Search NASA⌕ Search

SEARCH · Search NASA

Results for “dynamic covalent chemistry”

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.

777 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

In Silico Chemical Experiments in the Age of AI: From Quantum Chemistry to Machine Learning and Back

Computational chemistry is an indispensable tool for understanding molecules and predicting chemical properties. However, traditional computational methods face significant challenges due to the difficulty of solving the Schrödinger equations and the increasing computational cost with the size of the molecular system. In response, there has been a surge of interest in leveraging artificial intelligence (AI) and machine learning (ML) techniques to in silico experiments. Integrating AI and ML into computational chemistry increases the scalability and speed of the exploration of chemical space. However, challenges remain, particularly regarding the reproducibility and transferability of ML models. This review highlights the evolution of ML in learning from, complementing, or replacing traditional computational chemistry for energy and property predictions. Starting from models trained entirely on numerical data, a journey set forth toward the ideal model incorporating or learning the physical laws of quantum mechanics. This paper also reviews existing computational methods and ML models and their intertwining, outlines a roadmap for future research, and identifies areas for improvement and innovation. Ultimately, the goal is to develop AI architectures capable of predicting accurate and transferable solutions to the Schrödinger equation, thereby revolutionizing in silico experiments within chemistry and materials science.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Nanostructuring and Underscreening of Bisalt Electrolytes with Dual-Anion Effects: Insights from Small-Angle Scattering Prepeak Analysis

Using small-angle neutron scattering, we studied the nanostructure of a prototypical D(H)-bonded network electrolyte, alkaline sodium aluminate bisalt, at concentrations up to solute volume fraction of ~0.5. Analysis of the structure factor prepeak at 0.1 < Q < 1.0 Å-1 showed that its evolution is associated with nanoscopic species distribution in water-anion network., with differences in characteristic distance d between OD- and Al(OD)4- anions related to their distinct sizes and interactions. When the solute volume fraction approached 0.5, a common/maximum value of ~4.5 Å was found for the correlation length ? that characterizes the electrostatic force in concentrated electrolyte solution before precipitation occurred. This implies that the solutions’ morphology and behavior at high concentrations may be governed by geometric factors, rather than the chemistry of the specific anion. Furthermore, the scaling of ? with concentration yielded an exponent of 1.25(1), suggesting that ? is limited to a few Å. By combining the current observations of structural heterogeneity at the nanoscale, with dynamic heterogeneity at the microscopic scale from our previous quasi-elastic neutron scattering study, we have established a structural origin of local “caging” and restricted structural relaxation processes. These local solvent-solute interactions not only control dynamics heterogeneity in concentrated electrolytes but also are responsible for crystallization processes in industrial setting, such as aluminum production and radioactive waste treatment.

Wang, Hsiu-Wen↗
DOE OSTI2026

Influence of linkage chemistry and side-chain polarity on Ion 2 transport in click-functionalized polymerized ionic liquids.

Post-polymerization functionalization offers precise molecular weight control and enables the high-throughput investigation of structure−property relationships in polymer research. However, post-polymerization functionalization strategies often introduce additional linkage chemistry, and its role in the physical properties of polymerized ionic liquids (PILs) has yet to be explored. In this work, a series of PILs were synthesized using Cu(I)-catalyzed azide−alkyne cycloaddition (CuAAC), with comparison made to N-alkylation substitution chemistry. The triazole ring introduced by CuAAC chemistry was found to induce extensive ion aggregation and deteriorate ion transport. The impact of linkage chemistry on ion transport can be alleviated by incorporating polar ethylene glycol spacers in the side chain, achieving an ionic conductivity of 2.1 × 10−4 S/cm at 30 °C. Furthermore, the effect of polar spacer placement was explored, revealing that overall side-chain polarity, rather than polarity in the vicinity of the ionic group, governs ion aggregation and ion transport in PILs.

Shan, Naisong↗
NASA NTRS2015

Development of Li-Metal Battery Cell Chemistries at NASA Glenn Research Center

State-of-the-Art lithium-ion battery technology is limited by specific energy and thus not sufficiently advanced to support the energy storage necessary for aerospace needs, such as all-electric aircraft and many deep space NASA exploration missions. In response to this technological gap, our research team at NASA Glenn Research Center has been active in formulating concepts and developing testing hardware and components for Li-metal battery cell chemistries. Lithium metal anodes combined with advanced cathode materials could provide up to five times the specific energy versus state-of-the-art lithium-ion cells (1000 Whkg versus 200 Whkg). Although Lithium metal anodes offer very high theoretical capacity, they have not been shown to successfully operate reversibly.

battery↗
NASA NTRSDate not supplied

High-Order Methods in NASA’s Next Generation of Computational Fluid Dynamics Tools

The missions of the National Aeronautics and Space Administration (NASA) routinely produce unique requirements and challenges for development and application of Computational Fluid Dynamics (CFD) methods. NASA presently embodies four distinct Mission Directorates: Aeronautics Research, Exploration Systems, Science, and Space Operations. These missions generate requirements for systems that operate in a wide variety of environments. They range from the high-speed flight of aerodynamically optimized vehicles operating in the earth’s atmosphere to spacecraft designed for missions that don’t favor aerodynamic optimization, some operating in the atmosphere of planets and planetary moons such as Mars and Venus or Saturn’s moon Titan. Systems supporting these vehicles, such as rocket and jet propulsion, reaction control systems, fluid and thermal transfer systems, etc. can also generate their own unique set of flow phenomena that challenge today’s CFD methodology. Through the NASA Engineering and Safety Center (NESC), NASA annually conducts state-of-the-discipline assessments in fifteen distinct engineering disciplines. These assessments are performed by the NASA Technical Fellows that lead Technical Discipline Teams (TDT) of recognized experts in these fifteen areas. In the Aerosciences discipline, three topics have been identified as the top challenges for the discipline: aero-plume interaction prediction, unsteady separated flows, and aerothermodynamic prediction. These challenge areas are defined by the Agency’s high-risk projects and problems on which the NESC is requested to perform independent testing, analysis, and assessments. When viewed as a whole, these tests, analyses, and assessments provide a clear view of the recurring technical challenges facing Agency engineers and researchers and can be used to guide future research and technology development. The present state-of-the-art in the application of CFD at NASA is the use of Reynolds-Averaged Navier- Stokes (RANS) solvers, primarily executed in a steady-state mode of operation. In isolated cases, Unsteady RANS (URANS) solvers have been employed when steady RANS solutions produce poorly converging or oscillating results or in cases, such as aeroelastic analysis, which require unsteady aerodynamic simulation. For most traditional external and internal aerodynamic flows, structured overset grids or unstructured grids are employed to minimize geometric modeling and grid generation times. Grid adaptation, primarily as a series of coarse-grain intermediate processing steps is also seeing use on particularly complex flow problems and configurations. In the case of aerothermodynamic flows, engineers have been forced to continue to employ structured grid techniques as the present unstructured grid methodology has proven inadequate in the prediction of surface heating. In the area of aero-plume interaction modeling, two-gas, frozen chemistry simulation is generally the state-of-the- art, with some production solvers capable of predicting flows with only a single gas component. Prediction of flows falling into the afore-mentioned top Aerosciences technical challenges have severely stressed the present state-of-the-art in CFD prediction and for some problems, such as unsteady separated flows and aero-plume interaction cases, engineers have begun employing Large Eddy Simulation (LES) and Hybrid RANS/LES techniques. In some isolated aero-propulsion interaction cases, chemically reacting flow simulations have been applied. These methods are highly evolutionary and engineers have little experience in their application, so they cannot be heavily relied upon in today’s application environment. Therefore, this leads one to muse over which numerical technologies will be included in the CFD tools that will be employed 30 years in the future. This presentation will describe specific technical problems that have stressed NASA’s traditional CFD methods to their breaking point and will link these issues to the Agency’s top Aerosciences technical challenges. The discussion will then shift to the characteristics of future CFD solvers that will be required to attack these challenges and how these characteristics differ from the present state-of-the- art. High-order methods certainly appear to have a place in the development of future CFD tools and some of the physical characteristics of our most challenging problems suggest that high-order methods are the only way to effectively solve them. But there are some relatively severe implementation issues that face these methods, particularly in the area of general applicability and robust operation as an engineering tool. Desired characteristics of next-generation CFD solvers will be discussed and the author’s view of which emerging numerical technologies might be employed to address these attributes will also be presented

David M Schuster↗
DOE OSTI2026

Interaction of Soil pH and Mineralogy Controls Soil Organic Matter Persistence through Changes in the Composition and Amount of Microbial Necromass

Microbial necromass–mineral associations are key to long-term soil organic matter (SOM) persistence. However, how soil pH and mineralogy interact to regulate SOM stability remains poorly understood. Here, we used artificial soils to test how three clay minerals (bentonite, kaolinite, and goethite), adjusted to four pH levels (5–8), affect microbial activity (respiration), microbial physiology (carbon use efficiency, CUE), microbial-derived residue material (necromass), and the formation and stability of mineral-associated organic matter (MAOM). Artificial soils were inoculated with a rhizosphere-derived microbial community cultured under the same pH conditions and on two representative simulated exudate types (organic acids and carbohydrates) and incubated for 6 weeks. In two complementary experiments, we added necromass from known microbial taxa to the same minerals across pH levels to isolate the role of necromass chemistry and loading. We found that soil pH shaped MAOM chemistry by altering microbial activity and necromass composition. In interaction with mineral type, pH also controlled MAOM thermal stability. Higher necromass loading weakened mineral-organic bonding, reducing MAOM stability, consistent with zonal mineral–organic interaction models. Our results demonstrate that microbial activity, rather than carbon use efficiency, better predicts MAOM formation and that pH-dependent necromass composition and loading govern MAOM persistence. These findings advance mechanistic understanding of SOM stabilization and have implications for predicting soil carbon dynamics under shifting environmental conditions.

carbon use efficiency↗