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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Charge state-dependent ion condensation near conjugated polymer backbones

Despite the technological appeal of polymeric organic mixed ionic/electronic conductors (OMIECs) for diverse applications, a deep understanding of the fundamentals of mixed charge transport in these materials, especially regarding the complex interplay between polymer, ion and solvent structure in determining transport, is lacking. Herein, extensive molecular dynamics (MD) simulations of a model OMIEC representing various electrochemically gated states are reported that reveal charge state-dependent counterion condensation. X-ray diffraction simulations based on the MD data predict a measurable change in the scattering intensity at the counterion absorption edge, indicative of counterion repositioning with charging. We leverage an operando resonant X-ray scattering technique to experimentally corroborate the simulated scattering and report excellent agreement between predicted and experimental data, confirming that counterions preferentially reside in the lamellar mid-plane of crystallites at low doping, and near the polymer backbone at higher doping. Driving forces for ion type-dependent spatial repositioning and implications thereof are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Transformative Pathways for U.S. Industry: Unlocking American Innovation

The United States (U.S.) is undergoing an energy transformation that will depend on continued U.S. innovation. Although U.S. industry has been foundational to the nation’s economic growth and prosperity, it has also given rise to decades’ worth of industrial pollutants in our air and water, which acutely impact the most vulnerable communities, as well as greenhouse gas (GHG) emissions contributing to climate risk. At the same time, U.S. industry is facing growing competitive pressures. Global investors and financial regulations are increasingly focusing on emissions footprints, governments are developing emissions-based trade adjustments and procurement specifications, and downstream demand for low-carbon products is emerging. Developing cost-competitive solutions to meet these needs provides an opportunity to fundamentally transform U.S. industry and sharpen its competitive edge, while reducing the GHG emissions and adverse environmental and health impacts (see Figure ES-1). Innovation is central to this transformation. Pathways to Commercial Liftoff: Industrial Decarbonization, which provides a descriptive fact base on what is needed to reach commercial scale in the marketplace, estimates that over 60% of emissions reduction for the industrial sector will need to come from technologies that are still nascent today. This report, Transformative Pathways for U.S. Industry,3 focuses on the pathways that rely on the nascent and innovative technologies that were too early for consideration in the Pathways to Commercial Liftoff report. Targeted and sustained public and private investment in research, development, demonstration, and deployment is required to catalyze innovation and meet this moment.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

NEXAFS spectroscopy of alkylated benzothienobenzothiophene thin films at the carbon and sulfur K-edges

Alkylated benzothienobenzothiophenes are an important class of organic semiconductors that exhibit high performance in solution-processed organic field-effect transistors. In this work, we study the near-edge x-ray absorption fine-structure (NEXAFS) spectra of 2,7-didecyl[1]benzothieno[3,2-b][1]benzothiophene (C 10 -BTBT) at both the carbon and sulfur K-edges. Angle-resolved experiments of thin films are performed to characterize the dichroism associated with molecular orientation. First-principles calculations using the density functional theory-based many-body x-ray absorption spectroscopy (MBXAS) method are also performed to correlate the peaks observed and their dichroism with transitions to specific antibonding molecular orbitals. Interestingly, the dichroism of the dominant, lowest energy peak is opposite at the carbon and sulfur K-edges. While the low-energy peak at the carbon K-edge is assigned to carbon 1s → π* transitions with transition dipole moment (TDM) perpendicular to the planar BTBT core, the dominant low energy peak at the sulfur K-edge is assigned to sulfur 1s → σ* transitions with TDM oriented along the long axis of the BTBT core. These differences at the sulfur and carbon K-edges are understood through the MBAXS simulations that find a reordering of the energy of the lowest energy π* and σ* transitions at the sulfur K-edge due to the strong localization of the σ* orbital over the sulfur atom. This work highlights differences in the NEXAFS spectra of organic semiconductors at carbon and sulfur K-edges and provides new insights into peak assignment and x-ray dichroism relevant for studying the molecular orientation of organic semiconductor films.

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

Dithieno[3,2-c:3′,2′‑ h ][2,6]naphthyridine-4,9(5H,10H)-dione-Based Conjugated Polymers for High Stable n‑Type Organic Electrochemical Transistors

Amide/imide-based conjugated polymers have been utilized as n-type OECT materials and have demonstrated promising device performance. However, their performance remains insufficient in terms of both efficiency and stability, which limits their practical applications. The development of conjugated polymers based on amide and imide groups represents a promising approach to address this issue. Here, in this study, we introduced dithieno­[3,2-c:3′,2′-h]­[2,6]­naphthyridine-4,9­(5H,10H)-dione (TVTDA) into the design of the OECT materials for the first time. By copolymerizing it with (E)-2,2′-(ethene-1,2-diyl)­bis­(thiophene-3-carbonitrile), we prepared two polymers, TVTDA-2CNTVT-ST and TVTDA-2CNTVT-BR, which contain linear or branched ethylene glycol side chains, respectively. OECT devices based on these polymers demonstrate n-type charge transport characteristics, achieving promising μC* values of 7.17 and 26.5 F cm –1 V –1 s –1 for TVTDA-2CNTVT-ST and TVTDA-2CNTVT-BR, respectively. The higher electron mobility and μC* of TVTDA-2CNTVT-BR can be attributed to its mixed edge-on and face-on stacking mode, larger crystalline coherence length, and larger domain size in the thin film. To our delight, the OECT devices based on both polymers exhibit good operational stability after operating in an aqueous solution for 2000 s, with current retention rates exceeding 93%, representing the high level among the OECT devices based on amide/imide-conjugated polymers. Our study demonstrates that the TVTDA unit holds great potential for constructing high-performance n-type OECT materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Excited State Covalency, Dynamics, and Photochemistry of Square Planar Ni-Thiolate Complexes Revealed by Ultrafast X-ray Absorption

Highly covalent Ni bis(dithiolene) and related complexes provide an ideal platform for investigating the effects of metal–ligand orbital hybridization on excited state character and dynamics. In particular, we focus on the ligand field excited states that dominate the photophysics of first-row transition metal complexes. Here, we investigate if they can be significantly delocalized off the metal center, possibly yielding photochemical reactivity more similar to charge transfer excited states than metal-centered ligand field excited states. Here [Ni(mpo) 2 ] (mpo = 2-mercaptopyridine- N-oxide) provides a representative example for the larger chemical class and is an active electro- and photo-catalyst for proton reduction. A detailed characterization of the excited state electronic structure, dynamics, and photochemistry of [Ni(mpo) 2 ] is presented based on ultrafast transient X- ray absorption spectroscopy at the Ni and S 1s core absorption K-edges. By comparing the ultrafast Ni K-edge absorption to ab initio calculations, we identify an excited state relaxation mechanism where an initial ligand-to-metal charge transfer excitation results in both excited state electron transfer (generating a catalytically relevant reduced photoproduct [Ni(mpo) 2 ] − ) and relaxation to a pseudo-tetrahedral triplet ligand field excited state. From the ultrafast S K-edge absorption, the ligand field excited state is found to be highly delocalized onto the thiolate ligands and a tetrahedral structural distortion is shown to substantially influence the degree of delocalization. The results identify a significant structural coordinate to target when aiming to control the excited state covalency in square planar complexes.

Lim, Hyeongtaek [SLAC National Accelerator Laborat↗
DOE OSTI2025

In-pixel integration of signal processing and AI/ML based data filtering for particle tracking detectors

We present the first physical realization of in-pixel signal processing with integrated AI-based data filtering for particle tracking detectors. Building on prior work that demonstrated a physics-motivated edge-AI algorithm suitable for ASIC implementation, this work marks a significant milestone toward intelligent silicon trackers. Our prototype readout chip performs real-time data reduction at the sensor level while meeting stringent requirements on power, area, and latency. The chip is taped-out in 28nm TSMC CMOS bulk process, which has been shown to have sufficient radiation hardness for particle experiments. This development represents a key step toward enabling fully on-detector edge AI, with broad implications for data throughput and discovery potential in high-rate, high-radiation environments such as the High-Luminosity LHC.

Parpillon, Benjamin [Fermilab; Illinois U., Chicag↗
DOE OSTI2024

Tearing Stable Stationary ITER Baseline Operation in DIII-D

We present a tearing stable, stationary and reproducible operating solution for DIII-D plasmas characterized by the ITER Baseline Scenario normalized parameter set and shape. In these plasmas low differential rotation (Δf1,2) between the core and edge is identified as the single root cause of the onset of the primary limiting instability, the 2,1 Neoclassical Tearing Mode (NTM), while a group of other examined parameters have a much weaker impact on the stability. Explanation is offered by drift kinetic simulations, which show a six-fold reduction in the NTM onset threshold due to diminished stabilizing ion polarization currents when the seed island drift frequency ceases in the local plasma frame. Based on the experimental observation and the explanation provided by the theory, a new method is developed to sustain Δf1,2 by modifying the edge neoclassical potential through neutral gas fueling. This method enables stationary ITER baseline operation free of disruptive 2,1 tearing modes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Wafer-scale waveguide sidewall roughness scattering loss characterization by image processing

Photonic integrated circuits (PICs) are vital for developing affordable, high-performance optoelectronic devices that can be manufactured at an industrial scale, driving innovation and efficiency in various applications. Optical loss of modes in thin film waveguides and devices is a critical measure of their performance. Thin film growth, lithography, masking, and etching processes are imperfect processes that introduce significant sidewall and top-surface roughness and cause dominating optical losses in waveguides and photonic structures. This roughness, as perturbations couple light from guided to far-field radiation modes, leads to scattering losses that can be estimated from theoretical models. Typically, with UV-based lithography, sidewall roughness is significantly larger than wafer-top surface roughness. Atomic force microscopy (AFM) imaging measurement gives a 3D and high-resolution roughness profile, but the measurement is inconvenient, costly, and unscalable for large-scale PICs and at wafer-scale. Here, we evaluate the sidewall roughness profile based on 2D high-resolution scanning electron microscope (SEM) imaging. We characterized the loss on two homemade nitride and oxide films on 3-inch silicon wafers with 12 waveguide devices on each and correlated the scattering loss estimated from a 2D image-based sidewall profile and theoretical Payne model. The lowest loss of guided fundamental transverse electric (TE 0 ) mode is found at 0.075 dB/cm at 633 nm across 24 devices, a record at visible wavelength. Our work shows 100% success (edge continuity span exceeding 95% of image width/height) in edge detection in image processing of all images to estimate autocorrelation function and optical mode loss. These demonstrations offer valuable insights into waveguide sidewall roughness and a comparison of experimental and 2D SEM image processing based loss estimations with applications in loss characterization at wafer-scale PICs.

Khurana, Mohit (ORCID:0000000207898672)↗
DOE OSTI2025

Emerging applications: Neuromorphic computing and reservoir computing

The emergence of doped hafnium oxide (HfO 2 )-based ferroelectric films has enabled highly scalable and silicon-compatible ferroelectric devices, opening new frontiers in neuromorphic and reservoir computing. Among these, ferroelectric field-effect transistors (FeFETs) are particularly promising due to their analog memory characteristics and unique polarization dynamics. These properties make FeFETs ideal candidates for artificial synapses in neuromorphic architectures, supporting deep neural networks and spiking neural networks based on leaky-integrate-and-fire (LIF) mechanisms. Beyond neuromorphic computing, FeFETs also play a crucial role in physical reservoir computing, leveraging their intrinsic nonlinear and history-dependent behavior for efficient real-time learning. This approach offers significant advantages for time-series processing and edge artificial intelligence (AI) applications, addressing the growing need for energy-efficient computing. As a result, this article explores the principles, key demonstrations, and future potential of FeFET-based neuromorphic and reservoir computing, highlighting their impact on next-generation AI hardware.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Data-driven Modeling for Grid Edge IBRs: A Digital Twin Perspective of User-Defined Models

Recent events in Odessa have brought attention to the challenges associated with the interaction between Inverter- Based Resources (IBRs) and the transmission and distribution system. The NERC event diagnosis report has highlighted sev- eral issues, emphasizing the need for continuous performance monitoring of these IBRs by system operators. Key areas of concern include the mismatch of control and protection perfor- mance of IBRs between the original equipment manufacturer (OEM)-provided models and field measurements. The inability to replicate the realistic response can result in incorrect reliability and resilience studies. In this paper, we developed an approach on how to emulate the behavior of an IBR using measurement data obtained for system operators to utilize in real-time and long- term planning. Two experiments are conducted in the phasor domain and electromagnetic transients (EMT) domain to emulate the behavior for grid forming and grid following inverters under various operating conditions and the effectiveness of the proposed model is demonstrated in terms of accuracy and ease of utilizing user-defined models (UDMs)

Mahapatra, Kaveri [BATTELLE (PACIFIC NW LAB)]↗
DOE OSTI2025

Interligand Coupling Drives Fast Triplet Energy Transfer Routes in PbS/Tetracene Quantum Dot Hybrids

The binding of photoactive organic ligands to inorganic quantum dots (QDs) creates a versatile hybrid architecture that allows access to photophysical processes such as efficient triplet exciton generation with near-infrared radiation. Here we report the subnanosecond generation of a hybrid triplet state with mixed ligand-QD character by replacing native oleate ligands on small PbS QDs with 5,12-tetracenepropiolic acid, a bifunctional ligand with two carboxylic acids that tends to lie face-on with the QD surface at low loadings. The face-on geometry engenders a regime of strong electronic coupling that is evident in steady-state absorption and hastens triplet energy flow by several orders of magnitude compared with more typical tetracene-based ligands exhibiting weak coupling. We further determined via Fourier transform infrared (FTIR) and supported by density functional theory (DFT)-based geometry optimizations that high ligand loading causes a shift in QD-ligand mutual disposition toward an edge-on geometry that instigates the formation of intermolecular excited states characterized by triplet excimer-like features in photoluminescence and transient absorption. Our results demonstrate the ability to control strongly coupled ligand-QD systems toward ultrafast generation of photophysically relevant species such as triplets that are valuable for photon upconversion and catalysis.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Extracting the electronic structure of light elements in bulk materials through a Compton scattering method in the readily accessible hard x-ray regime

Here, our Compton profile measurements of Ti and TiH 2 using readily available hard X-ray radiation at 27.5 keV, detected by both a Hitachi Vortex silicon-drift detector and a high-resolution superconducting transition-edge sensor array, are found to be in excellent accord with state-of-the-art density functional theory based calculations. The spherically averaged difference between the Compton profiles of TiH 2 and Ti is well described by an inverted parabola, supporting an itinerant behavior of the electron gas screening the protons in the Ti matrix. Our experimental approach, validated by two different detectors, extends the applicability of Compton scattering technique to the readily accessible hard x-ray regime (below 30 keV). Our study suggests possibilities for experiments at low-flux bending magnet synchrotron beamlines and paves the way for the development of tabletop Compton experiments with x-ray tubes.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Bridging Control and Deployment: A Cross-Layer Analysis of Scalable Building Cluster Control

Building cluster control has emerged as a promising approach for enabling flexible and coordinated operation of distributed building systems, yet its transition from pilot demonstrations to routine grid-interactive operation remains limited. This paper argues that this gap cannot be explained by control algorithms alone. Instead, it arises from interacting barriers in communication infrastructure, data and semantic interoperability, uncertainty management, stakeholder participation, market design, and policy support. Accordingly, the paper reviews both technical and non-technical barriers to building cluster control. Technical challenges include heterogeneous devices and protocols, communication latency and reliability, distributed decision-making, and uncertainty propagation across aggregated loads. Non-technical barriers include user participation, stakeholder coordination, incentive allocation, and data governance. Existing solution approaches are synthesized, including semantic interoperability frameworks, edge and hierarchical communication architectures, distributed and transactive control strategies, uncertainty-aware optimization, policy mechanisms, and market reforms. Based on this analysis, two research directions are identified: testing infrastructures that can evaluate control performance under realistic multi-building conditions, and abstraction methods that allow building clusters to interact with other energy sectors through standardized flexibility representations. Overall, the paper provides a structured review of how building cluster control can move from isolated demonstrations toward reproducible, market-compatible, and grid-relevant implementation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

WIP: Collaborating to Introduce Second-Life Battery Technology Research in an Informal STEM Learning Environment

This work in progress, innovative practice, paper outlines an interdisciplinary collaborative model utilized by a team of educational researchers, and engineers to design a series of community-centered, place-based learning activities suitable for a middle or high school informal STEM learning environment. Based on the potential applications and benefits of Second-Life Electric Vehicle Batteries, the activities connect cutting-edge STEM research with multidimensional real-world challenges within their communities related to climate change, renewable energy integration and storage, intelligent transportation systems, and optimized energy management, that empowers students to think critically about the role they can play in shaping a more resilient, environmentally sustainable community.

Whiteside, Hope↗
DOE OSTI2026

Microsecond-latency feedback at a particle accelerator by online reinforcement learning on hardware

The commissioning and operation of future large-scale scientific experiments will challenge current tuning and control methods. Reinforcement learning (RL) algorithms are a promising solution due to their ability to dynamically adapt to changing environments and consider delayed consequences. In many real-world applications, RL policies must produce actions in real time, often within microseconds to milliseconds, imposing significant constraints on system latency and computational overhead that conventional machine learning libraries are not designed to handle. To control phenomena in real time at these timescales, RL needs to be deployed on-the-edge, namely on dedicated hardware located near the system it controls, without relying on a host CPU or cloud-based inference. In this work we present the design and deployment of an experience accumulator system in a particle accelerator. In this system, deep-RL algorithms run using hardware acceleration and act within a few microseconds, enabling the use of RL for control of phenomena like beam instabilities. The training uses the collected data offline to reduce the number of operations carried out on the acceleration hardware. The proposed architecture was tested in real experimental conditions at the Karlsruhe research accelerator, a synchrotron light source, where the system was used to control artificially induced horizontal betatron oscillations in real-time, with a control loop period of just 2.7 μs. The results showed a performance comparable to the commercial feedback system available at the accelerator, demonstrating the viability and potential of this approach. Due to the self-learning and reconfiguration capability of this implementation, a seamless application to other control problems is possible. Applications range from particle accelerators to large-scale research and industrial facilities.

FPGA↗
DOE OSTI2025

Conformal geometry from entanglement

In a physical system with conformal symmetry, observables depend on cross-ratios, measures of distance invariant under global conformal transformations (conformal geometry for short). We identify a quantum information-theoretic mechanism by which the conformal geometry emerges at the gapless edge of a 2+1D quantum many-body system with a bulk energy gap. We introduce a novel pair of information-theoretic quantities (\mathfrak{c}_{\textrm{tot}}, \eta) ( 𝔠 tot , η ) that can be defined locally on the edge from the wavefunction of the many-body system, without prior knowledge of any distance measure. We posit that, for a topological groundstate, the quantity \mathfrak{c}_{\textrm{tot}} 𝔠 tot is stationary under arbitrary variations of the quantum state, and study the logical consequences. We show that stationarity, modulo an entanglement-based assumption about the bulk, implies (i) \mathfrak{c}_{\textrm{tot}} 𝔠 tot is a non-negative constant that can be interpreted as the total central charge of the edge theory. (ii) \eta η is a cross-ratio, obeying the full set of mathematical consistency rules, which further indicates the existence of a distance measure of the edge with global conformal invariance. Thus, the conformal geometry emerges from a simple assumption on groundstate entanglement. We show that stationarity of \mathfrak{c}_{\textrm{tot}} 𝔠 tot is equivalent to a vector fixed-point equation involving \eta η , making our assumption locally checkable. We also derive similar results for 1+1D systems under a suitable set of assumptions.

Kim, Isaac H.↗
DOE OSTI2024

HDBind: encoding of molecular structure with hyperdimensional binary representations

Traditional methods for identifying “hit” molecules from a large collection of potential drug-like candidates rely on biophysical theory to compute approximations to the Gibbs free energy of the binding interaction between the drug and its protein target. These approaches have a significant limitation in that they require exceptional computing capabilities for even relatively small collections of molecules. Increasingly large and complex state-of-the-art deep learning approaches have gained popularity with the promise to improve the productivity of drug design, notorious for its numerous failures. However, as deep learning models increase in their size and complexity, their acceleration at the hardware level becomes more challenging. Hyperdimensional Computing (HDC) has recently gained attention in the computer hardware community due to its algorithmic simplicity relative to deep learning approaches. The HDC learning paradigm, which represents data with high-dimension binary vectors, allows the use of low-precision binary vector arithmetic to create models of the data that can be learned without the need for the gradient-based optimization required in many conventional machine learning and deep learning methods. This algorithmic simplicity allows for acceleration in hardware that has been previously demonstrated in a range of application areas (computer vision, bioinformatics, mass spectrometery, remote sensing, edge devices, etc.). To the best of our knowledge, our work is the first to consider HDC for the task of fast and efficient screening of modern drug-like compound libraries. We also propose the first HDC graph-based encoding methods for molecular data, demonstrating consistent and substantial improvement over previous work. We compare our approaches to alternative approaches on the well-studied MoleculeNet dataset and the recently proposed LIT-PCBA dataset derived from high quality PubChem assays. We demonstrate our methods on multiple target hardware platforms, including Graphics Processing Units (GPUs) and Field Programmable Gate Arrays (FPGAs), showing at least an order of magnitude improvement in energy efficiency versus even our smallest neural network baseline model with a single hidden layer. Our work thus motivates further investigation into molecular representation learning to develop ultra-efficient pre-screening tools. We make our code publicly available at https://github.com/LLNL/hdbind.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Development of an L-Edge X-ray Absorbance Spectrometer for Monitoring Dissolver Solutions in H-Canyon

Savannah River National Laboratory has developed a monitor to measure plutonium and uranium concentrations in solutions of dissolved nuclear fuel. The monitor will be installed in the sample aisle location for the 6.3D Dissolver in the Savannah River Site’s H-Canyon and used in support of the electrolytic dissolution such as Fast Critical Assembly fuel. The monitor is based on the atomic absorbance of x-rays. Elements are differentiated by the appearance of absorbance features at specific energies of the x-ray spectrum that correspond to L-edge transitions of inner core electrons. Hence, the technique is called L-Edge X-Ray Absorbance Spectroscopy (L-XRAS). The technique is suitable for nuclear fuel processing due to its relative insensitivity to other components of the dissolver solution, such as nitric acid, transition metals (Fe, Cr, Ni, Mn) such as those from stainless steel, particulates, and catalysts and additives. The instrumentation consists of a commercially available x-ray source and detector, a sample cell designed to interface with the airlift sampler associated with H-Canyon Tank 6.3D, and a stainless steel enclosure. SRNL wrote instrument control software and developed chemometric models to interpret x-ray intensity spectra and estimate analyte concentrations and uncertainties in real time.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗