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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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Molecular Design Strategies toward Improvement of Charge Injection and Ionic Conduction in Organic Mixed Ionic–Electronic Conductors for Organic Electrochemical Transistors
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Molecular Design of Supported MoO x Catalysts with Surface TaO x Promotion for Olefin Metathesis
A series of supported 3% MoOx catalysts were synthesized by incipient-wetness impregnation of 5%-15% TaO x surface modified γ-Al 2 O 3 support. The catalysts were characterized by in situ spectroscopies (DRIFTS, Raman, UV-vis, XAS) and multiple chemical probes (C 2 H 4 /C 4 H 8 titration, C 3 H 6 -TPSR, steady state propylene metathesis, NH 3 -IR adsorption). The supported tantalum oxide phase was present as surface TaO x sites on the γ-Al 2 O 3 support that capped that Al 2 O 3 surface hydroxyls. The change in available surface hydroxyls caused the subsequent anchoring of MoOx species to occur at different surface hydroxyls. This shifted the anchoring of MoO x species from basic (Al-OH) to neutral (Al 2 -OH) to more acidic (Al 3 -OH) surface hydroxyls as well as perturbation of the remaining alumina surface hydroxyls by the surface TaO x sites. The TaO x surface modified γ-Al 2 O 3 support increased the number of activated surface MoO x sites (Ns) by ~6x and the TOF by ~10x resulting in an increased activity of ~60x. In conclusion, It was found that the specific anchoring surface hydroxyls rather than the extent of oligomerization of the surface MoO x sites control the number of activated MoO x sites and TOF for propylene metathesis. No relationship between the nature of the surface Lewis/Brønsted acid sites and Ns and TOF were found to be present.
Molecular Design Considerations for Azobenzene Anolytes
Realization of high-density batteries requires the development of anolytes that display highly negative reduction potentials, solubility, and persistence in the charged state. Azobenzenes have garnered interest as potential anolytes for redox flow batteries. Here, we report the synthesis of a family of substituted azobenzene derivatives and evaluation of their solution-phase electrochemical properties. Systematic synthetic derivatization of this scaffold allows (1) access to anolytes of varying solubility, including intrinsically liquid derivatives that represent potential high-density charge carriers; (2) systematic variation of the reduction potential, and in some cases redox inventory, that provides azobenzenes with highly negative reduction potentials; and (3) control of the lifetime of the azobenzene radical anions that result from one-electron reduction. Electrokinetic experiments demonstrated that fast electron transfer occurs for all derivatives examined. Spectroscopic characterization of monoreduced azobenzene derivatives establishes that decomposition of the azobenzene radical anion proceeds via bimolecular disproportionation. Together, these results provide an experimental basis for the optimization of azobenzene anolytes for electrochemical storage applications, including redox flow batteries.
Molecular Design of Chiral Naphthalenediimide-Based Cations for Chiral One-Dimensional Metal Halide Semiconductors with Strong Chiroptical Activity and Amplified Charge Transport Ability
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Attention-based generative models for de novo molecular design
An implementation of attention within the variational autoencoder framework for continuous representation of molecules. The addition of attention significantly increases model performance for complex tasks such as exploration of novel chemistries.
Dyads with tunable near-infrared donor–acceptor excited-state energy gaps: molecular design and Förster analysis for ultrafast energy transfer
Nine dyads composed of bacteriochlorins were prepared to investigate excited-state energy transfer (FRET) processes.
Recent advances in electrolyte molecular design for alkali metal batteries
In response to societal developments and the growing demand for high-energy-density battery systems, alkali metal batteries (AMBs) have emerged as promising candidates for next-generation energy storage.
Leveraging Active Subspaces to Capture Epistemic Model Uncertainty in Deep Generative Models for Molecular Design
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Shaping Symmetry and Molding Morphology of Triply-Periodic Assemblies via Molecular Design of Block Copolymers
The research of this project integrates and advances state-of-the-art theoretical methods for geometrically complex BCP assembly (Grason), synthesis of precisely-defined BCP architectures (Coughlin), and quantitative and multi-scale approaches to morphological characterization of BCP assembly (Thomas).
Shaping Symmetry and Molding Morphology of Triply-Periodic Assemblies via Molecular Design of Block Copolymers
The research performed integrated and advanced state-of-the-art theoretical methods for geometrically-complex BCP assembly (Grason), synthesis of precisely-defined BCP architectures (Coughlin), and quantitative and multi-scale approaches to morphological characterization of BCP assembly (Thomas).
Application of Computer-Aided Molecular Design to a Pharmaceutical Separation
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Machine Learning-driven Molecular Design for Therapeutic Discovery
The ongoing novel coronavirus pandemic (COVID-19) has highlighted the need for new therapeutics to counter the threat of emerging viral pathogens. The main proteases are a promising target for developing antiviral inhibitors. In this work, we utilized a novel combination of artificial intelligence-driven iterative design of covalent inhibitor candidates, physics-based computational modeling of protein-inhibitor interactions, and “All in One” Native MS biophysical assay screening and characterization of therapeutic candidates. With our existing expertise in hit generation using a particular scaffold as a starting point, we first generated tens of thousands of compounds that preserve the key scaffold. In order to optimize the candidates, we calculated about 136 descriptors consisting of 2D and 3D features for molecules targeting the SARS-CoV-2 Main protease (Mpro). These compounds were initially filtered according to properties and further sorted by predicted binding affinity using our automated docking modeling and machine learning methods. We tested a handful of candidates and identified two as inhibitors of Mpro with micromolar affinities.
Shaping Symmetry and Molding Morphology of Triply-Periodic Network Assemblies via Molecular Design and Processing of Block Copolymers
Final technical report on DOE project conducted at Texas A & M University Dept. of Materials Science and Engineering concerning finding and understanding the design rules for triply periodic, bicontinuous morphological microdomain structures of block copolymers.