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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 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Supramolecular assembly of molecular wires alternating crown ethers and metal–halide complexes

Metal–halide complexes serve as key emissive centres in halide perovskites; however, precise control over their spatial organization through bottom-up assembly is challenging. Here we show that a crown-ether-assisted supramolecular assembly strategy can alternatingly connect metal–halide complexes and (crown ether@A) 2+ (where ‘A’ is an alkaline earth metal cation) complexes into a one-dimensional molecular wire, which can then be packed into a hexagonal crystal structure. This process resulted in the creation of an (18C6@Ba)MnBr 4 single crystal with green emission, achieving over 80% photoluminescence quantum yield and a narrow full width at half maximum. In addition, the non-centrosymmetric crystal structure gave rise to strong nonlinear optical responses, including second-harmonic generation. This versatile supramolecular assembly approach could be generalized to create various [M(I)X 2 ] − , [M(I)X 3 ] 2− , [M(II)X 4 ] 2− and [M(III)X 5 ] 2− molecular wires, broadening the potential for diverse emission colours and distinct optical properties. This strategy provides a general design principle for constructing supramolecular metal–halide building blocks with diverse optical functionalities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Tuning dispersity of linear polymers and polymeric brushes grown from nanoparticles by atom transfer radical polymerization

Molecular weight distribution imposes considerable influence on the properties of polymers, making it an important parameter, impacting morphology and structural behavior of polymeric materials. Atom transfer radical polymerization (ATRP) has established itself as a powerful tool to prepare polymers with predetermined molecular weight, preserved chain-end functionality, and low dispersity. More recently, ATRP has also been shown to provide a means to deliberately broaden molecular weight distributions, and, via retaining living chain-ends, to enable the formation of block copolymers with designed block dispersity, featuring new microstructures and potentially attractive properties. Here, similar methodologies have been developed to facilitate tuning of the dispersity of polymeric brushes grown from nanoparticles thus resulting in hybrid materials with enhanced fracture toughness and high inorganic content. Recent advances have given access to brush architectures comprised of uni- and bimodal block copolymers with unique morphologies along with interesting mechanical, thermal, and optical properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Influence of the molecular weight and size distribution of PSS on mixed ionic-electronic transport in PEDOT:PSS

The commercially available polyelectrolyte complex poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) is ubiquitous in organic and hybrid electronics. As such, it has often been used as a benchmark material for fundamental studies and the development of new electronic devices. Yet, most studies on PEDOT:PSS have focused on its electronic conductivity in dry environments, with less consideration given to its ion transport, coupled ionic-electronic transport, and charge storage properties in aqueous environments. These properties are essential for applications in bioelectronics (sensors, actuators), charge storage devices, and electrochromic displays. Importantly, past studies on mixed ionic-electronic transport in PEDOT:PSS neglected to consider how the molecular structure of PSS affects mixed ionic-electronic transport. Herein, we therefore investigated the effect of the molecular weight and size distribution of PSS on the electronic properties and morphology of PEDOT:PSS both in dry and aqueous environments, and overall performance in organic electrochemical transistors (OECTs). Using reversible addition–fragmentation chain transfer (RAFT) polymerization with two different chain transfer agents, six PSS samples with monomodal, narrow (D = 1.1) and broad (D = 1.7) size distributions and varying molecular weights were synthesized and used as matrices for PEDOT. We found that using higher molecular weight of PSS (Mn = 145 kg mol –1 ) and broad dispersity led to OECTs with the highest transconductance (up to 16 mS) and [μC*] values (~140 F cm –1 V –1 s –1 ) in PEDOT:PSS, despite having a lower volumetric capacitance (C* = 35 ± 4 F cm –3 ). The differences were best explained by studying the microstructure of the films by atomic force microscopy (AFM). We found that heterogeneities in the PEDOT:PSS films (interconnected and large PEDOT- and PSS-rich domains) obtained from high molecular weight and high dispersity PSS led to higher charge mobility (μOECT ~4 cm 2 V –1 s –1 ) and hence transconductance. Furthermore, these studies highlight the importance of considering molecular weight and size distribution in organic mixed ionic-electronic conductor, and could pave the way to designing high performance organic electronics for biological interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Dynamic Structure Discovery Applied to the Ion Transport in the Ubiquitous Lithium-ion Battery Electrolyte LP30

The electrolytes of the today omnipresent lithium-ion batteries (LIBs) have for more than 25 years been based upon 1 M LiPF 6 in a 50:50 EC:DMC mixture—commonly known as LP30. The success of the basic design of the LP30 electrolyte, with many variations and additions made over the years, is unchallenged. Yet, some molecular level fundamentals of LP30 are surprisingly elusive: the structure of the first solvation shell of the Li + cation is still a topic of current debate; the details of the dynamics are not fully understood; the interpretation of structural and dynamic properties is highly dependent on the analysis methods used; the contributions by different species to the ion transport and the energetics involved are not established. We here apply dynamic structure discovery analysis as implemented in CHAMPION to molecular dynamics simulation trajectories to bring new light on the structure and dynamics within LP30 and especially the (Li + ) ion transport to rationalize further development of LIB electrolytes.

25 ENERGY STORAGE↗
DOE OSTI2025

Simultaneous prediction of structural properties in epitaxially–grown GaN with quantum and conventional multi–output learning algorithms

Hundreds of GaN thin film crystal plasma–assisted molecular beam epitaxy synthesis experiment records spanning two decades were organized into a dataset correlating the growth experiment design parameters with discrete, binary determinations of crystallinity and surface morphology. Conventional data science techniques as well as both quantum and classical multi–output supervised machine learning algorithms were implemented to investigate the relationships between the operating parameter data and the structural figures of merit. Correlation coefficients, decision tree nodes, p–values, and SHAP values all support substrate temperature and gallium effusion cell conditions as being statistically significant for simultaneously influencing GaN crystallinity and surface morphology. Here, a conventional deep neural network learned best from the data, followed by a quantum–classical hybrid gradient boosting algorithm. When combined with calculations of uncertainty intervals based on VennAbers predictors, machine learning predictions of both structural properties show good agreement with results reported in published experimental literature.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Catalyst design for small molecule activation of energy consequence

This project targets the conversion of ubiquitous small molecules (e.g. NO, CO, H 2 O) into viable precursors to synthetic fuels. Current state of the art catalyst design has not directly targeted transition metal complexes capable of mediating the multi-electron redox processes necessary to reduce the overpotential (energy loss) required achieve efficient activation of small molecule substrates. In this vein, a new strategy has been developed for the assembly of polynuclear architectures; allowing for the construction of tunable polymetallic centers that assemble easily within a pre-organized template (conferring stability, selectivity and tunability) that can effect multi-electron redox processes for reactions. Catalyst development has commenced with the following target design elements: (1) catalysts featuring multiple transition metal ions in the same reaction space to greatly expand accessible molecular redox capabilities; (2) catalysts are assembled in a polynucleating ligand framework that permits control over the cluster morphology as well as the local steric and electronic environment of the transition metal ions within the cluster. The high-tunability of the catalyst composition (metal content) and geometric flexibility has permitted a rigorous assessment of electronic-structure-to-function relationship to be developed, further guiding synthetic efforts to realize more potent catalysts. The numerous permutations possible showcase the high degree of generality to this approach with many synthetic handles to tune redox and reaction chemistry. Trinuclear complexes have been synthesized featuring homo- and hetero-trinuclear cores featuring a variety of first row transition metal ions (Cr→Ni). The molecular clusters have been shown to successfully mediate multi-electron redox processes in a cooperative fashion without requiring strong chemical reductants or oxidants. The reactive molecular complexes are being utilized to activate and breakdown the robust bonds within typical waste stream small molecules (e.g., greenhouse gases) and convert them into value-added commodity chemicals. Ultimately, the catalysts developed by this approach will be required to convert energy acquired via renewable resources (e.g., solar or wind) into synthetic fuels as an energy storage mechanism.

10 SYNTHETIC FUELS↗
DOE OSTI2022

Is Genetic Engineering a Route to Enhance Microalgae-Mediated Bioremediation of Heavy Metal-Containing Effluents?

Contamination of the biosphere by heavy metals has been rising, due to accelerated anthropogenic activities, and is nowadays, a matter of serious global concern. Removal of such inorganic pollutants from aquatic environments via biological processes has earned great popularity, for its cost-effectiveness and high efficiency, compared to conventional physicochemical methods. Among candidate organisms, microalgae offer several competitive advantages; phycoremediation has even been claimed as the next generation of wastewater treatment technologies. Furthermore, integration of microalgae-mediated wastewater treatment and bioenergy production adds favorably to the economic feasibility of the former process—with energy security coming along with environmental sustainability. However, poor biomass productivity under abiotic stress conditions has hindered the large-scale deployment of microalgae. Recent advances encompassing molecular tools for genome editing, together with the advent of multiomics technologies and computational approaches, have permitted the design of tailor-made microalgal cell factories, which encompass multiple beneficial traits, while circumventing those associated with the bioaccumulation of unfavorable chemicals. Previous studies unfolded several routes through which genetic engineering-mediated improvements appear feasible (encompassing sequestration/uptake capacity and specificity for heavy metals); they can be categorized as metal transportation, chelation, or biotransformation, with regulation of metal- and oxidative stress response, as well as cell surface engineering playing a crucial role therein. This review covers the state-of-the-art metal stress mitigation mechanisms prevalent in microalgae, and discusses putative and tested metabolic engineering approaches, aimed at further improvement of those biological processes. Finally, current research gaps and future prospects arising from use of transgenic microalgae for heavy metal phycoremediation are reviewed.

Ranjbar, Saeed (ORCID:0000000256518605)↗
NASA NTRS1972

Molecular beam simulation of planetary atmospheric entry: Some recent results

Molecular beam sources for producing fast beams containing CO2 and atomic oxygen are discussed. Results pertinent to the design and calibration of mass spectrometer ion source for measurement of the Martian atmosphere during the free molecule portion of the entry trajectory are also presented. The shortcomings and advantages of the simulation technique are discussed. It is shown that an open cavity configuration retains sensitivity to atomic oxygen, provides reasonable signal enhancement from the stagnation effect, is not highly sensitive to pitch and yaw effects, and presents no unforeseen problems in measuring CO2 or atomic oxygen. The simulation techniques used provide assistance in designing, developing, and (potentially) in testing and calibrating the required flight instrument.

French, J. B.↗
NASA NTRS1972

Molecular beam simulation of planetary atmospheric entry - Some recent results.

Progress is reported in the development of molecular beam techniques to simulate entry into planetary atmospheres. Molecular beam sources for producing fast beams containing CO2 and atomic oxygen are discussed. Results pertinent to the design and calibration of a mass spectrometer ion source for measurement of the Martian atmosphere during the free molecule portion of the entry trajectory are also presented. The shortcomings and advantages of this simulation technique are discussed, and it is demonstrated that even with certain inadequacies much information useful to the ion source design was obtained. Particularly, it is shown that an open-cavity configuration retains sensitivity to atomic oxygen, provides reasonable signal enhancement from the stagnation effect, is not highly sensitive to pitch and yaw effects, and presents no unforeseen problems in measuring CO2 or atomic oxygen.

French, J. B.↗
NASA NTRS1994

The solar diameter and oblateness measured by the solar disk sextant on the 1992 September 30 balloon flight

This paper reports the results of a balloon flight of the Solar Disk Sextant (SDS) on 1992 September 30. This was the first flight in which the SDS used a wedge assembly fabricated by molecular contact in order to eliminate the wedge angle variations observed in previous flights. The instrument performed as designed. The main results obtained are values of the solar diameter for a number of discrete heliocentric latitudes, and the solar oblateness. The accuracy of the diameter values is better than 0.2 sec whereas the precision is approximately 1-2 mas. The equatorial solar diameter, at 1 AU, was 1919.06 sec +/- 0.12 sec, and the oblateness epsilon = 8.63 +/- 0.88 x 10(exp -6).

Sofia, S.↗
NASA NTRS2001

High-Flow PMR-Polymide Composites Developed With Mechanical Properties Comparable to Other High-Temperature Systems

PMR polyimides, in particular PMR-15, are well known for their excellent high-temperature stability and performance, and solvent resistance. However, the processing of these materials is limited, for the most part, to prepreg-based methods, such as compression or autoclave processing. These methods involve substantial amounts of hand labor, and as a result, manufacturing costs for components made from PMR polyimides can be high. In cost-sensitive applications, these high manufacturing costs can make the use of PMR polyimide-based components cost prohibitive. Lower cost manufacturing methods, such as resin transfer molding (RTM) and resin film infusion, have been demonstrated to reduce manufacturing costs by as much as 50 percent over prepreg-based methods. However, these processes are only amenable to materials with melt viscosities below 30 poise. Most PMR polyimides have melt viscosities on the order of 100 poise or higher. Recent efforts at the NASA Glenn Research Center have focused on chemical modifications to PMR polyimides to reduce their melt viscosity to the point where they could be processed by these low-cost manufacturing methods without adversely affecting their high-temperature properties and performance. These efforts have led to a new family of PMR polyimides that have melt viscosities significantly lower than that of PMR-15. Reductions in melt viscosity are brought about through the introduction of molecular twists in the polymer backbone. Carbon fiber (T650- 35) composites were prepared from one of these polyimides, designated PMR-Flex, by compression molding. The properties of these composites are presented below and compared with comparable composites made from PMR-15 and PETI-RTM, a new low-melt-viscosity polyimide.

Meador, Michael A.↗
DOE OSTI2025

Deep Learning Approaches for Predicting the Surface Tension of Ionic Liquids

Ionic liquids (ILs) are a novel class of solvents that have attracted significant attention due to their unique and tunable properties. Among their physiochemical characteristics, surface tension plays a critical role in various industrial applications including electrolytes, heat transfer fluids, and separation processes. However, because of the exploratory nature of IL design and the vast combinatorial space of possible anion–cation pairs, the experimental determination of these properties is often impractical, being both time-consuming and costly. To overcome these challenges, computational approaches are increasingly employed to develop accurate predictive models that can accelerate IL discovery and design. In this study, we present two deep learning (DL) models for predicting the surface tension of ILs across a broad temperature range at a constant pressure. The models use simplified molecular input line entry system, SMILES, representations of ILs to extract molecular features as inputs. Both DL models demonstrate excellent agreement with experimental data, achieving an R 2 value of 0.990 and a root-mean-square error of 0.792 mN/m. In conclusion, these results offer valuable insights for the rapid screening and rational design of ILs with tailored surface tension values.

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

Mining for Metal–Organic Systems: Chemistry Frontiers of Th-, U-, and Zr-Materials

The conceptual framework presented in this Perspective overviews the design principles of innovative thorium-based materials that could address urgent needs of the medicinal, nuclear energy, and waste remediation sectors from the lens of zirconium and uranium analogs. We survey the intersections of Zr, Th, and U chemistry with a focus on how the intrinsic behavior of each metal translates to broader material properties, including, but not limited to, structural and topological diversity, preferential metal–ligand binding, and reactivity. On the example of several classes of materials, including organometallic complexes, polyoxometalates, and the primary focus of this Perspective, metal–organic frameworks (MOFs), the design principles that govern the preparation of Zr-, Th-, and U-compounds, including oxophilicity, variation in oxidation states, and stable coordination environments have been considered. Further, we highlight how the impact of the mentioned variables may shift throughout the progression from discrete molecular systems to extended structures. We discuss the common assumption that zirconium-organic materials are typically considered a close analog of thorium-based congeners in areas such as material design and preparation. Through consideration of fundamental chemistry principles, we shed light on the relationships between Zr-, Th-, and U-based materials and highlight how a critical analysis of their distinct properties can be used to target a desired material performance. Finally, we provide a detailed understanding of Th-based materials chemistry by anchoring their fundamental properties between two well-studied reference points, zirconium- and uranium-containing analogs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Enhanced detection of volatile organic compounds (VOCs) by caffeine modified carbon nanotube junctions

Detection of vapor phase analytes and gas molecules is primarily essential for numerous applications including medical diagnostic, environmental monitoring, chemical threat detection, food quality control, and chemical warfare agents. Here, we developed Caffeine functionalized carbon nanotubes (CNTs) random network based vapor quantum resistive sensors (vQRSs) for volatile organic compounds (VOCs) detection. The localized transmission electron microscopy (TEM) image and energy dispersive X-ray spectroscopy (EDS) confirm migration of caffeine to CNT–CNT junction (CNTj). We have recorded more than one order of magnitude higher sensitivity and unique selectivity towards selective VOCs (e.g., acetone, toluene, ethanol, methanol, etc.) with short response time (few seconds) for caffeine modified CNT junction (Caf-CNTj) vQRSs. Molecular dynamics (MD) calculations suggest that the sensitivity of the sensor is diffusion limited, with an advective contribution for ethanol. Furthermore, the designed Caf-CNTj sensors can potentially be important candidate to be a part of electronic nose used for various application such as breath analysis and food quality monitoring.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Molecular evolution of human coronavirus-NL63, -229E, -HKU1 and -OC43 in hospitalized children in China

Human coronaviruses (HCoVs) HCoV-NL63, HCoV-229E, HCoV-HKU1 and HCoV-OC43 have been circulated in the human population worldwide, and they are associated with a broad range of respiratory diseases with varying severity. However, there are neither effective therapeutic drugs nor licensed vaccines available for the treatment and prevention of infections by the four HCoVs. In this study, we collected nasopharyngeal aspirates of children hospitalized for respiratory tract infection in China during 2014–2018 and conducted next-generation sequencing. Sequences of four HCoVs were then selected for an in-depth analysis. Genome sequences of 2 HCoV-NL63, 8 HCoV-229E, 2 HCoV-HKU1, and 6 HCoV-OC43 were obtained. Based on the full-length S gene, a strong temporal signal was found in HCoV-229E and the molecular evolutionary rate was 6 × 10 −4 substitutions/site/year. Based on the maximum-likelihood (ML) phylogenetic tree of complete S gene, we designated H78 as a new sub-genotype C2 of HCoV-HKU1, and the obtained P43 sequence was grouped into the reported novel genotype K of HCoV-OC43 circulating in Guangzhou, China. Based on the complete genome, potential recombination events were found to occur as two phenomena, namely intraspecies and interspecies. Moreover, we observed two amino acid substitutions in the S1 subunit of obtained HCoV-NL63 (G534V) and HCoV-HKU1 (H512R), while residues 534 and 512 are important for the binding of angiotensin-converting enzyme 2 and neutralizing antibodies, respectively. Our findings might provide a clue for the molecular evolution of the four HCoVs and help in the early diagnosis, treatment and prevention of broad-spectrum HCoV infection.

Shao, Nan↗
DOE OSTI2021

A Novel Hollow Fiber Membrane Reactor for High Purity H 2 Generation from Thermal Catalytic NH 3 Decomposition (Final Report)

Ammonia (NH 3 ), as a promising carbon neutral liquid fuel (CNLF) and an effective H 2 source, can be synthesized from air and water (N 2 extracted from air and H 2 from water) using renewable energy sources. To produce H 2 as an intermediate, it is essential to develop effective and economic NH 3 decomposition technologies. We have been developing an innovative hollow fiber membrane reactor for high purity H 2 generation from thermal catalytic NH 3 decomposition. The objective of the proposed research is to fabricate a compact and robust prototype with high energy efficiency (>80%) to deliver high purity (>99%) H2 at high rate per volume (>0.15 g H 2 /h/cm 3 ) from NH3 decomposition at low temperature (<450 °C) and high conversion (>99%). Our overall technical approach is to effectively combine an active catalyst for NH 3 decomposition with a selective H 2 membrane separation process in a novel, compact modular system to generate high purity H 2 and simultaneously achieve high NH 3 conversion and optimize the entire system energy efficiency. This novel integrated membrane reactor design, together with low-cost, highly active Ru-based catalyst, makes it most appropriate for the project objective. The proposed applied research and development work, therefore, represents an innovative and transformational solution to H 2 generation from thermal catalytic NH 3 decomposition. During the course of our research we i) synthesized and characterized ruthenium(Ru)-based catalysts, evaluated their catalytic performance for NH 3 decomposition and optimized the catalyst composition and performance based on machine learning, ii) prepared SAPO-34, MFI membranes on α-alumina hollow fibers and measured their performance for H 2 /N 2 , H 2 /N 2 /NH 3 separation and evaluated carbon molecular sieve (CMS) and Pd/Ag membranes for H 2 /N 2 , H 2 /N 2 /NH 3 separation at different conditions, iii) designed and evaluated several types of membrane reactors for H 2 production from NH 3 decomposition, and iv) evaluated the H 2 delivery cost base on catalysts development, membrane development and membrane reactor. For 3,1,12 RuYK catalyst, H 2 productivity of 6.35 mmol/min/gcat with NH 3 conversion of 95~98% was achieved at 5 bar and 400 °C; for SAPO-34 membrane, the best membrane showed H 2 permeance of 7.56×10 -7 mol/(m 2 ∙s∙Pa) and H 2 /N 2 selectivity of 23.1 at 20 °C; For CMS and Pd/Ag membranes, both showed superior stability for 71%H 2 /24%N 2 /5%NH 3 mixture separation at 450 °C and 7 bar for over 120 h; for the membrane reactor, high H 2 purity of >99.99% with NH 3 conversion of >99.4% were achieved in Pd/Ag membrane reactor at 450 °C, and the NH 3 concentration was always below 10 ppb in H 2 product. The H 2 generation rate was calculated to be as high as 0.47 g/h/cm 3 and the energy efficiency was calculated to be 88%. The membrane reactor showed superior stability for over 370 h and high H 2 purity, H 2 production rate and NH 3 conversion. Based on calculation, the H 2 delivery cost can be as low as $3.66/kg.

08 HYDROGEN↗
DOE OSTI2023

Biochemical Process Modeling and Simulation (BPMS)

The Biochemical Process Modeling and Simulation project aims to reduce the cost and time of research by applying theory, modeling, and simulation to the most relevant bottlenecks in the biochemical process. We use molecular modeling, quantum mechanics, metabolic modeling, fluid dynamics, and reaction-diffusion methods in close collaboration with pretreatment, hydrolysis, upgrading, and TEA. The project's outcomes are increased yields and efficiency of the biochemical process, added value to products, and reduced price of fuels by specifically targeting catalytic efficiency, reactor design, enzyme efficiency, and microbial design. We work closely with experimental projects to identify problems and iterate with experiments to find and refine solutions. By working with experimentalists, we decide on problems that can be solved with simulation that could otherwise not be solved or would take too long with experiment alone to reach BETO's targets. Over the years, we have produced solutions that have resulted in determining the most likely fatty-acid derivative for passive transport out of bacteria that upgrade biomass, and we have also designed enzyme mutations for enhanced lignin upgrading. Metabolic models have been developed to tune the activity of 2,3 butanediol production for the 2030 target. A computational method to deliver understanding of how complex omics data can be interpreted in the metabolic pathways of organisms used in the Agile Biofoundry. We have found methods to overcome specific barriers and continue to develop those methods. Our reactor studies have guided the design of both the microbes and reactors for aerobic and micro-aerobic production at all scales and have been instrumental in improving the accuracy of techno-economic analysis models. This project is essential in the process of selecting the final processes for 2030 SAF production targets. More specifically, recently, we have: 1) Predicted the strength of the basic structural interactions in commodity plastics to provide guidance for plastics upcycling strategies. 2) Developed computational tool to improve the characterization of lignin-derived compounds 3) Developed new methodologies to enable Machine Learning-based Directed Evolution for protein engineering. 4) Developed Machine Learning methods to predict protein promiscuity and mutations to further improve microbial and enzymatic driven processes and demonstrated the utility of ML approaches to engineering proteins from sparse experimental datasets. 5) Developed new methods to enable high-fidelity simulation of aerobic fermentation at industrial scale and resolving mismatch of time scales through subcycling/operator splitting 7) Identified the difficulty in preventing local high-oxygen conditions in industrial bubble columns, which leads to less-desirable acetoin production, suggesting future research directions in alternative reactor configurations (e.g loop reactors, shallow-channel reactors).

BIOMASS FUELS↗
DOE OSTI2024

Geometry-complete diffusion for 3D molecule generation and optimization

Abstract Generative deep learning methods have recently been proposed for generating 3D molecules using equivariant graph neural networks (GNNs) within a denoising diffusion framework. However, such methods are unable to learn important geometric properties of 3D molecules, as they adopt molecule-agnostic and non-geometric GNNs as their 3D graph denoising networks, which notably hinders their ability to generate valid large 3D molecules. In this work, we address these gaps by introducing the Geometry-Complete Diffusion Model (GCDM) for 3D molecule generation, which outperforms existing 3D molecular diffusion models by significant margins across conditional and unconditional settings for the QM9 dataset and the larger GEOM-Drugs dataset, respectively. Importantly, we demonstrate that GCDM’s generative denoising process enables the model to generate a significant proportion of valid and energetically-stable large molecules at the scale of GEOM-Drugs, whereas previous methods fail to do so with the features they learn. Additionally, we show that extensions of GCDM can not only effectively design 3D molecules for specific protein pockets but can be repurposed to consistently optimize the geometry and chemical composition of existing 3D molecules for molecular stability and property specificity, demonstrating new versatility of molecular diffusion models. Code and data are freely available on GitHub .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗