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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 91 records · Page 5

Exploration of structure-activity relationships for the SARS-CoV-2 macrodomain from shape-based fragment linking and active learning

The macrodomain of severe acute respiratory syndrome coronavirus 2 nonstructural protein 3 is required for viral pathogenesis and is an emerging antiviral target. We previously performed an x-ray crystallography–based fragment screen and found submicromolar inhibitors by fragment linking. However, these compounds had poor membrane permeability and liabilities that complicated optimization. Here, we developed a shape-based virtual screening pipeline—FrankenROCS. We screened the Enamine high-throughput collection of 2.1 million compounds, selecting 39 compounds for testing, with the most potent binding with a 130 μM median inhibitory concentration (IC 50 ). We then paired FrankenROCS with an active learning algorithm (Thompson sampling) to efficiently search the Enamine REAL database of 22 billion molecules, testing 32 compounds with the most potent binding with a 220 μM IC 50 . Further optimization led to analogs with IC 50 values better than 10 μM. This lead series has improved membrane permeability and is poised for optimization. FrankenROCS is a scalable method for fragment linking to exploit synthesis-on-demand libraries.

Science & Technology - Other Topics↗

Expanding Parameter Space to Enable Low-Temperature Synthesis of Crystalline Indium Phosphide Quantum Dots

Established methods to synthesize indium phosphide quantum dots (QDs) require high temperatures (>180 °C) to make high-quality material for optoelectronic applications. Nonpolar solvent environments are overwhelmingly used in InP QD synthesis to reach the necessary high temperatures and for compatibility with the reactive precursors. In this study, we explored InP QD synthesis in polar aprotic solvent environments to dramatically decrease the temperature required for InP crystallization by imparting ionicity to the precursors and stabilizing charged reaction intermediates. A custom air-free 96- well plate setup was employed to identify key factors impacting low-temperature QD formation, including an increased percentage of polar solvent, carboxylic acid choice, and inclusion of polar additives. Guided by these insights, we developed a synthesis of crystalline, green-emitting InP QDs at 60 °C in a toluene-dimethylformamide mixture. Here's, the QDs withstood established Zn 2+ and HF surface treatments, which increased the photoluminescence quantum yield to 25%. Additionally, we demonstrated the rapid synthesis of quasi-wurtzite InP QDs at room temperature in a polar solvent environment using an acid-free indium myristate precursor.

absorption↗

A substitutional quantum defect in WS2 discovered by high-throughput computational screening and fabricated by site-selective STM manipulation

Abstract Point defects in two-dimensional materials are of key interest for quantum information science. However, the parameter space of possible defects is immense, making the identification of high-performance quantum defects very challenging. Here, we perform high-throughput (HT) first-principles computational screening to search for promising quantum defects within WS 2 , which present localized levels in the band gap that can lead to bright optical transitions in the visible or telecom regime. Our computed database spans more than 700 charged defects formed through substitution on the tungsten or sulfur site. We found that sulfur substitutions enable the most promising quantum defects. We computationally identify the neutral cobalt substitution to sulfur ( $${\rm{Co}}_{{{{{{{{\rm{S}}}}}}}}}^{0}$$ Co S 0 ) and fabricate it with scanning tunneling microscopy (STM). The $${\rm{Co}}_{{{{{{{{\rm{S}}}}}}}}}^{0}$$ Co S 0 electronic structure measured by STM agrees with first principles and showcases an attractive quantum defect. Our work shows how HT computational screening and nanoscale synthesis routes can be combined to design promising quantum defects.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Structure prediction of porous organic crystals

In this work, we explore the possibility of applying automated crystal structure prediction to reproduce the experimentally identified metastable porous polymorphs. Using our recently developed High-Throughput Organic Crystal Structure Prediction ( HTOCSP ) framework, we conducted a systematic study on five representative organic crystalline systems including hydrogen-bonded frameworks (HOFs), featured by the presence of significant porosity, in conjunction with different choices of energy models from classical, machine learning force fields, tight binding to density functional theory. Our results suggest that the current structure generation framework, with careful selection of symmetry conditions, is likely to generate rather complex and abundant metastable crystal candidates for porous crystals. In conjunction with the recent advance in universal machine learning force fields, it becomes possible to identify experimental structures as the energetically favorable candidates from a simple energy versus density analysis, thus paving the way for computational design of complex porous materials with the target systems prior to the experimental synthesis and characterization.

36 MATERIALS SCIENCE↗

Novel Chalcopyrites for Advanced Photoelectrochemical Water Splitting

With the support of DoE’s EERE office, our team has established a unique tool-chest of capabilities, including theoretical modeling (Lawrence Livermore National Laboratory: LLNL), state-of-the-art synthesis (Hawaii Natural Energy Institute: HNEI, Stanford, and the National Renewable Energy Laboratory: NREL) and advanced materials and interfaces characterization (University of Nevada, Las Vegas: UNLV, and Lawrence Berkeley National Laboratory: LBNL), to accelerate the development of high efficiency and durable chalcopyrite materials for advanced photoelectrochemical (PEC) water splitting. Using this synergistic approach, we have successfully created new wide bandgap chalcopyrite photocathodes generating over 10 mA/cm 2 , developed innovative strategies to protect them from corrosion, and engineered novel integration methods to circumvent thin film materials mechanical, chemical and thermal incompatibility. In Task 1 “Modeling and synthesis of chalcopyrite photocathodes”, we expanded our library of wide bandgap chalcopyrites for PEC water splitting. With support from LLNL’s “Computational Materials Diagnostics and Optimization of PEC Devices”, LBNL’s “photophysical” and NREL’s “I-III-VI Compound Semiconductors for Water-Splitting” nodes, we investigated two new chalcopyrite candidates for PEC water splitting: Cu(In,Al)Se 2 and Cu(In,B)Se 2 . We also further developed ordered vacancy compounds, such as CuGa 3 Se 5 , with unprecedented durability during PEC waters splitting in acidic solutions. In Task 2 “Interfaces engineering for enhanced efficiency and durability”, we addressed both the non-ideal band-edge positions of chalcopyrites with respect to water redox potentials, as well as their chemical instability under PEC water splitting, with a buried-junctions approach. With help from NREL’s “High-Throughput Experimental Thin Film Combinatorial Capabilities” and “Corrosion Analysis of Materials” nodes, we engineered environmentally friendly n-type buffers, including Mn x Zn 1-x O, to adjust the chalcopyrite band-edge positions and achieved photovoltages as high as 925 mV. Also, we integrated non-precious catalytic-protecting layers, such as WO 3 , to enhance the water splitting long-term stability of chalcopyrite absorbers. Finally, in Task 3 “Hybrid photoelectrode device integration”, we proposed an innovative method to bond wide bandgap photocathodes onto narrow bandgap PV drivers at room temperature using conductive polymers. Our semi-monolithic approach addressed fundamental processing incompatibility issues, as both the photocathode and the PV driver are processed separately. Proof-of-concept whole-chalcopyrite tandems were obtained by consecutive exfoliation and transfer of fully integrated 1.85 eV CuGa 3 Se 5 and 1.13 eV CuInGaSe 2 stacks from their Mo/SLG substrates onto a new single FTO host substrate.

08 HYDROGEN↗

Optimizing Cell-based Antimicrobials through Pooled Genomic Libraries

DNA synthesis and assembly technologies ushered in through synthetic biology have great promise for biomanufacturing, bioremediation, and the development of living therapeutics. Unfortunately, predicting sequence to function relationships, including for biosynthetic pathways expressed in a new host organism, is difficult and often requires many iterative cycles of design, construction, and testing. We are working to develop data-driven approaches to identify the genetic determinants of growth defects and productivity for the expression of a cell-based antimicrobial. We assayed the growth, pigment production, and antimicrobial activity of a collection of over 10,000 genetic mutants of the violacein biosynthetic pathway and sequenced the genetic variation of these mutants. Through this project, we have developed an innovative codebase to automate the determination of pigmentation and antimicrobial clearing diameter for tens of thousands of genetic mutants cultivated on agar dishes. Further, we have written DNA sequence analysis code to demultiplex & provide consensus sequences from high-throughput PacBio long-read circular consensus sequencing (CCS) datasets. From this foundation, we plan to map DNA sequence to function to predict an optimal genetic design to maximize antimicrobial activity while minimizing deleterious growth effects. The workflows and algorithms developed through this project can be broadly applied to other engineered functions in microbes, uncovering sequence to function relationships for complex phenotypes where function impacts fitness.

59 BASIC BIOLOGICAL SCIENCES↗

Predictions of delafossite-hosted honeycomb and kagome phases

Delafossites, typically denoted by the formula ABO 2 , are a class of layered materials that exhibit a wide range of electronic and optical properties. Recently, the idea of modifying these delafossites into ordered kagome or honeycomb phases via strategic doping has emerged as a potential way to tailor these properties. In this study, we use high-throughput density functional theory calculations to explore many possible candidate kagome and honeycomb phases by considering dopants selected from the parent compounds of known ternary delafossite oxides from the inorganic crystal structure database. Here our results indicate that while A-site in existing delafossites can host a limited range of elemental specifies, and display a low propensity for mixing or ordering, the oxide sub-units in the BO 2 much more readily admit guest species. Our study identifies four candidate B-site kagome and fifteen candidate B-site honeycombs with a formation energy more than 50 meV f.u. −1 below other competing phases. The ability to predict and control the formation of these unique structures offers exciting opportunities in materials design, where innovative properties can be engineered through the selection of specific dopants. A number of these constitute novel correlated metals, which may be of interest for subsequent efforts in synthesis. These novel correlated metals may have significant implications for quantum computing, spintronics, and high-temperature superconductivity, thus inspiring future experimental synthesis and characterization of these proposed materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

FPGA-accelerated SpeckleNN with SNL for real-time X-ray single-particle imaging

We present the implementation of a specialized version of our previously published unified embedding model, SpeckleNN, for real-time speckle pattern classification in X-ray Single-Particle Imaging (SPI), using the SLAC Neural Network Library (SNL) on an FPGA platform. This hardware realization transitions SpeckleNN from a prototypic model into a practical edge solution, optimized for running inference near the detector in high-throughput X-ray free-electron laser (XFEL) facilities, such as those found at the Linac Coherent Light Source (LCLS). To address the resource constraints inherent in FPGAs, we developed a more specialized version of SpeckleNN. The original model, which was designed for broader classification across multiple biological samples, comprised ~5.6 million parameters. The new implementation, while reducing the parameter count to 64.6K (a 98.8% reduction), focuses on maintaining the model's essential functionality for real-time operation, achieving an accuracy of 90%. Furthermore, we compressed the latent space from 128 to 50 dimensions. This implementation was demonstrated on the KCU1500 FPGA board, utilizing 71% of available DSPs, 75% of LUTs, and 48% of FFs, with an average power consumption of 9.4W according to the Vivado post-implementation report. The FPGA performed inference on a single image with a latency of 45.015 microseconds at a 200 MHz clock rate. In comparison, running the same inference on an NVIDIA A100 GPU resulted in an average power consumption of ~73W and an image processing latency of around 400 microseconds. Our FPGA-accelerated version of SpeckleNN demonstrated significant improvements, achieving an 8.9 × speedup and a 7.8 × reduction in power consumption compared to the GPU implementation. Key advancements include model specialization and dynamic weight loading through SNL, which eliminates the need for time-consuming FPGA design re-synthesis, allowing fast and continuous deployment of models (re)trained online. These innovations enable real-time adaptive classification and efficient vetoing of speckle patterns, making SpeckleNN more suited for deployment in XFEL facilities. This implementation has the potential to significantly accelerate SPI experiments and enhance adaptability to evolving experimental conditions.

47 OTHER INSTRUMENTATION↗

High-throughput manufacturing of epitaxial membranes from a single wafer by 2D materials-based layer transfer process

Layer transfer techniques have been extensively explored for semiconductor device fabrication as a path to reduce costs and to form heterogeneously integrated devices. These techniques entail isolating epitaxial layers from an expensive donor wafer to form freestanding membranes. However, current layer transfer processes are still low-throughput and too expensive to be commercially suitable. Here we report a high-throughput layer transfer technique that can produce multiple compound semiconductor membranes from a single wafer. We directly grow two-dimensional (2D) materials on III–N and III–V substrates using epitaxy tools, which enables a scheme comprised of multiple alternating layers of 2D materials and epilayers that can be formed by a single growth run. Each epilayer in the multistack structure is then harvested by layer-by-layer mechanical exfoliation, producing multiple freestanding membranes from a single wafer without involving time-consuming processes such as sacrificial layer etching or wafer polishing. Moreover, atomic-precision exfoliation at the 2D interface allows for the recycling of the wafers for subsequent membrane production, with the potential for greatly reducing the manufacturing cost.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Design-driven optimization of low-cost reagent formulations for reproducible and high-yielding cell-free gene expression

Access to recombinant proteins is vital in basic science and biotechnology research. Cell-free gene expression systems provide one approach to address this need, but widespread utilization remains limited by the cost, complexity, and inconsistency of current platforms. To address these limitations, we carry out a multi-dimensional definitive screening design to reduce the number of reagent components and remove costly secondary energy substrates. From 1,231 different reagent formulations, we discover a simple and reproducible system based on 12 components. The optimized reagent formulation can produce 2.4 ± 0.3 g/L of protein product at the 15-µL scale (~$\$60$/gprotein) and 3.7 ± 0.2 g/L (~$\$39$/gprotein) at the 4-mL scale with oxygen supplementation. This provides an average 95% reduction in cost over previous cell-free reagent formulations. We further show that the optimized reagent formulation can produce nucleoside triphosphates from nitrogenous bases and ribose and that it is robust to failure across batches of cell lysates, users/locations, and in the synthesis of more than 20 different proteins. For example, we demonstrate the production of fifteen therapeutically relevant products, including full-length aglycosylated monoclonal antibodies. We anticipate that our optimized reagent formulation will democratize the use of cell-free systems for protein manufacturing and synthetic biology applications.

Biologics↗

Non‐Equilibrium Synthesis Methods to Create Metastable and High‐Entropy Nanomaterials

Stabilizing multiple elements within a single phase enables the creation of advanced materials with exceptional properties arising from their complex composition. However, under equilibrium conditions, the Hume–Rothery rules impose strict limitations on solid-state miscibility, restricting combinations of elements with mismatched crystal structures, atomic radii, valence states, or electronegativities. This severely narrows the accessible compositional space for creating new inorganic materials. In this review, we highlight how non-equilibrium synthesis methods, featuring ultrafast heating and quenching, can overcome these thermodynamic barriers, enabling integration of immiscible elements into metastable and high-entropy nanostructures. The resulting materials benefit from both kinetic trapping and stabilization by high configurational entropy, leading to enhanced phase stability. These materials can exhibit unique structural and functional properties that are needed for advancing catalysis, energy storage, thermoelectrics, and sensing. Furthermore, the ability of non-equilibrium methods to generate unconventional compositions and structures expands the material design space dramatically, offering rich datasets for AI-guided materials discovery. When combined with their inherent high-throughput and scalable characteristics, these approaches enable rapid, iterative optimization and accelerate the development and industrial production of next-generation inorganic materials.

high-entropy materials↗

Bioelectrochemical crossbar architecture screening platform for extracellular electron transfer

Electroactive microbes can serve as living components in bioelectronic devices, where their unique ability to transfer electrons enables applications in sensing, energy conversion, and synthesis, but they remain challenging to engineer because the bioelectrochemical systems (BESs) used for characterization are low throughput. Here, we present a bioelectrochemical crossbar architecture screening platform (BiCASP) that uses stacked and orthogonally arrayed electrodes to enable individual sample selection for characterization in arrayed formats. This device reports on the current generated by electroactive bacteria on the minute timescale, decreasing the time for data acquisition by several orders of magnitude compared to conventional BESs. This device increases the throughput of screening engineered biological components in cells, identifying mutants of the membrane protein wire MtrA in Shewanella oneidensis that retain the ability to support extracellular electron transfer (EET). BiCASP may be integrated with bioelectronics that need directed evolution of electroactive proteins.

Shewanella↗

Re-directing mixed-feed deconstruction products to hybrid polyesters: Tolerance windows for commodity plastics reconstruction

Solvolysis is a promising strategy for mixed-feed polyester recycling, but little attention has been given to downstream product separations or the impact of using imperfectly separated monomer mixtures in recycled polymer reconstruction. Here, we challenge the traditional need for high-purity monomers in polycondensation synthesis of engineering thermoplastics. Monomer mixtures are derived from catalyzed methanolysis of polyethylene terephthalate (PET), polybutylene terephthalate (PBT), and polybutylene adipate-co-terephthalate (PBAT), with separation scenarios ranging from high (99:1) to low (90:10) purity. We focus on challenging-to-separate products like ethylene glycol and 1,4-butanediol and evaluate tolerance for comonomer incorporation in recycled hybrid polyesters: polybutylene-co-ethylene terephthalate (PBET) and polybutylene ethylene adipate-co-terephthalate (PBEAT). Evaluations are made between “contaminant” monomer incorporation, and the resulting materials’ thermal properties, crystalline structure, tensile toughness, and rheology. Ultimately, we highlight that despite incorporation of contaminant monomer, high-performance hybrid polyesters of PET, PBT, and PBAT are obtained while reducing the strain of high-throughput separations.

36 MATERIALS SCIENCE↗

Synthetic Accessibility and Sodium Ion Conductivity of the Na8–x A x P2O9 (NAP) High-Temperature Sodium Superionic Conductor Framework

Advancement of solid-state electrolytes (SSEs) for all solid-state batteries typically focuses on modification of a known structural framework to improve conductivity, e.g., cation substitution for an immobile ion or varying the concentration of the mobile ions. Novel frameworks can be disruptive by enabling fast ion conduction aided by different structure and diffusion mechanisms, thereby unlocking optimal conductors with different properties. Herein, we perform a high-throughput survey of a structural framework for sodium ion conduction, Na8–x A x P2O9 (NAP), to understand the family’s thermodynamic stability, synthesizability, and ionic conduction. We show that the parent phase Na4TiP2O9 (NTP) undergoes a structural distortion (with accompanying conductivity transition) due to unstable phonons arising from pseudo-Jahn–Teller mode in the 1D titanium chains. Screening compounds in which Ti is substituted by other metals computationally reveal a number of candidates that are predicted to be low in formation energy and have high predicted ionic conductivities. High-throughput experimental and subsequent methodology optimization trials deliver one new compound, Na4SnP2O9 (NSP). X-ray diffraction (XRD), microscopy, and spectroscopy characterization indicate that the room-temperature structure of NSP is similar to the high-temperature, orthorhombic NTP phase but with some small unresolved structural differences. These uncharacterized structural details are speculated to limit the ion conductivity. Temperature-dependent XRD and electrochemical impedance spectroscopy indicate multiple coupled conductivity–structure transitions at a high temperature. We demonstrate the challenges with synthesis development and a priori identification of promising SSE phases as a major bottleneck in new (energy) materials development.

Chemical reactions↗

Crystal Orientation and Defect Mapping in Electron-Beam-Sensitive Zeolites with Near-Axis Transmission Kikuchi Diffraction

Porous materials are vital in catalysis, energy conversion, and environmental remediation. Understanding structural heterogeneity in zeolites is key to linking synthesis, framework intergrowths, and catalytic performance, yet current methods for phase identification and spatial mapping lack sufficient resolution or throughput. We present a high-throughput approach using near-axis transmission Kikuchi diffraction in a scanning electron microscope, achieving high phase and spatial resolution for electron-beam-sensitive zeolites, including ZSM-5 and, for the first time, Zeolite A. Here, this method enables direct visualization of intergrowth features that critically affect catalytic and adsorption behavior, bridging the gap between ensemble-averaged X-ray diffraction and high-resolution but low-throughput transmission electron microscopy. Combining nanoscale mapping with statistical sampling is highly suited for machine-learning pipelines guiding new structure function understanding and could be extended to other beam-sensitive porous materials such as metal–organic or covalent–organic frameworks.

crystallography↗

Biocatalytic Synthesis of α-Amino Esters via Nitrene C–H Insertion

α-Amino esters are precursors to noncanonical amino acids used in developing small-molecule therapeutics, biologics, and tools in chemical biology. α-C–H amination of abundant and inexpensive carboxylic acid esters through nitrene transfer presents a direct approach to α-amino esters. Methods for nitrene-mediated amination of the protic α-C–H bonds in carboxylic acid esters, however, are underdeveloped. This gap arises because hydrogen atom abstraction (HAA) of protic C–H bonds by electrophilic metal-nitrenoids is slow: metal-nitrenoids preferentially react with polarity-matched, hydridic C–H bonds, even when weaker protic C–H bonds are present. This study describes the discovery and evolution of highly stable protoglobin nitrene transferases that catalyze the enantioselective intermolecular amination of the α-C–H bonds in carboxylic acid esters. We developed a high-throughput assay to evaluate the activity and enantioselectivity of mutant enzymes together with their sequences using the Every Variant Sequencing (evSeq) method. Furthermore, the assay enabled the identification of enantiodivergent enzymes that function at ambient conditions in Escherichia coli whole cells and whose activities can be enhanced by directed evolution for the amination of a range of substrates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Antibiotic that inhibits trans -translation blocks binding of EF-Tu to tmRNA but not to tRNA

trans-Translation is conserved throughout bacteria and is essential in many species. High-throughput screening identified a tetrazole-based trans-translation inhibitor, KKL-55, that has broad-spectrum antibiotic activity. A biotinylated version of KKL-55 pulled down elongation factor thermo-unstable (EF-Tu) from bacterial lysates. Purified EF-Tu bound KKL-55 in vitro with a K d = 2 µM, confirming a high-affinity interaction. An X-ray crystal structure showed that KKL-55 binds in domain 3 of EF-Tu, and mutation of residues in the binding pocket abolished KKL-55 binding. RNA-binding assays in vitro showed that KKL-55 inhibits binding between EF-Tu and transfer-messenger RNA (tmRNA) but not between EF-Tu and tRNA. These data demonstrate a new mechanism for the inhibition of EF-Tu function and suggest that this specific inhibition of EF-Tu•tmRNA binding is a viable target for antibiotic development.

59 BASIC BIOLOGICAL SCIENCES↗

Engineered Microorganisms for Enhanced Rare Earth Element Bio-mining and Separations (Final Technical Report)

Rare earth elements (REE) are critical ingredients of sustainable energy technologies, but their extraction from ore and separation from one another pose formidable challenges. To solve the challenge of REE supply, we used advanced genomics, high-throughput screening with synthetic REE minerals, and synthetic biology to engineer two sets of exotic microbes to (1) extract REE from ores, spent cracking catalysts, coal ash and electronic waste with high efficiency and selectivity, and (2) to purify REE into single element batches, all under benign conditions without the need of harsh solvents and high temperatures. This work integrated our expertise in systems and synthetic biology (Buz Barstow); rare-earth geochemistry (Esteban Gazel) and mineral synthesis (Megan Holycross); and microsystems engineering (Mingming Wu) by first elucidating the set of rules that predict an organism’s phenotype and then applying them to solve this critical problem in sustainable energy. These new technologies could help to revitalize the US rare earth industry and provide a new source of these critical elements for future energy technologies. We have already had some big success in tech transfer. Two of our team members (postdoctoral fellow Alexa Schmitz and graduate student Sean Medin) were able to study the supply chain for REE in the United States, and identify an opportunity to commercialize our REE mineral-dissolution technology. Alexa and Sean recently founded REEgen, Inc., an REE biomining company. Dr. Schmitz was recently awarded a fellowship from the Activate Foundation to support the first two years of REEgen. Cornell showed its support for this technology and company, and Dr. Schmitz was awarded the Rising Women Innovator’s award. These two awards unlocked support from Cornell’s Praxis Incubator.

58 GEOSCIENCES↗