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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Antigen‐binding fragments with improved crystal lattice packing and enhanced conformational flexibility at the elbow region as crystallization chaperones

It has been shown previously that a set of three modifications—termed S1, Crystal Kappa, and elbow—act synergistically to improve the crystallizability of an antigen-binding fragment (Fab) framework. Here, we prepared a phage-displayed library and performed crystallization screenings to identify additional substitutions—located near the heavy-chain elbow region—which cooperate with the S1, Crystal Kappa, and elbow modifications to increase expression and improve crystallizability of the Fab framework even further. One substitution (K141Q) supports the signature Crystal Kappa-mediated Fab:Fab crystal lattice packing interaction. Another substitution (E172G) improves the compatibility of the elbow modification with the Fab framework by alleviating some of the strain incurred by the shortened and bulkier elbow linker region. A third substitution (F170W) generates a split-Fab conformation, resulting in a powerful crystal lattice packing interaction comprising the biological interaction interface between the variable heavy and light chain domains. In sum, we have used K141Q, E172G, and F170W substitutions—which complement the S1, Crystal Kappa, and elbow modifications—to generate a set of highly crystallizable Fab frameworks that can be used as chaperones to enable facile elucidation of Fab:antigen complex structures by x-ray crystallography.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Using phage display for rational engineering of a higher-affinity humanized 3’ phosphohistidine-specific antibody

Abstract Histidine phosphorylation is a non-canonical post-translational modification (PTM), with 1-phosphohistidine (1-pHis) and 3-phosphohistidine (3-pHis) isoforms, that is understudied due to a lack of robust reagents, including high-affinity pHis-specific antibodies. Engineering pHis antibodies is challenging due to the labile nature of its phosphoramidate (P-N) bond. We developed a strategy for in vitro engineering of antibodies for the detection of native 3-pHis targets, in which the rabbit SC44-8 anti-3-pTza mAb is humanized into a scaffold (hSC44) that is suitable for phage display. Six unique Fab phage-displayed hSC44 scaffold libraries were screened for antibodies that bound 3-pHis with higher affinity and had specificity for 3-pHis versus 3-pTza. hSC44.20N32F L , the best engineered antibody, has ~10-fold higher affinity for 3-pHis than parental hSC44. Eleven new Fab structures, including the first antibody-pHis peptide structures, together with structural and quantum mechanical calculations, provided molecular insights into 3-pHis and 3-pTza discrimination by hSC44.20N32F L and the increased affinity obtained through engineering. We demonstrated the utility of these high-affinity 3-pHis-specific antibodies for the recognition of pHis proteins in mammalian cells by immunoblotting and immunofluorescence staining. Our work describes a general method for engineering labile PTM-specific antibodies and provides novel antibodies for investigating the role of 3-pHis in cell biology.

Martyn, Gregory D.↗
DOE OSTI2020

An ultrapotent synthetic nanobody neutralizes SARS-CoV-2 by stabilizing inactive Spike

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus enters host cells via an interaction between its Spike protein and the host cell receptor angiotensin-converting enzyme 2 (ACE2). By screening a yeast surface-displayed library of synthetic nanobody sequences, we developed nanobodies that disrupt the interaction between Spike and ACE2. Cryo–electron microscopy (cryo-EM) revealed that one nanobody, Nb6, binds Spike in a fully inactive conformation with its receptor binding domains locked into their inaccessible down state, incapable of binding ACE2. Affinity maturation and structure-guided design of multivalency yielded a trivalent nanobody, mNb6-tri, with femtomolar affinity for Spike and picomolar neutralization of SARS-CoV-2 infection. mNb6-tri retains function after aerosolization, lyophilization, and heat treatment, which enables aerosol-mediated delivery of this potent neutralizer directly to the airway epithelia.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Projector Selection for SOFAST Testing

In Concentrating Solar Power (CSP) there is a need for mirrors that are optically accurate, as they are used to focus light onto a receiver at high concentration. To test the accuracy of the mirrors’ optical slopes, we employ a technique called deflectometry. Deflectometry measures mirror slope directly. A projector displays an image onto a screen or wall, and a mirror is positioned to reflect the image to a camera. The camera sees the mirror’s reflection of the screen and sends imaging information to software which analyzes the reflected images from the mirror to determine the local slopes and curvature of the mirror. For this, projectors that can provide a crisp and clear image are imperative. Choosing the right projector(s) can be a long and tedious process; this paper will cover the process we used to select projectors for the SOFAST systems in the Sandia Concentrating Solar Optics Laboratory (CSOL).

14 SOLAR ENERGY↗
DOE OSTI2023

Real-time mixed reality display of dual particle radiation detector data

Radiation source localization and characterization are challenging tasks that currently require complex analyses for interpretation. Mixed reality (MR) technologies are at the verge of wide scale adoption and can assist in the visualization of complex data. Herein, we demonstrate real-time visualization of gamma ray and neutron radiation detector data in MR using the Microsoft HoloLens 2 smart glasses, significantly reducing user interpretation burden. Radiation imaging systems typically use double-scatter events of gamma rays or fast neutrons to reconstruct the incidence directional information, thus enabling source localization. The calculated images and estimated ’hot spots’ are then often displayed in 2D angular space projections on screens. By combining a state-of-the-art dual particle imaging system with HoloLens 2, we propose to display the data directly to the user via the head-mounted MR smart glasses, presenting the directional information as an overlay to the user’s 3D visual experience. We describe an open source implementation using efficient data transfer, image calculation, and 3D engine. We thereby demonstrate for the first time a real-time user experience to display fast neutron or gamma ray images from various radioactive sources set around the detector. We also introduce an alternative source search mode for situations of low event rates using a neural network and simulation based training data to provide a fast estimation of the source’s angular direction. Using MR for radiation detection provides a more intuitive perception of radioactivity and can be applied in routine radiation monitoring, education & training, emergency scenarios, or inspections.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

An exopolysaccharide pathway from a freshwater Sphingomonas isolate

Bacteria embellish their cell envelopes with a variety of specialized polysaccharides. Biosynthesis pathways for these glycans are complex, and final products vary greatly in their chemical structures, physical properties, and biological activities. This tremendous diversity comes from the ability to arrange complex pools of monosaccharide building blocks into polymers with many possible linkage configurations. Due to the complex chemistry of bacterial glycans, very few biosynthetic pathways have been defined in detail. As part of an initiative to characterize novel polysaccharide biosynthesis enzymes, we isolated a bacterium from Lake Michigan called Sphingomonas sp. LM7 that is proficient in exopolysaccharide (EPS) production. We identified genes that contribute to EPS biosynthesis in LM7 by screening a transposon mutant library for colonies displaying altered colony morphology. A gene cluster was identified that appears to encode a complete wzy/wzx-dependent polysaccharide assembly pathway. Deleting individual genes in this cluster caused a non-mucoid phenotype and a corresponding loss of EPS secretion, confirming the role of this gene cluster in polysaccharide production. We extracted EPS from LM7 cultures and determined that it contains a linear chain of 3- and 4-linked glucose, galactose, and glucuronic acid residues. Finally, we show that the EPS pathway in Sphingomonas sp. LM7 diverges from that of sphingan-family EPSs and adhesive polysaccharides such as the holdfast that are present in other Alphaproteobacteria. Our approach of characterizing complete biosynthetic pathways holds promise for engineering polysaccharides with valuable properties.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Static metrology of the meter-scale deformable heliostat

This paper describes a heliostat metrology system which is developed based on deflectometry, utilizing a static perforated panel instead of conventional dynamic monitor displays to provide incident rays. The developed method is named static screen deflectometry (SSD). This robust and scalable method is especially valuable for outdoor tests of large reflectors used in concentrating solar-thermal power (CSP) systems. The developed method has been successfully demonstrated on a 2.4 𝑚 × 3.3 𝑚 float glass deformable reflector bent to focus sunlight at 113 𝑚 distance throughout a day. From images obtained from a camera at 50𝑚 distance, the reflector surface was measured to an accuracy of less than 1 𝑚𝑟𝑎𝑑 rms slope error in the full test scope.

14 SOLAR ENERGY↗
DOE OSTI2025

Web-Based Tools for Data-Informed Remedy Optimization: Software Theory and User Guide

This report documents the development and application of two web-based decision-support tools for pump-and-treat (P&T) groundwater remediation systems: PTOLEMY (Pump-and-Treat Optimized Location Evaluation to Maximize Yields) and OPTIMA (Optimization for Pump-and-Treat Implementation, Management, & Assessment). These tools enhance remedy design and management by leveraging advanced computational methods – specifically deep learning and multi-objective optimization – within a user-friendly platform. By integrating data-driven models with established hydrogeological knowledge, PTOLEMY and OPTIMA enable more efficient evaluation of well placement and operational strategies, helping site managers balance multiple remediation objectives under complex conditions. Both tools are implemented as modules within the SOCRATES (Suite Of Comprehensive Rapid Analysis Tools for Environmental Sites) web platform, which provides data access, visualization, and analytics to support remedy optimization across sites in the U.S. Department of Energy Office of Environmental Management complex. PTOLEMY is a rapid screening module designed to identify promising locations for new extraction wells. It employs a multi-channel three-dimensional convolutional neural network (MC3D-CNN) trained on high-fidelity simulation data to predict the relative performance (in terms of contaminant mass recovery) of potential well sites. Through an interactive web interface, PTOLEMY visualizes the probability of high performance across a site, highlighting areas where an extraction well is likely to yield above-threshold contaminant removal over a multi-year period. PTOLEMY’s map-based displays and exportable results support transparent communication of screening analyses. By focusing attention on the most favorable candidate locations, the tool augments traditional engineering judgment and physics-based modeling, providing a data informed basis for subsequent detailed evaluations. OPTIMA is a multi objective optimization module designed to find wellfield layouts and operating schedules that meet various cleanup goals. It quickly evaluates thousands of candidate setups – combinations of well locations, timing, and rates – and returns a small set of best trade-off options for comparison. At its core, OPTIMA uses a U-Net-based surrogate model – a deep-learning emulator of a groundwater flow and transport simulator – to dramatically accelerate scenario evaluations. Coupling this fast surrogate with the NSGA-II (Non-dominated Sorting Genetic Algorithm II) evolutionary algorithm, OPTIMA explores a wide decision space of well locations and schedules to identify Pareto-optimal solutions that trade off key objectives (e.g., minimizing cleanup time, maximizing contaminant mass removal, and minimizing plume extent). The tool outputs a family of optimal configurations and visualizes their trade-offs (Pareto frontiers of cleanup metrics and maps of optimized well placements). Site managers can use these results to understand the range of viable strategies and to select candidate designs for more detailed verification. OPTIMA is currently under active development and not yet fully released; this guide provides early documentation to support planning and gather user feedback.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Remote operation of the DIII-D National Fusion Facility

Abstract Full remote scientific operation of the DIII-D National Fusion Facility is now possible through significant advances in the computer science hardware and software infrastructure made over the last decade. Capabilities around information visualization, data movement, and communication have all been enhanced. The level of capability deployed to remotely operate DIII-D required an infrastructure advancement over what had previously been achieved in the fusion community. The large quantity of real-time data that is automatically displayed on DIII-D’s control room screens can now be visualized by remote participants via web-based applications. New audio/video solutions using the VoIP and instant messaging application Discord have been implemented to mimic the dynamic and ad-hoc scientific conversations that are critical in successfully operating an experimental campaign. Discord’s ability for a user to rapidly move between audio channels, text with images, and share screens is a significant enhancement over traditional videoconferencing tools. In addition, multiple combinations of broadcast audio are made available via a web-based application to allow remote participants to simultaneously listen to general announcements/sounds while conducting their own specific conversations. Secure methodologies have been put into place to allow remote control of hardware including DIII-D’s plasma control system application. Secure methods also included the ability of the on-site team to closely coordinate their work with remote team members which has been enhanced through extensions to the wireless network and the use of tablet computers for audio/video/screen sharing. However, no amount of software can fully replace the need for ‘hands on hardware.’ This infrastructure was severely stress tested during the COVID-19 pandemic where occupancy of the DIII-D control room was restricted. Operational efficiency during the pandemic, measured in discharges per hour, remained high (3.8 ± 0.8) compared to values obtained pre-pandemic (3.7 ± 0.8).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Nanobody screening and machine learning guided identification of cross-variant anti-SARS-CoV-2 neutralizing heavy-chain only antibodies

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) continues to persist, demonstrating the risks posed by emerging infectious diseases to national security, public health, and the economy. Development of new vaccines and antibodies for emerging viral threats requires substantial resources and time, and traditional development platforms for vaccines and antibodies are often too slow to combat continuously evolving immunological escape variants, reducing their efficacy over time. Previously, we designed a next-generation synthetic humanized nanobody (Nb) phage display library and demonstrated that this library could be used to rapidly identify highly specific and potent neutralizing heavy chain-only antibodies (HCAbs) with prophylactic and therapeutic efficacy in vivo against the original SARS-CoV-2. In this study, we used a combination of high throughput screening and machine learning (ML) models to identify HCAbs with potent efficacy against SARS-CoV-2 viral variants of interest (VOIs) and concern (VOCs). To start, we screened our highly diverse Nb phage display library against several pre-Omicron VOI and VOC receptor binding domains (RBDs) to identify panels of cross-reactive HCAbs. Using HCAb affinity for SARS-CoV-2 VOI and VOCs (pre-Omicron variants) and model features from other published data, we were able to develop a ML model that successfully identified HCAbs with efficacy against Omicron variants, independent of our experimental biopanning workflow. This biopanning informed ML approach reduced the experimental screening burden by 78% to 90% for the Omicron BA.5 and Omicron BA.1 variants, respectively. The combined approach can be applied to other emerging viruses with pandemic potential to rapidly identify effective therapeutic antibodies against emerging variants.

Antibodies↗
DOE OSTI2021

Data-Driven Strategies for Accelerated Materials Design

The ongoing revolution of the natural sciences by the advent of machine learning and artificial intelligence sparked significant interest in the material science community in recent years. The intrinsically high dimensionality of the space of realizable materials makes traditional approaches ineffective for large-scale explorations. Modern data science and machine learning tools developed for increasingly complicated problems are an attractive alternative. An imminent climate catastrophe calls for a clean energy transformation by overhauling current technologies within only several years of possible action available. Tackling this crisis requires the development of new materials at an unprecedented pace and scale. For example, organic photovoltaics have the potential to replace existing silicon-based materials to a large extent and open up new fields of application. In recent years, organic light-emitting diodes have emerged as state-of-the-art technology for digital screens and portable devices and are enabling new applications with flexible displays. Reticular frameworks allow the atom-precise synthesis of nanomaterials and promise to revolutionize the field by the potential to realize multifunctional nanoparticles with applications from gas storage, gas separation, and electrochemical energy storage to nanomedicine. In the recent decade, significant advances in all these fields have been facilitated by the comprehensive application of simulation and machine learning for property prediction, property optimization, and chemical space exploration enabled by considerable advances in computing power and algorithmic efficiency. In this Account, we review the most recent contributions of our group in this thriving field of machine learning for material science. We start with a summary of the most important material classes our group has been involved in, focusing on small molecules as organic electronic materials and crystalline materials. Specifically, we highlight the data-driven approaches we employed to speed up discovery and derive material design strategies. Subsequently, our focus lies on the data-driven methodologies our group has developed and employed, elaborating on high-throughput virtual screening, inverse molecular design, Bayesian optimization, and supervised learning. We discuss the general ideas, their working principles, and their use cases with examples of successful implementations in data-driven material discovery and design efforts. Furthermore, we elaborate on potential pitfalls and remaining challenges of these methods. Finally, we provide a brief outlook for the field as we foresee increasing adaptation and implementation of large scale data-driven approaches in material discovery and design campaigns.

36 MATERIALS SCIENCE↗
DOE OSTI2024

CO2 response screen in grass Brachypodium reveals the key role of a MAP kinase in CO2-triggered stomatal closure

Abstract Plants respond to increased CO2 concentrations through stomatal closure, which can contribute to increased water use efficiency. Grasses display faster stomatal responses than eudicots due to dumbbell-shaped guard cells flanked by subsidiary cells working in opposition. However, forward genetic screening for stomatal CO2 signal transduction mutants in grasses has yet to be reported. The grass model Brachypodium distachyon is closely related to agronomically important cereal crops, sharing largely collinear genomes. To gain insights into CO2 control mechanisms of stomatal movements in grasses, we developed an unbiased forward genetic screen with an EMS-mutagenized B. distachyon M5 generation population using infrared imaging to identify plants with altered leaf temperatures at elevated CO2. Among isolated mutants, a “chill1” mutant exhibited cooler leaf temperatures than wild-type Bd21-3 parent control plants after exposure to increased CO2. chill1 plants showed strongly impaired high CO2-induced stomatal closure despite retaining a robust abscisic acid-induced stomatal closing response. Through bulked segregant whole-genome sequencing analyses followed by analyses of further backcrossed F4 generation plants and generation and characterization of sodium azide and CRISPR-cas9 mutants, chill1 was mapped to a protein kinase, Mitogen-Activated Protein Kinase 5 (BdMPK5). The chill1 mutation impaired BdMPK5 protein-mediated CO2/HCO3− sensing together with the High Temperature 1 (HT1) Raf-like kinase in vitro. Furthermore, AlphaFold2-directed structural modeling predicted that the identified BdMPK5-D90N chill1 mutant residue is located at the interface of BdMPK5 with the BdHT1 Raf-like kinase. BdMPK5 is a key signaling component that mediates CO2-induced stomatal movements and is proposed to function as a component of the primary CO2 sensor in grasses.

Lopez, Bryn N. K. (ORCID:0009000937288216)↗
DOE OSTI2026

Organic superbases in Lewis pair catalyzed hydrogenations of imines

Organic superbases have recently emerged as powerful components in metal-free catalytic systems, yet their role in frustrated Lewis pair (FLP) catalyzed hydrogenation reactions remain underexplored. In this article, we investigate the diphosphazene superbases P 2 - t Bu (1) and P 2 -Et (2) as base components combined with electronically tunable boranes of formula 9-(X n -C 6 H 5-n )BBN, where X n = 4-NMe₂, 4-OMe, 4-Me, 4-H, 4-F, 4-OCF 3 , 4-CF 3 , 3,5-(CF3), in FLP-catalyzed hydrogenations of imines. While the more sterically encumbered base 1 forms persistent FLPs whose activity correlates with the hydride affinity of the borane, less hindered base 2 generates Lewis acid–base adducts and displays superior catalytic performance, especially with boranes of lower hydride affinity. A systematic screening identified the adduct 2/9-(4-MeO-C 6 H 4 )BBN as the most active catalytic system, achieving quantitative hydrogenation of N-benzylidene aniline at 80 °C and H 2 pressures as low as 40 bar in THF. Multinuclear NMR spectroscopic studies and DFT calculations support a mechanistic scenario in which reversible adduct formation and subsequent dissociation to the free acid–base pair precede heterolytic H₂ cleavage, with adduct stability and borane electrophilicity concurrently dictating catalytic activity. Under optimized conditions, the most active catalyst system, 2/9-(4-MeO-C 6 H 4 )BBN, hydrogenates a broad range of aldimines, including electron-rich 4-NMe₂ and push-pull substrates, mono- and bis-ortho-substituted imines, and selected heteroaryl imines, with excellent yields and selectivity. Collectively, these findings establish design principles for tuning BBN-derived FLP systems and expand the scope of metal-free hydrogenation catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Screening the complex biological behavior of late lanthanides through genome-wide interactions

Abstract Despite their similar physicochemical properties, recent studies have demonstrated that lanthanides can display different biological behaviors. Hence, the lanthanide series can be divided into three parts, namely early, mid, and late lanthanides, based on their interactions with biological systems. In particular, the late lanthanides demonstrate distinct, but poorly understood biological activity. In the current study, we employed genome-wide functional screening to help understand biological effects of exposure to Yb(III) and Lu(III), which were selected as representatives of the late lanthanides. As a model organism, we used Saccharomyces cerevisiae, since it shares many biological functions with humans. Analysis of the functional screening results indicated toxicity of late lanthanides is consistent with disruption of vesicle-mediated transport, and further supported a role for calcium transport processes and mitophagy in mitigating toxicity. Unexpectedly, our analysis suggested that late lanthanides target proteins with SH3 domains, which may underlie the observed toxicity. This study provides fundamental insights into the unique biological chemistry of late lanthanides, which may help devise new avenues toward the development of decorporation strategies and bio-inspired separation processes.

Pallares, Roger M. (ORCID:0000000174238706)↗
DOE OSTI2025

Combining computational modeling and experimental library screening to affinity-mature VEEV-neutralizing antibody F5

Engineered monoclonal antibodies have proven to be highly effective therapeutics in recent viral outbreaks. However, despite technical advancements, an ability to rapidly adapt or increase antibody affinity and by extension, therapeutic efficacy, has yet to be fully realized. We endeavored to stand-up such a pipeline using molecular modeling combined with experimental library screening to increase the affinity of F5, a monoclonal antibody with potent neutralizing activity against Venezuelan Equine Encephalitis Virus (VEEV), to recombinant VEEV (IAB) E1E2 antigen. We modeled the F5/E1E2 binding interface and generated predictions for mutations to improve binding using a Rosetta-based approach and dTERMen, an informatics approach. The modeling was complicated by the fact that a high-resolution structure of F5 is not available and the H3 loop of F5 exceeds the length for which current modeling approaches can determine a unique structure. A subset of the predicted mutations from both methods were incorporated into a phage display library of scFvs. This library and a library generated by error-prone PCR were screened for binding affinity to the recombinant antigen. Results from the screens identified favorable mutations which were incorporated into 12 human-IgG1 variants. The best variant, containing eight mutations, improved KD from 0.63 nM (parental) to 0.01 nM. While this did not improve neutralization or therapeutic potency of F5 against IAB, it did increase cross-reactivity to other closely related VEEV epizootic and enzootic strains, demonstrating the potential of this method to rapidly adapt existing therapeutics to emerging viral strains.

affinity-maturation↗
DOE OSTI2022

Fracture properties of high-entropy alloys

Abstract Since the concept of high-entropy alloys (HEAs) as materials with at least four or five principal elements in (near)-equiatomic composition was introduced in 2004, this new class of materials has penetrated essentially all materials science-related fields. The main reason for this is that some face-centered-cubic alloy compositions have been shown to exhibit truly outstanding mechanical properties with extraordinary combinations of strength, ductility, and fracture toughness, particularly at cryogenic temperatures, whereas certain body-centered-cubic refractory compositions display remarkable high-temperature strength. While significant efforts have been put into rapid screening and narrowing the compositional space of HEAs to a manageable scope, there are still only a few metallic alloys that push the limits of mechanical performance. Here, we review work on some of the most damage-tolerant HEAs discovered to date and discuss the fundamental reasons why their resistance to fracture and subsequent stable crack growth is so exceptional. Graphical abstract

Gludovatz, Bernd (ORCID:0000000224203879)↗
DOE OSTI2023

Discovery of multi-functional polyimides through high-throughput screening using explainable machine learning

Polyimides have been widely used in modern industries because of their excellent mechanical and thermal properties, e.g., high-temperature fuel cells, displays, and aerospace composites. However, it usually takes decades of experimental efforts to develop a successful product. Aiming to expedite the discovery of high-performance polyimides, we utilize computational methods of machine learning (ML) and molecular dynamics (MD) simulations. Our study provides compelling evidence for the effectiveness of a data-driven approach in discovering novel polyimides. We first build a comprehensive library of more than 8 million hypothetical polyimides based on the polycondensation of existing dianhydride and diamine/diisocyanate molecules. Then we establish multiple ML models for the thermal and mechanical properties of polyimides based on their experimentally reported values, including glass transition temperature, Young’s modulus, and tensile yield strength. The obtained ML models demonstrate excellent predictive performance in identifying the key chemical substructures influencing the thermal and mechanical properties of polyimides. The use of explainable machine learning describes the effect of chemical substructures on individual properties, from which human experts can understand the cause of the ML model decision. Applying the well-trained ML models, we obtain property predictions of the 8 million hypothetical polyimides. Then, we screen the whole hypothetical dataset and identify three (3) best-performing novel polyimides that have better-combined properties than existing ones through Pareto frontier analysis. For an easy query of the discovered high-performing polyimides, we also create an online platform https://polyimide-explorer.herokuapp.com/ that embeds the developed ML model with interactive visualization. Furthermore, we validate the ML predictions through all-atom MD simulations and examine their synthesizability. The MD simulations are in good agreement with the ML predictions and the three novel polyimides are predicted to be easy to synthesize via Schuffenhauer’s synthetic accessibility score. Following the proposed ML guidance, we successfully synthesized a novel polyimide and the experimentally obtained high glass transition/thermal decomposition temperature demonstrated its excellent thermal stability. Here our study demonstrates an efficient way to expedite the discovery of novel polymers using ML prediction and MD validation. The high-throughput screening of a large computational dataset can serve as a general approach for new material discovery in other polymeric material exploration problems, such as organic photovoltaics, polymer membranes, and dielectrics.

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

Metabolomic Profiling of Wild-type and Mutant Soybean Root Nodules Using Laser-ablation Electrospray Ionization Mass Spectrometry Reveals Altered Metabolism

The establishment of the nitrogen-fixing symbiosis between soybean and Bradyrhizobium japonicum is complex. In order to document the changes in plant metabolism due to the symbiosis, we utilized laser ablation electrospray ionization mass spectrometry (LAESI-MS) for in situ metabolic profiling of wild-type nodules, nodules infected with a B. japonicum nifH mutant unable to fix nitrogen, nodules doubly infected by both strains, and nodules formed on plants mutated in the stearoyl-acyl carrier protein desaturase (sacpd-c) gene, which were previously shown to have altered nodule ultrastructure. Results showed that the relative abundance of fatty acids, purines, and lipids was significantly changed in response to the symbiosis. The nifH mutant nodules had elevated levels of jasmonic acid (JA), correlating with signs of nitrogen deprivation. Nodules resulting from the mixed inoculant displayed similar, overlapping metabolic distributions within the sectors of effective (fix+) and ineffective (nifH mutant, fix-) endosymbionts. These data are inconsistent with the notion that plant sanctioning is cell autonomous. Nodules lacking sacpd-c displayed an elevation of soyasaponins and organic acids in the central necrotic regions. This study demonstrates the utility of LAESI-MS for high-throughput screening of plant phenotypes. Overall, nodules disrupted in the symbiosis were elevated in metabolites related to plant defense.

Agtuca, Beverly J.↗