and associated operating conditions impact overall economics and environmental impacts. The framework is used for the identification of green solvents (from a database of 1,000 solvents) that separate an industrial ML film composed of polyethylene (PE), ethylene vinyl alcohol (EVOH), and polyethylene terephthalate (PET). Our analysis shows the effectiveness of the framework and reveals fundamental trade-offs between solvent greenness, solubility, and economics. Our work emphasizes the importance of taking a holistic systems view during solvent design and aims to inform the development of new processes for ML film recycling and the identification of new ML films that are easier to recycle.

economics↗
DOE OSTI2020

Appendix Q: Recommendations for Developing Molecular Assays for Microbial Pathogen Detection Using Modern In Silico Approaches

We describe the use of in silico approaches to improve the process of molecular assay development and reduce time and cost by utilizing available databases of whole genome pathogen sequences combined with modern bioinformatics and physical modeling tools. Well-characterized assays are needed for accurately detecting pathogens in environmental and patient samples and also for evaluation of the efficacy of a medical countermeasure that may be administered to patients. The polymerase chain reaction (PCR) remains the gold standard for pathogen detection due to the simplicity of its instrumentation, low cost of reagents, and outstanding limit of detection (LOD), sensitivity, and specificity. However, creation of such PCR assays often involves iterations of design, preliminary testing, and thorough validation with clinical isolates and testing in relevant matrices, which can be time consuming, costly, and result in suboptimal assays. Since formal validation (e.g., for Emergency Use Authorization [EUA] or Food and Drug Administration [FDA] licensure) of an infectious disease assay can be very expensive and can require extensive time of development, having a well-designed assay up front is a critical first step. Yet, many assays described in the literature utilized limited design capabilities and many initially promising assays fail the validation process, resulting in increased costs and timelines for successful product development. While the computational approaches outlined in this document by no means obviate the need for wet lab testing, they can reduce the amount of effort wasted on empirical optimization and iterative redesigns and also guide validation studies. The proposed computational approaches also result in higher performing assays with better sensitivity, specificity, and lower LOD and reduce the possibility of assay failure due to signature erosion. To provide clarity, an extensive glossary of defined terms is provided.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Reactome and the Gene Ontology: digital convergence of data resources

Abstract Motivation Gene Ontology Causal Activity Models (GO-CAMs) assemble individual associations of gene products with cellular components, molecular functions and biological processes into causally linked activity flow models. Pathway databases such as the Reactome Knowledgebase create detailed molecular process descriptions of reactions and assemble them, based on sharing of entities between individual reactions into pathway descriptions. Results To convert the rich content of Reactome into GO-CAMs, we have developed a software tool, Pathways2GO, to convert the entire set of normal human Reactome pathways into GO-CAMs. This conversion yields standard GO annotations from Reactome content and supports enhanced quality control for both Reactome and GO, yielding a nearly seamless conversion between these two resources for the bioinformatics community. Supplementary information Supplementary data are available at Bioinformatics online.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Water Structure and Dynamics Near the Surfaces of Silicalite-1

Zeolites are crystalline microporous aluminosilicates that are commonly used as industrial sorbents and membranes. Solvent structuring and dynamics near zeolite crystal surfaces are thought to influence interfacial transport and molecular recognition processes, as well as fundamental aspects of their crystallization from solution. Here, in this work, we use molecular dynamics (MD) simulations to investigate the behavior of interfacial water near the exposed (010), (100), and (101) crystal faces of silicalite-1, one of the most widely studied zeolites. The MD simulations reveal that water’s translational and orientational order is strongly influenced by the distinct corrugations, pore apertures, and functional group distributions presented on each surface. Specifically, we observe two distinct hydration layers near each surface. Water molecules in the contact layer are hydrogen bonded to two or three exposed surface silanol groups. The relative populations of water molecules that are doubly and triply hydrogen bonded to the surface strongly depend on the distribution of the exposed silanols. The interactions with exposed surface silanols also influence water’s local orientational order and distribution across each surface. We also show that the structuring of the solvent near the different faces of silicalite-1 strongly impacts the interfacial dynamics. The translational and orientational relaxation dynamics of water are slowest in the contact layers and correlate with structural ordering near each face.

42 ENGINEERING↗
DOE OSTI2021

Imaging Reconfigurable Molecular Concentration on a Graphene Field-Effect Transistor

The spatial arrangement of adsorbates deposited onto a clean surface under vacuum typically cannot be reversibly tuned. Here we use scanning tunneling microscopy to demonstrate that molecules deposited onto graphene field-effect transistors (FETs) exhibit reversible, electrically tunable surface concentration. Continuous gate-tunable control over the surface concentration of charged F 4 TCNQ molecules was achieved on a graphene FET at T = 4.5K. This capability enables the precisely controlled impurity doping of graphene devices and also provides a new method for determining molecular energy level alignment based on the gate-dependence of molecular concentration. Gate-tunable molecular concentration is explained by a dynamical molecular rearrangement process that reduces total electronic energy by maintaining Fermi level pinning in the device substrate. Finally, the molecular surface concentration is fully determined by the device back-gate voltage, its geometric capacitance, and the energy difference between the graphene Dirac point and the molecular LUMO level.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Intrinsic glassy-metallic transport in an amorphous coordination polymer

Conducting organic materials, such as doped organic polymers, molecular conductors and emerging coordination polymers4, underpin technologies ranging from displays to flexible electronics. Realizing high electrical conductivity in traditionally insulating organic materials necessitates tuning their electronic structure through chemical doping6. Furthermore, even organic materials that are intrinsically conductive, such as single-component molecular conductors, require crystallinity for metallic behavior. However, conducting polymers are often amorphous to aid durability and processability. Using molecular design to produce high conductivity in undoped amorphous materials would enable tunable and robust conductivity in many applications, but there are no intrinsically conducting organic materials that maintain high conductivity when disordered. Here we report an amorphous coordination polymer, Ni tetrathiafulvalene tetrathiolate, which displays markedly high electronic conductivity (up to 1,200 S cm –1 ) and intrinsic glassy-metallic behavior. Theory shows that these properties are enabled by molecular overlap that is robust to structural perturbations. This unusual set of features results in high conductivity that is stable to humid air for weeks, pH 0–14 and temperatures up to 140 °C. Furthermore, these findings demonstrate that molecular design can enable metallic conductivity even in heavily disordered materials, raising fundamental questions about how metallic transport can exist without periodic structure and indicating exciting new applications for these materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1973

Materials processing in zero gravity

Manufacturing processes which are expected to show drastic changes in a space environment due to the absence of earth gravity are classified according to (1) buoyancy and thermal convection sensitive processes and (2) processes where molecular forces like cohesion and adhesion remain as the relatively strongest and hence controlling factors. Some specific process demonstration experiments carried out during the Apollo 14 mission and in the Skylab program are described. These include chemical separation by electrophoresis, the M551 metals melting experiment, the M552 exothermic brazing experiment, the M553 sphere forming experiment, the M554 composite casting experiment, and the M555 gallium arsenide crystal growth experiment.

Wuenscher, H. F.↗
DOE OSTI2025

Origin of Stabilization of Ligand-Centered Mixed Valence Ruthenium Azopyridine Complexes: DFT Insights for Neuromorphic Applications

Redox-driven conductance changes are critical processes in molecular- and coordination-complex-based memristive thin films and devices that are envisioned for neuromorphic technologies, but fundamental mechanisms of conductance switching are not fully understood. Here, we explore charge disproportionation (CD) processes in [Ru II L 2 ](PF 6 ) 2 molecular systems that intrinsically involve interfragment charge transfer (IFCT). Using a combination of ab initio molecular dynamics simulation (AIMD), time-dependent density functional theory (TD-DFT), and density functional theory (DFT) calculations, we investigate the electron transfer mechanisms and the roles of temperature and cell volumetric expansion in facilitating the counterion movements and electronic transitions required for low-cost IFCT and charge redistribution. A detailed analysis of the density of states and TD-DFT calculations highlights that unpaired electrons play a crucial role in low-energy transitions, with the azo (N=N) groups of the ligand serving as the primary sites for electronic transport between molecular fragments, further stabilizing the asymmetric state. Localization of added electrons on azo ligands occurs with negligible change at the Ru centers, supported by atomic volume expansions up to +4.74 bohr 3 , and goes along with a progressive reduction of the HOMO−LUMO gap across redox states, suggesting enhanced conductivity. The TD-DFT analysis reveals a dominant IFCT excitation at 2082.76 nm in the doubly reduced (22) state, while a stabilization energy of 1.20 eV of the asymmetric (13) state relative to the symmetric (22) state is predicted by constrained DFT. Periodic DFT and AIMD simulations emulating a molecular film show that the stabilization of the asymmetric state, relative to a symmetric one, translates in net charge separation values (order of ∼0.33 e) that are strongly linked to increased counterion mobility (average counterion displacements exceeding 0.7 Å per atom during CD events) and the involvement of azo groups in electron redistribution. These findings, which align with previously reported experimental and computational data, provide key insights into the IFCT mechanisms and electronic transport facilitated by azo groups, with important implications for redox-driven memristive and neuromorphic technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1972

Transient variation of martian ground-atmosphere thermal boundary layer structure.

Results of a numerical simulation of the diurnal redistribution of temperature by radiative and molecular-conductive processes in the Martian soil-atmosphere system. An attempt is made to assess the importance of atmospheric molecular conduction near the surface and to estimate the characteristic depth of the diurnal temperature wave. The computational results are found to indicate a dual structure in the diurnal temperature wave propagation pattern, with a diffusive-type wave in the lowest 150 m superimposed on a radiatively induced disturbance with a characteristic scale of 1.8 km. Atmospheric molecular thermal conduction typically accounts for about 15% of the total heating/cooling in the lowest 25 m. Thermal conduction in both the soil and atmosphere appears to be an important factor in the thermal coupling of these subsystems. A free-convection regime in the conduction layer is predicted by the model for about five hours of the Martian day.

Pallmann, A. J.↗
DOE OSTI2024

Thermodynamics and kinetics of interconversion between platinum nanoparticles and cations in zeolites

In metal-containing zeolites, sintering and redispersion processes exercise control over the identity of metal site structures, but the thermodynamic and kinetic factors that influence these molecular-level processes are not completely understood. Furthermore, we assess the ability of first principles informed free energy models (for supported and unsupported nanoparticles) and kinetic models integrating Ostwald ripening with atom trapping to describe the interconversion between Pt cations and nanoparticles encapsulated in chabazite (CHA) zeolites. Density functional theory-derived thermodynamic phase diagrams show that the interconversion between cations, favored in oxidizing environments, and particles, favored in reducing environments, is fully reversible within a wide range of their respective conditions (temperatures and pressures) for CHA and several other zeolite topologies. Kinetic Monte Carlo simulations of Pt redispersion are consistent with experimentally observed redispersion kinetics of encapsulated Pt nanoparticles in CHA zeolites, and model results suggest the zeolite host imparts additional stability for Pt nanoparticles. We envision our thermodynamic and kinetic models for Pt-CHA are also capable of describing nanoparticle and cation interconversions for other zeolite frameworks under similar conditions.

36 MATERIALS SCIENCE↗