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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Functional roles of the [2Fe-2S] clusters in Synechocystis PCC 6803 Hox [NiFe]-hydrogenase reactivity with ferredoxins

The HoxEFUYH complex of Synechocystis PCC 6803 (S. 6803) consists of a HoxEFU ferredoxin:NAD(P)H oxidoreductase subcomplex and a HoxYH [NiFe]-hydrogenase subcomplex that catalyzes reversible H2 oxidation. Prior studies have suggested that the presence of HoxE is required for reactivity with ferredoxin; however, it is unknown how HoxE is functionally integrated into the electron transfer network of the HoxEFU:ferredoxin complex. Deciphering electron transfer pathways is challenged by the rich iron-sulfur cluster content of HoxEFU, which includes a [2Fe-2S] cluster in each subunit, along with multiple [4Fe-4S] clusters and a flavin cofactor. To resolve the role of HoxE, we determined the biophysical and thermodynamic properties of each [2Fe-2S] cluster in HoxEFU using steady-state and potentiometric EPR analysis in combination with square wave voltammetry (SWV). The temperature-dependence of the EPR signal for HoxE confirmed the coordination of a single [2Fe-2S] cluster that was shown by SWV to have an E m = -424 mV (versus SHE). Strikingly, when the E m of the HoxE [2Fe-2S] cluster was analyzed in HoxEFU titrations, it was shifted by >100 mV to an E m < -525 mV (versus SHE). EPR titrations of HoxEFU gave an E m value for the [2Fe-2S] cluster of HoxF, E m = -419 mV and HoxU, E m = -349 mV. These values were used to re-analyze the diaphorase kinetics in reactions performed with ferredoxins with varying E m 's. The results are formulated into a model of HoxEFU:ferredoxin reactivity and the role of HoxE in mediating electron transfer within the HoxEFU:ferredoxin complex.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Beta-delayed gamma spectra compilation and analysis following the thermal-neutron induced fission of 235 U, 239,241 Pu

The integral gamma and electron spectra emitted by fission products, also known as delayed gamma and electron spectra, were measured at Oak Ridge National Laboratory in the 1970s for the thermal-neutron induced fission of 235 U and 239,241 Pu. Scintillator detectors were used to measure these spectra, data used later on to obtain decay heat values - that is, the spectra mean values per unit time as function of time - work that was published in the Nuclear Science and Technology journal; the spectral data, however, was only published in laboratory reports. Here, in this work, we analyze the gamma spectra data using modern methods and nuclear databases to reveal the signature of individual fission products as well as to gauge the performance of the ENDF/B-VIII.0 decay data sub-library, concluding about possible future enhancements in predictive capabilities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Classifying biophysical subpopulations of insulin secretory granules using quantitative whole-cell structure analysis

Pancreatic beta cells contain insulin secretory granules (ISGs), organelles where proinsulin is converted into insulin. As ISGs mature, they undergo extensive biophysical remodeling, producing a spectrum of subpopulations with heterogeneous molecular and spatial characteristics. However, systematic methods to define ISG subpopulations remain underdeveloped. To address this gap in knowledge, we employed soft X-ray tomography (SXT), which can quantitatively measure the biochemical density of ISGs within whole beta cells. Using unsupervised clustering, we classified subpopulations based on molecular density, size, and spatial positioning. Across different insulin secretory stimuli, we observed shifts toward mature and releasable subtypes, demonstrating that exogenous signals can dynamically remodel ISG subpopulation distributions. We extended this methodology to primary beta cells characterized using volume electron microscopy (vEM). Integrating subpopulations from SXT and vEM uncovered insights inaccessible by a single method in isolation. This strategy establishes a framework for defining therapeutic approaches aimed at enriching physiologically beneficial ISG subpopulations.

dense-core granules↗
DOE OSTI2025

Mechanically flexible mid-wave infrared imagers using black phosphorus ink films

The mid-wave infrared (MWIR) spectral range (λ = 3–8 μm) enables important sensing and imaging applications, including non-invasive bioimaging, night vision, and autonomous navigation. Commercial MWIR photodetectors are limited to rigid imagers based on heteroepitaxial materials. There is an emerging need for mechanically flexible MWIR imagers to broaden their functionality and practicality. Recently, photodetectors using van der Waals (vdW) black phosphorus (BP) flakes have demonstrated highly sensitive room-temperature photodetection. Additionally, vdW materials are solution-processable, facilitating scalable processing and flexible device fabrication. In this work, we present flexible MWIR imagers consisting of photodiodes fabricated on thin plastic substrates using BP ink films. We demonstrate mechanically robust responsivity up to 2.5-mm bending radii and after 5000 bending cycles. Leveraging this flexibility, we achieve full-azimuthal imaging, detecting directional light sources with precision. These results establish a scalable approach for large-area, conformable MWIR imaging and pave the way for integration with flexible electronics.

Wijaya, Theodorus Jonathan↗
DOE OSTI2020

Magnetic proximity and nonreciprocal current switching in a monolayer WTe2 helical edge

The integration of diverse electronic phenomena, such as magnetism and nontrivial topology, into a single system is normally studied either by seeking materials that contain both ingredients, or by layered growth of contrasting materials. The ability to simply stack very different two-dimensional van der Waals materials in intimate contact permits a different approach. Here we use this approach to couple the helical edges states in a two-dimensional topological insulator, monolayer WTe 2 , to a two-dimensional layered antiferromagnet, CrI 3 . We find that the edge conductance is sensitive to the magnetization state of the CrI 3 , and the coupling can be understood in terms of an exchange field from the nearest and next-nearest CrI 3 layers that produces a gap in the helical edge. We also find that the nonlinear edge conductance depends on the magnetization of the nearest CrI 3 layer relative to the current direction. At low temperatures this produces an extraordinarily large nonreciprocal current that is switched by changing the antiferromagnetic state of the CrI 3 .

36 MATERIALS SCIENCE↗
DOE OSTI2026

A multimodal large language model for materials science

Understanding and predicting the properties of inorganic materials is crucial for accelerating advancements in materials science and driving applications in energy, electronics and beyond. Integrating material structure data with language-based information through multimodal large language models (LLMs) offers great potential to support these efforts by enhancing human–artificial intelligence interaction. However, a key challenge lies in integrating atomic structures at full resolution into LLMs. In this work, we introduce MatterChat, a versatile structure-aware multimodal LLM that unifies material structural data and textual inputs into a single cohesive model. MatterChat uses a bridging module to effectively align a pretrained universal machine learning interatomic potential with a pretrained LLM, reducing training costs and enhancing flexibility. Our results demonstrate that MatterChat greatly improves performance in material property prediction and human–artificial intelligence interaction, surpassing general-purpose LLMs such as GPT-4. We also demonstrate its usefulness in applications such as more advanced scientific reasoning and step-by-step material synthesis.

Tang, Yingheng [Lawrence Berkeley National Laborat↗
DOE OSTI2022

Self-assembled HfO 2 -Au nanocomposites with ultra-fine vertically aligned Au nanopillars

Oxide-metal-based hybrid materials have gained great research interest in recent years owing to their potential for multifunctionality, property coupling, and tunability. Specifically, oxide-metal hybrid materials in a vertically aligned nanocomposite (VAN) form could produce pronounced anisotropic physical properties, e.g., hyperbolic optical properties. Herein, self-assembled HfO 2 -Au nanocomposites with ultra-fine vertically aligned Au nanopillars (as fine as 3 nm in diameter) embedded in a HfO 2 matrix were fabricated using a one-step self-assembly process. The film crystallinity and pillar uniformity can be obviously improved by adding an ultra-thin TiN-Au buffer layer during the growth. Here, the HfO 2 -Au hybrid VAN films show an obvious plasmonic resonance at 480 nm, which is much lower than the typical plasmonic resonance wavelength of Au nanostructures, and is attributed to the well-aligned ultra-fine Au nanopillars. Coupled with the broad hyperbolic dispersion ranging from 1050 nm to 1800 nm in wavelength, and unique dielectric HfO 2 , this nanoscale hybrid plasmonic metamaterial presents strong potential for the design of future integrated optical and electronic switching devices.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Localized phase contrast imaging at the Wendelstein 7-X stellarator

In its basic form, phase contrast imaging (PCI) provides line-integrated measurements of electron density fluctuations in plasmas. As turbulent fluctuations in magnetically confined plasmas have wave vectors almost perpendicular to the background magnetic field, the signals scattered by fluctuations from different parts of the PCI line-of-sight (LoS) are spatially separated in focal planes of the plasma. This allows localized PCI measurements by placing a mask in such a plane, to only permit signals from specific parts of the LoS to reach the PCI detectors. The present paper describes modeling and design of localization masks for the PCI system at the Wendelstein 7-X (W7-X) stellarator as well as the first results obtained using the masks in the recent long-pulse W7-X experimental campaign. During this project, we have extended the theory describing the mask response within the Fraunhofer diffraction model. As a novel development, we show from first principles that the mask response is determined by the fraction of power of the scattered beam spots that passes the mask. These insights have been used to select the W7-X mask design, consisting of a circular cutout, allowing the unscattered beam spot to pass the mask, with wedges covering a fixed angular range outside the central cutout. In the recent W7-X experimental campaign, the masks have verified the location of the main turbulence features observed by the PCI system and provided new information about the location of short-wavelength magnetohydrodynamic modes.

Physics↗
DOE OSTI2026

Hofstadter butterfly and quantum transport benchmarks in PVA-exfoliated graphene heterostructures

Polymer exposure during van der Waals heterostructure fabrication is widely regarded as compromising the integrity of the electronic system required for hosting emergent quantum physics. This assumption has persisted largely because electronic benchmarking of heterostructures from polymer-exposed graphene has remained limited to only foundational transport metrics, such as mobility and charge inhomogeneity. Here, we challenge this assumption by establishing that graphene heterostructures produced by polyvinyl alcohol (PVA)-assisted exfoliation and encapsulated in hexagonal boron nitride using elevated-temperature lamination satisfy demanding quantum transport benchmarks. Beyond exhibiting ultra-high mobility and ballistic transport, these heterostructures yield quantum scattering times comparable to the best polymer-free devices. Most demanding of all, moiré superlattices from PVA-exposed graphene exhibit Hofstadter butterfly spectra, confirming spatially uniform interlayer coupling across the device area. These results establish that PVA exposure is compatible with low-disorder electronic systems, relaxing the trade-off between scalable fabrication and low-disorder quantum transport. This study motivates further development of polymer-assisted assembly with engineered residue-removal protocols.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Studies in pulse shape discrimination for an optimized ASIC design

The continued advancements of Silicon Photomultipliers (SiPMs) have made them viable photosensors for low recoil energy Pulse Shape Discrimination (PSD) between fast neutron and gamma interactions when coupled to an appropriate scintillator. At the same time, the large number of channels in a typical array calls for the development of low-cost and low-power electronics. A custom integrated circuit (ASIC) is an ideal solution for this purpose. To assess the requirements for such an ASIC, studies were performed using two scintillators, Stilbene and EJ-276, coupled to a 6 x 6 mm SiPM from Onsemi. We demonstrate that both scintillators are viable for performing PSD for interaction energies from 100 keV to several MeV while optimizing the integration periods used in the PSD metric. These measurements inform the design parameters of the ASIC under development.

Si-PMTs↗
DOE OSTI2024

Intricate short-range order in GeSn alloys revealed by atomistic simulations with highly accurate and efficient machine-learning potentials

GeSn alloys hold promise for silicon-compatible integrated applications in electronics, photonics, and topological quantum devices. However, understanding their intricate structures using density functional theory (DFT) calculations is hindered by spatiotemporal constraints. To overcome this limitation, we develop highly accurate and efficient machine-learning interatomic potentials based on a neuroevolution potential approach with farthest point sampling on a comprehensive DFT data set. The application of the developed machine-learning potential in large-scale atomistic simulations bridges the spatiotemporal gap between modeling and advanced characterizations, and facilitates the discovery of structural intricacies in GeSn alloys. Through extensive statistical sampling, we identify a type of short-range order (SRO) that is distinguished by both its structural signature and electronic band gap from the SRO structure previously predicted. Modeling based on a large simulation cell reveals the coexistence of nano SRO domains with various degrees of ordering, demonstrating a complex spatial heterogeneity of SRO structure. Finally, our study not only reinforces the significance of fine-level structural information in alloys, but it also constitutes an effective framework for exploring SRO in a broad range of complex alloys based on highly accurate and effective machine-learning potentials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Grid-forming Control of Single- and Two-Stage Solar PV Systems with Mode Transition

Legacy power systems once dominated by con-ventional synchronous machines are transitioning into systems driven by fast-acting power-electronic converters that integrate renewable resources. The majority of integrated renewables such as PV and wind bring down system inertia and can cause stability issues due to their volatile nature. The state-of-the-art grid-forming (GFM) control is proven to enhance system inertia and stability in low-inertia systems. However, most of the existing GFM inverters are applied for battery systems, which are much more expensive than PV. Motivated by this, in this paper we propose a holistic grid-forming (GFM) control strategy for PV systems without the need of energy storage. The proposed strategy is developed on the secondary level of the grid-forming control that enables the PV inverter to operate smoothly among islanded, synchronization, GFM, and limited grid-forming (LGF) modes. The practical criteria for determining the operation modes are established and implemented based on the grid operation scenarios. Here, the proposed design is successfully validated by case studies with a laboratory prototype using Siemens Software Defined Inverters.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

An Intelligent Power Electronic System for Secondary Use Batteries

This paper presents a plug-and-play power electronic system for integration of multiple energy storage system technologies. The system uses a communication and control architecture with individual developed modules to support scaling to larger systems for the electric grid. An optimization framework is also presented to demonstrate the functionality of the system. This system is shown to work in hardware with a constructed testbed to demonstrate different use cases and systems. Results are presented for a full efficiency cycle test.

Starke, Michael↗
DOE OSTI2022

Highly enhanced ferroelectricity in HfO 2 -based ferroelectric thin film by light ion bombardment

Continuous advancement in nonvolatile and morphotropic beyond-Moore electronic devices requires integration of ferroelectric and semiconductor materials. The emergence of hafnium oxide (HfO 2 )–based ferroelectrics that are compatible with atomic-layer deposition has opened interesting and promising avenues of research. However, the origins of ferroelectricity and pathways to controlling it in HfO 2 are still mysterious. We demonstrate that local helium (He) implantation can activate ferroelectricity in these materials. Additionally, the possible competing mechanisms, including He ion–induced molar volume changes, vacancy redistribution, vacancy generation, and activation of vacancy mobility, are analyzed. These findings both reveal the origins of ferroelectricity in this system and open pathways for nanoengineered binary ferroelectrics.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Ferroelectric materials toward next-generation electromechanical technologies

Ferroelectric materials have been widely used in various electromechanical devices, from ultrasonic transducers and actuators to mechanical energy harvesters. The key performance metrics of these devices, such as sensitivity, efficiency, and bandwidth of ultrasonic transducers, are largely determined by the piezoelectric properties. This Review highlights recent research progress in improving the piezoelectricity of ferroelectric materials and offers potential strategies for further enhancement to meet the ever-increasing demands for high-performance piezoelectric devices and systems. Here, it provides insights into the future development of ferroelectrics to address the increasing demands of emerging applications, including photoacoustic imaging and piezoelectric fans and motors in integrated circuit–enabled electronic devices. Additionally, it emphasizes the need to consider environmental impacts across the entire life cycle of ferroelectrics, from sourcing and manufacturing to usage and disposal.

36 MATERIALS SCIENCE↗
DOE OSTI2020

BinaryCIF and CIFTools—Lightweight, efficient and extensible macromolecular data management

3D macromolecular structural data is growing ever more complex and plentiful in the wake of substantive advances in experimental and computational structure determination methods including macromolecular crystallography, cryo-electron microscopy, and integrative methods. Efficient means of working with 3D macromolecular structural data for archiving, analyses, and visualization are central to facilitating interoperability and reusability in compliance with the FAIR Principles. We address two challenges posed by growth in data size and complexity. First, data size is reduced by bespoke compression techniques. Second, complexity is managed through improved software tooling and fully leveraging available data dictionary schemas. To this end, we introduce BinaryCIF, a serialization of Crystallographic Information File (CIF) format files that maintains full compatibility to related data schemas, such as PDBx/mmCIF, while reducing file sizes by more than a factor of two versus gzip compressed CIF files. Moreover, for the largest structures, BinaryCIF provides even better compression—factor ten and four versus CIF files and gzipped CIF files, respectively. Herein, we describe CIFTools, a set of libraries in Java and TypeScript for generic and typed handling of CIF and BinaryCIF files. Together, BinaryCIF and CIFTools enable lightweight, efficient, and extensible handling of 3D macromolecular structural data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Precision Agriculture using Networks of Degradable Analytical Sensors (PANDAS) (Final Technical Report)

Precision agriculture, where sensing of soil, environment and crop conditions are used to precisely synchronize inputs (such as water and fertilizer) to crop needs enhances input use efficiency. This can improve yields and farm profitability while mitigating environmental losses, improving soil carbon content and substantially decreasing energy use for food, feed and fuel crops. Unfortunately, farmers are not yet able to harness the full potential of these management technologies as there is a lack of available management information, and there is therefore a need for sensors that are able to economically measure spatio-temporal variability in soil and crop properties of extremely heterogeneous farm fields precisely at high resolution and at low cost. Real-time, in-situ monitoring of agricultural soil conditions is today carried out using devices that limit the total number of nodes that can be used economically to typically one per acre or less. Higher spatio-temporal resolution sensing would enable more precise agricultural input optimization, with significant benefits to the farmer and the environment. In order to address this issue, this project focused on developing additively manufactured, biodegradable, soil sensors with predicted costs of < $\$$1 per unit to monitor crop inputs (such as water and fertilizer) that predictably, harmlessly degrade away into the soil when no longer needed. These sensor nodes should be easy to place, accurately and continuously monitor soil and crop conditions for an entire season, be read remotely using existing farm equipment, require no ongoing maintenance, not impede farm operations and produce no persistent waste. This approach could enable a >100× increase in information density over current solutions for precision farming of row and other crops, and lead to significant reductions in input energy use and provide increased yield for biofuel crops. Over the course of this project the team at the University of Colorado Boulder, University of California Berkeley, and Colorado State University/Kansas State University investigated a wide range of printable biodegradable electronic materials and sensor designs for determining soil moisture and soil nitrate concentration. These efforts expanded the available materials set for printed soil degradable electronic materials, particularly for conductors, enabling high conductivity and stability. Printed soil moisture and nitrate sensors with suitable sensitivity and selectivity were developed and characterized. Low power and passive wireless electronic systems were integrated with the soil sensors, and testing was carried out with completed sensors to understand their functionality under agricultural conditions. Additionally, other sensor types enabled by the biodegradable materials set created during this project, such as soil microbial activity sensors, were also developed and demonstrated. Project outputs include 10 peer reviewed publications, 4 patent applications, 21 technical presentations, 3 PhD thesis, 10 media reports, 8 additional grants worth over $\$$6M, and the formation of 3 start-up companies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Adaptive Neuro Fuzzy Inference System for Cyber-Intrusion Detection in a Smart Grid

The evolution of the power grid has brought increasing deployment of advance metering infrastructure, penetration of intelligent electronic devices, and integration of physical power system components with information and communications technologies. With the fast-expanding connectivity, cyber vulnerabilities arise due to the use of internet-based communication systems. These systems are targets of cyber-intrusions which attempt to disturb the normal power system functions. Traditional intrusion detection algorithms have been developed without an explicit model of the cyber components. In this paper, an algorithm to detect false data injections in the power system is proposed considering both cyber and physical models of the power system. The algorithm is based on an Adaptive Neuro Fuzzy Inference System (ANFIS) which collects information from state variables of the cyber-physical system to meet the performance requirements of the grid. Simulations of the proposed approach using the IEEE 13-bus test system validate the effectiveness of this artificial intelligence-based algorithm.

Adaptive Neuro Fuzzy Inference System (ANFIS), cyb↗