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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Harnessing Nanobodies for Precision Targeting of Proteoforms: Opportunities and Challenges in Therapeutics and Diagnostics

Proteoforms are biologically distinct yet structurally similar proteins that play key roles in driving disease progression but are rarely accounted for in the development of therapeutics and diagnostics. Nanobodies (Nbs) have emerged as a therapeutic and diagnostic “silver bullet” as they possess unique structural and functional attributes that offer advantages over traditional antibodies. One of the most profound advantages of Nbs is the heightened sensitivity and ability to distinguish subtle changes in the conformation of a given protein. Thus, Nbs have significant potential as therapeutic and diagnostic agents that can identify and distinguish specific pathological proteoforms that underlie a given disease. However, there remain significant challenges in obtaining sufficient quantities and purities of specific proteoform antigens that are required for engineering proteoform-specific Nbs. Recent advancements in chemical biology tools for precision proteoform synthesis have made this task feasible for the first time. In this perspective, we discuss the advantages and challenges associated with developing proteoform-specific Nbs and how success in this endeavor will significantly advance the fields of therapeutics and diagnostics.

Antigens↗
DOE OSTI2020

TeraChem: A graphical processing unit-accelerated electronic structure package for large-scale ab initio molecular dynamics

TeraChem was born in 2008 with the goal of providing fast on-the-fly electronic structure calculations to facilitate ab initio molecular dynamics studies of large biochemical systems such as photoswitchable proteins and multichromophoric antenna complexes. Originally developed for videogaming applications, graphics processing units (GPUs) offered a low-cost parallel computer architecture that became more accessible for general-purpose GPU computing with the release of CUDA in 2007. The evaluation of the electron repulsion integrals (ERIs) is a major bottleneck in electronic structure codes and provides an attractive target for acceleration on GPUs. Thus, highly efficient routines for evaluation of and contractions between the ERIs and density matrices were implemented in TeraChem. Here, electronic structure methods were developed and implemented to leverage these integral contraction routines, resulting in the first quantum chemistry package designed from the ground up for GPUs. This GPU acceleration makes TeraChem capable of performing large-scale ground and excited state calculations in the gas and condensed phase. Today, TeraChem's speed forms the basis for a suite of quantum chemistry applications, including optimization and dynamics of proteins, automated and interactive chemical discovery tools, and large-scale nonadiabatic dynamics simulations.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

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↗
DOE OSTI2020

Functional genetic encoding of sulfotyrosine in mammalian cells

Protein tyrosine O -sulfation (PTS) plays a crucial role in extracellular biomolecular interactions that dictate various cellular processes. It also involves in the development of many human diseases. Regardless of recent progress, our current understanding of PTS is still in its infancy. To promote and facilitate relevant studies, a generally applicable method is needed to enable efficient expression of sulfoproteins with defined sulfation sites in live mammalian cells. Here we report the engineering, in vitro biochemical characterization, structural study, and in vivo functional verification of a tyrosyl-tRNA synthetase mutant for the genetic encoding of sulfotyrosine in mammalian cells. We further apply this chemical biology tool to cell-based studies on the role of a sulfation site in the activation of chemokine receptor CXCR4 by its ligand. Our work will not only facilitate cellular studies of PTS, but also paves the way for economical production of sulfated proteins as therapeutic agents in mammalian systems.

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

Long-term super-resolution inner mitochondrial membrane imaging with a lipid probe

The inner mitochondrial membrane (IMM) generates power to drive cell function, and its dynamics control mitochondrial health and cellular homeostasis. Here, we describe the cell-permeant, lipid-like small molecule MAO-N 3 and use it to assemble high-density environmentally sensitive (HIDE) probes that selectively label and image the IMM in live cells and multiple cell states. MAO-N 3 pairs with strain-promoted azide–alkyne click chemistry-reactive fluorophores to support HIDE imaging using confocal, structured illumination, single-molecule localization and stimulated emission depletion microscopy, all with significantly improved resistance to photobleaching. These probes generate images with excellent spatial and temporal resolution, require no genetic manipulations, are non-toxic in model cell lines and primary cardiomyocytes (even under conditions that amplify the effects of mitochondrial toxins) and can visualize mitochondrial dynamics for 12.5 h. This probe will enable comprehensive studies of IMM dynamics with high temporal and spatial resolution.

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

Structural basis for intermodular communication in assembly-line polyketide biosynthesis

Assembly-line polyketide synthases (PKSs) are modular multi-enzyme systems with considerable potential for genetic reprogramming. Understanding how they selectively transport biosynthetic intermediates along a defined sequence of active sites could be harnessed to rationally alter PKS product structures. Here, to investigate functional interactions between PKS catalytic and substrate acyl carrier protein (ACP) domains, we employed a bifunctional reagent to crosslink transient domain–domain interfaces of a prototypical assembly line, the 6-deoxyerythronolide B synthase, and resolved their structures by single-particle cryogenic electron microscopy (cryo-EM). Together with statistical per-particle image analysis of cryo-EM data, we uncovered interactions between ketosynthase (KS) and ACP domains that discriminate between intra-modular and inter-modular communication while reinforcing the relevance of conformational asymmetry during the catalytic cycle. Our findings provide a foundation for the structure-based design of hybrid PKSs comprising biosynthetic modules from different naturally occurring assembly lines.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

High-precision chemical quantum sensing in flowing monodisperse microdroplets

A method is presented for high-precision chemical detection that integrates quantum sensing with droplet microfluidics. Using nanodiamonds (ND) with fluorescent nitrogen-vacancy (NV) centers as quantum sensors, rapidly flowing microdroplets containing analyte molecules are analyzed. A noise-suppressed mode of optically detected magnetic resonance is enabled by pairing controllable flow with microwave control of NV electronic spins, to detect analyte-induced signals of a few hundredths of a percent of the ND fluorescence. Using this method, paramagnetic ions in droplets are detected with low limit-of-detection using small analyte volumes, with exceptional measurement stability over >10 3 s. In addition, these droplets are used as microconfinement chambers by co-encapsulating ND quantum sensors with various analytes such as single cells, suggesting wide-ranging applications including single-cell metabolomics and real-time intracellular measurements from bioreactors. Important advances are enabled by this work, including portable chemical testing devices, amplification-free chemical assays, and chemical imaging tools for probing reactions within microenvironments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1977

Synthesis of silane and silicon in a non-equilibrium plasma jet

The feasibility of using a non-equilibrium hydrogen plasma jet as a chemical synthesis tool was investigated. Four possible processes were identified for further study: (1) production of polycrystalline silicon photovoltaic surfaces, (2) production of SiHCl3 from SiCl4, (3) production of SiH4 from SiHCl3, and (4) purification of SiCl4 by metal impurity nucleation. The most striking result was the recognition that the strongly adhering silicon films, amorphous or polycrystalline, produced in our studies could be the basis for preparing a photovoltaic surface directly; this process has potential advantages over other vapor deposition processes.

Calcote, H. F.↗
NASA NTRS2007

Thermal Analysis on Plume Heating of the Main Engine on the Crew Exploration Vehicle Service Module

The crew exploration vehicle (CEV) service module (SM) main engine plume heating is analyzed using multiple numerical tools. The chemical equilibrium compositions and applications (CEA) code is used to compute the flow field inside the engine nozzle. The plume expansion into ambient atmosphere is simulated using an axisymmetric space-time conservation element and solution element (CE/SE) Euler code, a computational fluid dynamics (CFD) software. The thermal analysis including both convection and radiation heat transfers from the hot gas inside the engine nozzle and gas radiation from the plume is performed using Thermal Desktop. Three SM configurations, Lockheed Martin (LM) designed 604, 605, and 606 configurations, are considered. Design of multilayer insulation (MLI) for the stowed solar arrays, which is subject to plume heating from the main engine, among the passive thermal control system (PTCS), are proposed and validated.

Wang, Xiao-Yen J.↗
NASA NTRS2020

Electromagnetic Compatibility Test and Analysis Campaign of NASA's Mars 2020 Rover

NASA's Mars 2020 Rover—with a launch window opening July 2020, and landing expected February 2021—has mission objectives to look for evidence of habitability, seek biosignatures of past life, collect and cache samples for possible future return to Earth, and prepare for future human missions. The Rover platform is similar to the previous Mars Science Laboratory (MSL) “Curiosity” rover that landed in 2012 but contains a new suite of scientific instruments and upgrades to existing functionality. The scientific payload includes a trio of chemical analysis tools (PIXL, SHERLOC, SuperCam), a ground penetrating radar (RIMFAX), an upgraded weather station (MEDA), upgraded high resolution camera (MastCam-Z), and an oxygen-producing experiment (MOXIE). These changes—along with new efficiency goals to operate more Rover subsystems concurrently and thus collect more science—presented new electromagnetic compatibility (EMC) challenges. In this paper, we will describe the campaign to ensure Mars 2020 mission success from an electromagnetic environment perspective: 1) confirming existing MSL heritage subsystems and EMC requirements were compatible with the new Mars 2020 mission objectives, 2) engaging with engineers and scientists early in the project to identify and evaluate risks before hardware assembly and performing ambitious risk reduction tests, 3) undertaking a comprehensive subsystem qualification test program based on tailored MIL-STD-461F requirements, occasionally leading to redesign, 4) synthesizing the data collected to perform detailed analyses toward the goal of making risk-informed decisions at a system level. The spacecraft has successfully completed all three planned system level tests, demonstrating self-compatibility with minimal impact to operations from electromagnetic interference in all mission phases.

Gonzales, Edward C↗
DOE OSTI2023

Integration of Experimental Hydroprocessing and FCC Data with Process (Aspen Plus) and Refinery Optimization (Aspen PIMS) Models

NREL's Economic, Sustainability, and Market Analysis (ESMA) team develops process models in Aspen Plus to support techno-economic analysis (TEA) and life-cycle assessment (LCA) of conversion pathways from renewable and circular resources to fuels and chemicals. These tools are being applied to assess probable operational constraints or bottlenecks associated with refinery co-processing and repurposing opportunities. The team also utilizes optimizable refinery models to quantify opportunities for biofuel and bioproduct pathways through integration with existing refining infrastructure. The goals of analysis are to model the transition of refineries to renewable and circular feedstocks and quantify the costs production and CO2 abatement through utilization of existing refineries. At the core of the ESMA team's work is the process data derived from conversion experiments on hydroprocessing and fluid catalytic cracking performed at NREL. The objective of this presentation is to highlight new analysis approaches and capabilities in pathway analysis and refinery optimization modeling with specific emphasis on integration of experimental data.

BIOMASS FUELS,ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

The Chemical Management System (CMS): A Useful Tool for Inventory Management

Comprehensive inventory management is central to the efficient operation of any facility that uses and stores chemicals. There are numerous software packages available that perform this function satisfactorily. Most commercially available inventory management software is regulatory or procurement focused and usually comes with upfront or monthly fees. Finally, this report describes freely downloadable software developed at Sandia National Laboratories that delivers an effective inventory management system with an additional focus on chemical security.

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

The Rise of Neural Networks for Materials and Chemical Dynamics

Machine learning (ML) is quickly becoming a premier tool for modeling chemical processes and materials. ML-based force fields, trained on large data sets of high-quality electron structure calculations, are particularly attractive due their unique combination of computational efficiency and physical accuracy. This Perspective summarizes some recent advances in the development of neural network-based interatomic potentials. Designing high-quality training data sets is crucial to overall model accuracy. One strategy is active learning, in which new data are automatically collected for atomic configurations that produce large ML uncertainties. Another strategy is to use the highest levels of quantum theory possible. Transfer learning allows training to a data set of mixed fidelity. A model initially trained to a large data set of density functional theory calculations can be significantly improved by retraining to a relatively small data set of expensive coupled cluster theory calculations. These advances are exemplified by applications to molecules and materials.

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

Ecological Benchmark for Chemicals

The Ecological Benchmark Tool dataset serves as a comprehensive repository of benchmarks designed to assess ecological risks at contaminated sites. This tool facilitates the evaluation of various environmental media and contaminants, supporting regulatory compliance and ecological protection. Benchmarks are available for air, biota, sediment, soil, and surface water. The dataset also provides species-specific benchmarks for fish, plants, birds, mammals, and invertebrates. Users can select benchmark sources, media, individual chemicals, and retrieve results in tabular or spreadsheet formats for analysis. Benchmarks are derived from authoritative sources, including government agencies, scientific councils, and academic publications. The dataset supports ecological risk assessments, regulatory decision-making, and environmental planning, with tools for benchmarking against chemical thresholds, sensitive species protection, and habitat impact evaluations. This structured approach ensures a robust evaluation of ecological risks tailored to site-specific and regulatory needs.

Stewart, Debra [Oak Ridge National Laboratory (ORN↗
DOE OSTI2021

Using GANs with adaptive training data to search for new molecules

The process of drug discovery involves a search over the space of all possible chemical compounds. Generative Adversarial Networks (GANs) provide a valuable tool towards exploring chemical space and optimizing known compounds for a desired functionality. Standard approaches to training GANs, however, can result in mode collapse, in which the generator primarily produces samples closely related to a small subset of the training data. In contrast, the search for novel compounds necessitates exploration beyond the original data. In this work, we present an approach to training GANs that promotes incremental exploration and limits the impacts of mode collapse using concepts from Genetic Algorithms. In our approach, valid samples from the generator are used to replace samples from the training data. We consider both random and guided selection along with recombination during replacement. By tracking the number of novel compounds produced during training, we show that updates to the training data drastically outperform the traditional approach, increasing potential applications for GANs in drug discovery.

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

Achieving clean production with nanostructured coated milling tools dry machining low carbon steel

The advancement of clean production using nanostructured materials in subtractive manufacturing processes has focused on replacing the use of liquid lubrication with solid lubricants coated to conventional cutting tools machining low carbon steel (~ 0.2 wt. % carbon). However, little is known about the wear mechanisms that dominate such tools when coated with functional graded nanostructured coatings. The present study follows an international standard for characterizing such wear (ISO 8688) but uses advanced measurement techniques such as x-ray fluorescence technology to measure the diffusion of chemical species from tool to workpiece and vice versa, that contributes to tool wear with the view to enhance the principles of cleaner production. The results show that when commercially-available tools coated with the appropriate functionally graded industrial coating, diffusion does not take place and creates an effective chemical barrier during machining. The experimental methods used in the study include machining workpieces using a CNC milling machine, tachometer for measuring spindle speed, dynamometer for measuring cutting forces, infra-red camera for measuring cutting temperatures, chemical species diffusion wear using x-ray florescence detector, and an optical microscope for measuring tool wear. Coupled with the physical measurement of wear, it is concluded that mechanical wear dominates the milling of a low carbon steel and that thermal properties of the coatings do not correlate with such wear. It is also concluded that flank wear as a function of volume of workpiece removed and machining duration (machining index) is a sound method for assessing the transition of the stages of wear during clean machining operations. The present study not only has implication for the design of better cutting tools, but also advances dry machining processes that eliminate the use of liquid lubricants making subtractive production processes cleaner. The main conclusions drawn from this study show that coated tools have a longer life under dry conditions compared to uncoated tools and that there is no correlation between coating properties and tool wear. In conclusion, diffusion of chemical species into the cut chips did not occur because of the lack of thermally induced chemical wear of the cutting tool and that wear is caused by the gradual erosion of the flank face due to the chip abrading the cutting tool.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Using block-copolymer nanolithography as a tool to sensitively evaluate variation in chemical dry etching rates of semiconductor materials with sub-5 nm resolution

Ion implantation is a robust and established method to customize the electronic properties of Si. However, fabricating doped, ultrafine semiconductor nanostructures can be challenging. Ion implantation has well-established effects on the dry etch rates of Si, which becomes increasingly consequential as the target dimension shrinks below a few tens of nanometers. While dry etching arrays of block copolymer-templated nanoscale holes (pitch = 37.5 nm, diameter ~25 nm) into p-type, n-type, and undoped Si, we observed that the lateral etch rate was notably larger for the n-type regions than p-type or undoped regions. By doing image analyses on high resolution electron micrographs of the nanostructured hole arrays, we were able to extract the porosity and average radii of the holes with subnanometer sensitivity and compare the relative etch rates between different doping conditions. We found that degenerately doped n-type silicon consistently etches between approximately 17% and 27% faster in the lateral direction than p-type Si, resulting in significantly larger porosity and, consequently, less mechanical stability. Here, we demonstrate that top-down dimensional analysis of a densely packed porous nanostructure is a robust method for assessing extremely small differences in the lateral, chemical etch rate of doped Si to a degree of sensitivity that was previously unachievable. The minute, dense-packed nature of block copolymer self-assembled nanostructures is shown to be ideal for this application. This proposed method could be useful for designing fabrication processes for heterogeneous nanostructures, as slight dry etch rate variations that may be within process tolerance at the micrometer-scale appear to have nontrivial consequences at the nanometer scale.

42 ENGINEERING↗