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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

TransPlatformer

We propose TransPlatformer for translating toxicogenomics from one platform to another. Transcriptomic profiling has evolved through multiple generations of technology, from microarrays (e.g., Affymetrix, CodeLink) to more recent high-throughput sequencing and targeted panels such as S1500+. Microarrays, which dominated gene expression studies in the early 2000s, provided affordable and high-throughput transcript quantification but suffered from cross-hybridization issues and limited dynamic range . RNA-Seq, introduced in the late 2000s, revolutionized transcriptomics by enabling unbiased and comprehensive gene expression analysis, albeit at higher costs and computational demands . Despite advances, many studies rely on historical microarray data, necessitating the translation of legacy data into modern platforms to ensure continuity and comparability. This translation is complicated by factors such as platform-specific probe design, differences in transcript coverage, and batch effects . Existing methods for cross-platform mapping include statistical normalization, machine learning models, and biological anchoring approaches. The ability to translate transcriptomic data between platforms has broad implications, including enhanced meta-analyses, improved toxicological modeling, and better integration of historical datasets with contemporary research. TransPlatformer seeks to contribute to this effort by evaluating translation methodologies and proposing novel strategies to improve cross-platform gene expression harmonization. In this repository there are code examples for TransPlatformer implementation

Cong, Guojing↗
DOE OSTI2025

Toward High-Voltage Cathodes for Zinc-Ion Batteries: Discovery Pipeline and Material Design Rules

Efficient energy storage systems are crucial to address the intermittency of renewable energy sources. As multivalent batteries, Zn-ion batteries (ZIBs), while inherently low voltage, offer a promising low-cost alternative to Li-ion batteries due to the viable use of zinc as the anode. However, to maximize the potential impact of ZIBs, rechargeable cathodes with improved Zn diffusion are needed. To better understand the chemical and structural factors influencing Zn-ion mobility within battery electrode materials, we employ a high-throughput computational screening approach to systematically evaluate candidate intercalation hosts for ZIB cathodes, expanding the chemical search space on empty intercalation hosts that do not contain Zn. We leverage a high-throughput screening funnel to identify promising cathodes in ZIBs, integrating screening criteria with density functional theory (DFT)-based calculations of Zn2+ intercalation and diffusion inside the host materials. Using these data, we identify the design principles that favor Zn-ion mobility in candidate cathode materials. Building on previous work on divalent-ion cathodes, this study broadens the chemical space for next-generation multivalent energy storage systems.

electrodes↗
DOE OSTI2025

Network Slicing for Federated Learning in Operational Technology Environment

Industrial Control Systems (ICS) and Supervisory Control and Data Acquisition (SCADA) environments are essential to modern infrastructure, facing challenges in ensuring low-latency, high-throughput communication while mitigating cyber threats. This paper presents a framework integrating Federated Learning (FL) and network slicing with Quality of Service (QoS) to enable real-time monitoring without disrupting OT operations. Leveraging digital twin technology and Network Function Virtualization (NFV), the architecture supports predictive analytics and Industry 4.0 requirements. FL facilitates decentralized model training, preserving data privacy and scalability, though it introduces potential throughput constraints. Network slicing addresses this by creating dedicated virtualized segments optimized for performance and security. Advanced fault tolerance at the container and instance levels enhances system reliability. The proposed architecture ensures high throughput, low latency, and secure orchestration for real-time anomaly detection in OT networks. Performance evaluations validate its efficiency in throughput, deployment, and learning accuracy, providing a robust foundation for future ICS automation and data-driven decision-making.

Delgado, Brian G. Rodiles [University of Texas at ↗
DOE OSTI2024

Electronic structure simulations in the cloud computing environment

The transformative impact of modern computational paradigms and technologies, such as high-performance computing, quantum computing, and cloud computing, has opened up profound new opportunities for scientific simulations. Scalable computational chemistry is one beneficiary of this technological progress. The main focus of this paper is on the performance of various quantum chemical formulations, ranging from low-order methods to high-accuracy approaches, implemented in different computational chemistry packages, such as NWChem, NWChemEx, SPEC, ExaChem, and FLOSIC codes on the Azure Quantum Element (AQE) Microsoft cloud services. We pay particular attention to the intricate workflows for performing composite chemistry simulations, associated data curation, and mechanisms for accuracy assessment, as defined by the enabling cloud Computational Chemistry as a Service (CCaaS). Our focus also extends to Arrows' automated workflow for high throughput simulations. Finally, we provide a perspective on the role of cloud computing in supporting the mission of leadership computational facilities (LCFs).

computational chemistry, electronic structure, Clo↗
DOE OSTI2026

Architector 2.0: Expanded Capabilities for Metal Complex Engineering

Automated three-dimensional molecular construction from two-dimensional graph representations is critical to high-throughput discovery eIorts. Software capabilities in this area have accelerated research across fields ranging from protein design and drug discovery to transition metal catalyst development. When Architector was first introduced, it uniquely enabled high-throughput, chemically relevant three-dimensional construction of f-element complexes. Since its introduction, Architector has been applied in large-scale computational campaigns, targeted studies in critical mineral extraction, and artificial intelligence-driven discovery eIorts.

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

Non-Electricity Based Renewable Fuels: Theory and Computation for Solar Thermochemical Hydrogen

Dominated by photovoltaics and wind, current renewable energy sources generate mostly electricity, but 80% of the global final energy consumption occurs in form of fuels. Therefore, direct solar fuel generation would be a major breakthrough for the energy transition. Solar thermochemical hydrogen (STCH) is one of the very few potential routes towards scalable renewable fuels, but currently suffers from lack of an oxide working material that could optimally perform energy conversion within the thermodynamic boundary conditions. Theory and computation can contribute in two distinct ways, through materials search and discovery, but also by providing detailed mechanistic models for specific systems so to advance our understanding of possible design strategies. To enable high-throughput materials screening, we developed a defect graph neural network (dGNN) machine learning approach,[1] which accelerates the prediction of defect formation energies by replacing the tedious density functional theory (DFT) supercell calculations for all possible defect sites. This approach enables high-throughput database screening of oxides, which was integrated with thermodynamic modeling to extract the reduction entropies as additional selection criterion for STCH. Once potential candidate materials are identified, detailed models can guide materials design by predicting performance characteristics. One challenge is to quantitatively predict thermochemical equilibria at high concentrations when the redox active defects start to interact with each other, thereby impeding the formation of additional defects. Introducing a model for the free energy of defect interaction, parametrized on the basis of DFT data, we simulated the complete STCH redox cycle for (Sr,Ce)MnO3 alloys, achieving near-quantitative agreement with experimental data.[2] The analysis of these simulations reveals how defect interactions diminish the reduction entropy and H2 yield, suggesting to include these interactions in design considerations. Finally, we revisit the popular van't Hoff method for analyzing reduction enthalpies and entropies. This method is not ideal, as it involves a temperature-dependent convolution of gas-phase and solid-state entropies, causing uncertainties in the same order of magnitude as the physical quantities of interest. To avoid this problem, we suggest a simple alternative approach which can be applied to experimental and simulated data alike.

first-principles calculations↗
DOE OSTI2024

Integrated design of aluminum-enriched high-entropy refractory B2 alloys with synergy of high strength and ductility

Refractory high-entropy alloys (RHEAs) are promising high-temperature structural materials. Their large compositional space poses great design challenges for phase control and high strength-ductility synergy. The present research pioneers using integrated high-throughput machine learning with Monte Carlo simulations supplemented by ab initio calculations to effectively navigate phase selection and mechanical property predictions, developing single-phase ordered B2 aluminum-enriched RHEAs (Al-RHEAs) demonstrating high strength and ductility. These Al-RHEAs achieve remarkable mechanical properties, including compressive yield strengths up to 1.7 gigapascals, fracture strains exceeding 50%, and notable high-temperature strength retention. They also demonstrate a tensile yield strength of 1.0 gigapascals with a ductility of 9%, albeit with B2 ordering. Furthermore, we identify valence electron count domains for alloy ductility and brittleness with the explanation from density functional theory and provide crucial insights into elemental influence on atomic ordering and mechanical performance. The work sets forth a strategic blueprint for high-throughput alloy design and reveals fundamental principles governing the mechanical properties of advanced structural alloys.

Science & Technology - Other Topics↗
NASA NTRS2004

Plasma Enhanced Growth of Carbon Nanotubes For Ultrasensitive Biosensors

The multitude of considerations facing nanostructure growth and integration lends itself to combinatorial optimization approaches. Rapid optimization becomes even more important with wafer-scale growth and integration processes. Here we discuss methodology for developing plasma enhanced CVD growth techniques for achieving individual, vertically aligned carbon nanostructures that show excellent properties as ultrasensitive electrodes for nucleic acid detection. We utilize high throughput strategies for optimizing the upstream and downstream processing and integration of carbon nanotube electrodes as functional elements in various device types. An overview of ultrasensitive carbon nanotube based sensor arrays for electrochemical biosensing applications and the high throughput methodology utilized to combine novel electrode technology with conventional MEMS processing will be presented.

Cassell, Alan M.↗
NASA NTRS1993

X ray, extreme and far ultraviolet optical thin films for space applications

Far and extreme ultraviolet optical thin film filters find many uses in space astronomy, space astrophysics, and space aeronomy. Spacebased spectrographs are used for studying emission and absorption features of the earth, planets, sun, stars, and the interstellar medium. Most of these spectrographs use transmission or reflection filters. This requirement has prompted a search for selective filtering coatings with high throughput in the FUV and EUV spectral region. Important progress toward the development of thin film filters with improved efficiency and stability has been made in recent years. The goal for this field is the minimization of absorption to get high throughput and enhancement of wavelength selection. The Optical Aeronomy Laboratory (OAL) at the University of Alabama in Huntsville has recently developed the technology to determine optical constants of bulk and film materials for wavelengths extending from x-rays (0.1 nm) to the FUV (200 nm), and several materials have been identified that were used for designs of various optical devices which previously have been restricted to space application in the visible and near infrared. A new design concept called the Pi-multilayer was introduced and applied to the design of optical coatings for wavelengths extending from x-rays to the FUV. Section 3 of this report explains the Pi-multilayer approach and demonstrates its application for the design and fabrication of the FUV coatings. Two layer Pi-stacks have been utilized for the design of reflection filters in the EUV wavelength range from 70 - 100 nm. In order to eliminate losses due to the low reflection of the imaging optics and increase throughput and out-of-band rejection of the EUV instrumentation we introduced a self-filtering camera concept. In the FUV region, MgF2 and LiF crystals are known to be birefringent. Transmission polarizers and quarterwave retarders made of MgF2 or LiF crystals are commercially available but the performances are poor. New techniques for the design of the EUV and FUV polarizers and quarterwave retarders are described in Section 5. X- and gamma-ray detectors rely on a measurement of the electron which is effected when a ray interacts with matter. The design of an x- and gamma-ray telescope to operate in a particular region of the spectrum is, therefore, largely dictated by the mechanism through which the rays interact. Energy selection and the focusing of the incident high energy rays can be achieved with spectrally selective high reflective multilayers. The design and spectral performance of narrowband reflective x-ray Pi-multilayers are presented in section 6.

Zukic, Muamer↗
DOE OSTI2026

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↗
DOE OSTI2024

Equilipy: a python package for calculating phase equilibria

The CALPHAD (CALculation of PHAse Diagram) approach (Nigel Saunders & Miodownik, 1998) provides predictions for thermodynamically stable phases in multicomponent-multiphase materials across a wide range of temperatures. Consequently, the CALPHAD calculations became an essential tool in materials and process design (Luo, 2015). Such design tasks frequently require navigating a high-dimensional space due to multiple components involved in the system. This increasing complexity demands high-throughput CALPHAD calculations, especially in the rapidly evolving field of alloy design. In response to the need, we developed Equilipy an open-source Python package designed for calculating phase equilibria of multicomponent-multiphase systems. Equilipy is specifically tailored for high-throughput CALPHAD calculations, offering parallel computations across multiple processors and nodes with the given NPT input conditions namely elemental compositions (N), pressure (P), and temperature (T). Equilipy utilizes the program structure and Gibbs energy functions from the Fortran-based program, Thermochimica (Piro et al., 2013), with incorporating a new Gibbs energy minimization algorithm. This algorithm, originally developed by Capitani and Brown in 1987 (Capitani & Brown, 1987), has been revised and implemented to enhance the stability and performance of calculations. The Fortran codes are precompiled and interfaced with Python via F2PY, ensuring high computation speed. Benchmark tests shown in Figure 1 demonstrate that Equilipy’s computation speed is comparable to those of established commercial software, TC-Python and PanPython. This result highlights its efficiency and potential applications in various scientific and industrial fields.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

A dual dynamic shutter system for accelerating ion irradiation sample throughput via lateral gas implantation gradients

Ion irradiation for material performance testing is limited due to its serial nature, which allows for only one value of the implantation (appm) versus dose (dpa) parameter space to be explored for each ion and experiment at a time. While ion irradiation can accelerate the process by up to three orders of magnitude compared to neutron irradiation experiments, the sample throughput for ion irradiation remains relatively low. To address these limitations, a novel capability has been developed at the Michigan Ion Beam Laboratory (MIBL), enabling for the creation of single- and two-dimensional lateral ion implantation gradients using recently installed motorized-controlled ion-beam shutters. This advancement can generate a wide scope of the two-dimensional (H+, He2+) implantation parameter space within a single sample. Integration of this new capability now allows for dual- and triple-ion beam experiments to be performed with full user control over not only the ion implantation depth, but also laterally across the sample by imposing ion implantation concentration gradients, thus providing researchers with a high-throughput means for material testing under various irradiation conditions. Furthermore, recent improvements in MIBL's microbeam ion-beam analysis (IBA) target station now allow for probing these concentration gradients in irradiated alloys with exceptional spatial resolution, down to 10 µm. These two approaches promise to significantly improve ion irradiation capabilities and increase the sample throughput by several orders of magnitude. The application of the shutter technique plus the subsequent microbeam characterization of the imposed implantation gradients are showcased by two proof-of-principle ion-irradiated experiments, one performed on single-crystal Si and the other on the fusion-candidate alloy F82H-IEA. These advancements mark a substantial leap in ion-beam technology, offering researchers a robust, high-throughput method to efficiently investigate candidate alloys with high technological readiness for both advanced fission and fusion reactor applications, in a time- and cost-effective manner.

36 - MATERIALS SCIENCE↗
NASA NTRS2004

Plasma Enhanced Growth of Carbon Nanotubes For Ultrasensitive Biosensors

The multitude of considerations facing nanostructure growth and integration lends itself to combinatorial optimization approaches. Rapid optimization becomes even more important with wafer-scale growth and integration processes. Here we discuss methodology for developing plasma enhanced CVD growth techniques for achieving individual, vertically aligned carbon nanostructures that show excellent properties as ultrasensitive electrodes for nucleic acid detection. We utilize high throughput strategies for optimizing the upstream and downstream processing and integration of carbon nanotube electrodes as functional elements in various device types. An overview of ultrasensitive carbon nanotube based sensor arrays for electrochemical bio-sensing applications and the high throughput methodology utilized to combine novel electrode technology with conventional MEMS processing will be presented.

Cassell, Alan M.↗
DOE OSTI2025

A self-supervised robotic system for autonomous contact-based spatial mapping of semiconductor properties

Integrating robotically driven contact-based material characterization techniques into self-driving laboratories can enhance measurement quality, reliability, and throughput. While deep learning models support robust autonomy, current methods lack reliable pixel-precision positioning and require extensive labeled data. To overcome these challenges, we propose an approach for building self-supervised autonomy into contact-based robotic systems that teach the robot to follow domain expert measurement principles at high throughputs. We demonstrate the performance of this approach by autonomously driving a 4-DOF robotic probe for 24 hours to characterize semiconductor photoconductivity at 3025 uniquely predicted poses across a gradient of drop-casted perovskite film compositions, achieving throughputs of more than 125 measurements per hour. Spatially mapping photoconductivity onto each drop-casted film reveals compositional trends and regions of inhomogeneity, valuable for identifying manufacturing defects. With this self-supervised neural network–driven robotic system, we enable high-precision and reliable automation of contact-based characterization techniques at high throughputs, thereby allowing measurement of previously inaccessible yet important semiconductor properties for self-driving laboratories.

Science & Technology - Other Topics↗
DOE OSTI2024

Grand canonically optimized grain boundary phases in hexagonal close-packed titanium

Grain boundaries (GBs) profoundly influence the properties and performance of materials, emphasizing the importance of understanding the GB structure and phase behavior. As recent computational studies have demonstrated the existence of multiple GB phases associated with varying the atomic density at the interface, we introduce a validated, open-source GRand canonical Interface Predictor (GRIP) tool that automates high-throughput, grand canonical optimization of GB structures. While previous studies of GB phases have almost exclusively focused on cubic systems, we demonstrate the utility of GRIP in an application to hexagonal close-packed titanium. We perform a systematic high-throughput exploration of tilt GBs in titanium and discover previously unreported structures and phase transitions. In low-angle boundaries, we demonstrate a coupling between point defect absorption and the change in the GB dislocation network topology due to GB phase transformations, which has important implications for the accommodation of radiation-induced defects.

36 MATERIALS SCIENCE↗
NASA NTRS2015

High-Reflectivity Multi-Layer Coatings for the CLASP Sounding Rocket Project

We are planning an international rocket experiment Chromospheric Lyman-Alpha Spectro-Polarimeter (CLASP) is (2015 planned) that Lyman alpha line (Ly alpha line) polarization spectroscopic observations from the sun. The purpose of this experiment, detected with high accuracy of the linear polarization of the Ly alpha lines to 0.1% by using a Hanle effect is to measure the magnetic field of the chromosphere-transition layer directly. For polarization photometric accuracy achieved that approximately 0.1% required for CLASP, it is necessary to realize the monitoring device with a high throughput. On the other hand, Ly alpha line (vacuum ultraviolet rays) have a sensitive characteristics that is absorbed by the material. We therefore set the optical system of the reflection system (transmission only the wavelength plate), each of the mirrors, subjected to high efficiency of the multilayer coating in accordance with the role. Primary mirror diameter of CLASP is about 30 cm, the amount of heat about 30,000 J is about 5 minutes of observation time is coming mainly in the visible light to the telescope. In addition, total flux of the sun visible light overwhelmingly large and about 200 000 times the Ly alpha line wavelength region. Therefore, in terms of thermal management and 0.1% of the photometric measurement accuracy achieved telescope, elimination of the visible light is essential. We therefore, has a high reflectivity (greater than 50%) in Ly alpha line, visible light is a multilayer coating be kept to a low reflectance (less than 5%) (cold mirror coating) was applied to the primary mirror. On the other hand, the efficiency of the polarization analyzer required chromospheric magnetic field measurement (the amount of light) Conventional (magnesium fluoride has long been known as a material for vacuum ultraviolet (MgF2) manufactured ellipsometer; Rs = 22%) about increased to 2.5 times were high efficiency reflective polarizing element analysis. This device, Bridou et al. (2011) is proposed "that is coated with a thin film of the substrate MgF2 and SiO2 fused silica." As a result of the measurement, Rs = 54.5%, to achieve a Rp = 0.3%, high efficiency, of course, capable of taking out only about spolarized light. Other reflective optical elements (the secondary mirror, the diffraction grating-collector mirror), subjected to high-reflection coating of Al + MgF2 (reflectance of about 80%), less than 5% in the entire optical system by these (CCD Science was achieved a high throughput as a device for a vacuum ultraviolet ray of the entire system less than 5% (CCD of QE is not included).

sounding rocket↗
NASA NTRS2015

Solar Lyman-Alpha Polarization Observation of the Chromosphere and Transition Region by the Sounding Rocket Experiment CLASP

We are planning an international rocket experiment Chromospheric Lyman-Alpha Spectro-Polarimeter (CLASP) is (2015 planned) that Lyman α line (Ly(alpha) line) polarization spectroscopic observations from the sun. The purpose of this experiment, detected with high accuracy of the linear polarization of the Ly(alpha) lines to 0.1% by using a Hanle effect is to measure the magnetic field of the chromosphere-transition layer directly. For polarization photometric accuracy achieved that approx. 0.1% required for CLASP, it is necessary to realize the monitoring device with a high throughput. On the other hand, Ly(alpha) line (vacuum ultraviolet rays) have a sensitive characteristics that is absorbed by the material. We therefore set the optical system of the reflection system (transmission only the wavelength plate), each of the mirrors, subjected to high efficiency of the multilayer coating in accordance with the role. Primary mirror diameter of CLASP is about 30 cm, the amount of heat about 30,000 J is about 5 minutes of observation time is coming mainly in the visible light to the telescope. In addition, total flux of the sun visible light overwhelmingly large and about 200 000 times the Ly(alpha) line wavelength region. Therefore, in terms of thermal management and 0.1% of the photometric measurement accuracy achieved telescope, elimination of the visible light is essential. We therefore, has a high reflectivity (> 50%) in Lyα line, visible light is a multilayer coating be kept to a low reflectance (<5%) (cold mirror coating) was applied to the primary mirror. On the other hand, the efficiency of the polarization analyzer required chromospheric magnetic field measurement (the amount of light) Conventional (magnesium fluoride has long been known as a material for vacuum ultraviolet (MgF2) manufactured ellipsometer; Rs = 22%) about increased to 2.5 times were high efficiency reflective polarizing element analysis. This device, Bridou et al. (2011) is proposed "that is coated with a thin film of the substrate MgF2 and SiO2 fused silica." As a result of the measurement, Rs = 54.5%, to achieve a Rp = 0.3%, high efficiency, of course, capable of taking out only about s-polarized light. Other reflective optical elements (the secondary mirror, the diffraction gratingcollector mirror), subjected to high-reflection coating of Al + MgF2 (reflectance of about 80%), less than 5% in the entire optical system by these (CCD Science was achieved a high throughput as a device for a vacuum ultraviolet ray of the entire system less than 5% (CCD of QE is not included).

Narukage, Noriyuki↗
DOE OSTI2025

Developing machine learning for heterogeneous catalysis with experimental and computational data

Machine learning techniques have emerged as a useful tool for identifying complex patterns and correlations in large datasets, such as associating catalyst performance to its physicochemical properties. In the heterogeneous catalysis communities, machine learning models have mostly been developed using high-throughput quantum chemistry calculations, with only a few case studies resulting in experimentally validated catalyst improvements. This limited success may be due to the use of simplified catalyst structures in computational studies and the lack of comprehensive experimental datasets. In this Review, we bring together studies integrating high-throughput approaches and machine learning for the advancement of solid heterogeneous catalysis, leveraging both experimental and computational data. We systematically analyze trends in the field, based on the descriptors used as model input and output; the materials, devices, or reactions investigated; the dataset size; and the overall achievements. Furthermore, for models reporting unitless R 2 values, we compare the performances based on these mentioned trends.

Computational chemistry↗