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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Defect-induced formation and frustration-driven multiple magnetic transitions in Gd 2 Co 0.90 Si 2.90

A new ternary compound, Gd 2 Co 0.90 Si 2.90 , has been synthesized in a chemically single phase by deliberately introducing lattice vacancies in the Co and Si sites. The system is characterized by DC magnetization, heat capacity, resistivity and density functional theory (DFT) calculations. Here, a detailed experimental study reveals that the system exhibits an antiferromagnetic transition below T N = 11.3 K followed by spin freezing behaviour below T B ~ 4.8 K. An additional high-temperature magnetic transition could also be detected at T H ~ 150 K, which is short range in character and is associated with defect-induced polarization of the conduction electrons. The spin-glass-like state formation in the system is additionally bolstered by the observation of magnetic relaxation and associated aging phenomena as well as the magnetic memory effect. On the basis of non-equilibrium dynamical behaviour, we argue that the glassy state in this compound favours the hierarchical model over the droplet model. DFT calculations and experimental outcomes establish that the ground state is magnetically frustrated due to the small energy difference between distinct spin configurations having closely spaced ground-state energies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Active Learning of Microgrid Frequency Dynamics Using Neural Ordinary Differential Equations

Accurate frequency modelling of inverter‐based resource (IBR)‐dominated power systems is crucial for ensuring stable, reliable and resilient operations, particularly given their inherent low‐inertia characteristics and fast dynamics that traditional swing equation‐based models inadequately capture. This paper explores neural ordinary differential equations (Neural ODEs) as a computationally efficient, data‐driven framework for modelling power system frequency dynamics, specifically within microgrids integrating high penetrations of distributed energy resources (DERs). The developed neural ODEs framework incorporates a neural network architecture designed to capture input dynamics. By actively perturbing the system with a known signal, the Python‐based neural ODEs framework was trained using measured system states and inputs, without the need for detailed system information. The framework, tested on a model of the Cordova, AK, microgrid, achieved a goodness of fit ranging from 60% to 99% across different state variables and maintained a mean square error in the 10 -6 p.u. range under square and step excitation signals. The proposed approach demonstrated robustness to measurement noise and initial condition variations while maintaining low computational complexity suitable for real‐time power system control applications. Furthermore, transfer learning enabled the neural ODEs model to adapt to the following changes in system topology or generator dispatch, highlighting its effectiveness for dynamic microgrids with frequently evolving configurations and diverse DERs.

Aryal, Tara [South Dakota State Univ., Brookings, ↗
DOE OSTI2025

Laser-driven flash x-ray radiography of a shocked metallic foil

Characterizing hydrodynamic instability evolution in millimeter-scale, high-Z foils is crucial for understanding complex phenomena in high-energy-density physics. Here, we demonstrate a proof-of-concept, laser-driven flash x-ray radiography platform tailored for two-dimensional linear density mapping in shocked high-Z foils. Using chromium (Cr) foils with internal shockwaves (∼100 μm width), our platform achieves a spatial resolution of 59.8 ± 1.4 μm by employing a broadband x-ray source extending into the hundreds of keV range. The setup combines a compound parabolic concentrator cone with a tantalum wire target, a magnetic field to deflect residual transmitted electrons, and a copper casing to shield the sides and rear of the image plate pack. By varying the delay of the short-pulse beam driving the flash x-ray source, we resolve shockwave dynamics, specifically the velocity, position, width, and density profile, within the Cr foil. Reported experimental results are consistent with the corresponding hydrodynamics and radiation transport simulations, which accurately reproduce the measured electron and x-ray source terms. These developments enable the conversion of shockwave radiographs into two-dimensional density maps, enhancing interpretability for hydrodynamic instability evolution applications and validating the simulation approach.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Prototype Modeling for a Light-Trapping Planar-Cavity Enclosed Particle Solar Receiver

Concentrating solar thermal (CST) systems present a promising avenue for affordable and reliable energy production. Solar receivers are key components that determine the efficiency and longevity of these systems. Particle-based solar receivers have emerged as a compelling alternative to traditional technologies, offering several advantages that address limitations in current CST systems. This is especially true as next-generation CST technologies target applications including electricity generation, thermochemical processes, and industrial process heat, many of which necessitate higher operating temperatures than current commercial molten salt systems. Molten-salt thermal energy storage (TES) systems, commonly used in CSP, face challenges related to freezing and corrosion. Particle-based TES systems, in contrast, do not experience these issues, as particles are stable at high temperatures, exceeding 1000 degrees Celsius. This capability allows for a wider range of applications, including those requiring higher temperatures for industrial processes and efficient electricity generation. A novel innovation in particle-based solar receiver technology is the light-trapping planar cavity receiver (LTPCR) configuration developed by NREL. The LTPCR design consists of small cavity-like structures using opaque planar surfaces, enabling efficient capture and absorption of solar energy. A high incident flux concentration at the cavity aperture is absorbed on the receiver walls, and subsequently transferred to particles on the inside of cavities. The particles flow through the system, forming a fluidized bed inside of the receiver panels, effectively capturing the absorbed solar heat. Air is used as a fluidizing medium in this process to enhance particle heat transfer and mixing. The effectiveness of this design lies in its ability to manage solar flux conditions and ensure high solar-to-thermal receiver efficiency. A 100-kW prototype is currently being tested at the King Saud University in Saudi Arabia to assess the receiver performance. A range of modeling analyses for the optical, thermal, and mechanical effects were conducted to assess the performance of the receiver under on-sun conditions. The solar flux resulting from the KSU heliostat field was modeled using NREL SolTrace software and produced up to 600 kW/m2 at the receiver aperture. The solar flux absorbed on the receiver walls was then used within a computational fluid dynamics (CFD) model to predict wall temperature distributions along with radiation and convection loss. A two-phase CFD model was developed for the fluidized bed of silica sand inside the receiver panels to predict local wall-to-particle heat transfer coefficients, particle temperature distributions, and outlet temperature of the particles. We have also conducted analyses to understand the thermomechanical behavior of these innovative enclosed light-trapping solar receivers optimized for particle heating. We used finite element analysis (FEA) to predict the receiver's performance using temperature distributions obtained from CFD and based on the resulting stress profiles, evaluated creep-fatigue damage with a goal of achieving a 30-year service life. Analysis showed a significant impact of the particle-to-wall heat transfer coefficients (HTCs) on receiver performance, with higher HTCs resulting in reduced stress and increased lifespan. For instance, when using Inconel 740H, increasing the HTC from 800 W/m2 K to 1400 W/m2 K increased the creep life from 4,000 hours to over 100,000 hours. This highlights the importance of understanding and optimizing heat transfer in the design of high-efficiency receivers.

14 SOLAR ENERGY↗
DOE OSTI2025

Butterfly valve performance factors using the multiphysics object oriented simulation environment

Butterfly valves are typically used in nuclear reactors to control incompressible fluid flow with high inlet velocities. Performance factors for butterfly valves include the pressure drop across the valve and the loss coefficient from which hydrodynamic torque and flow coefficients can be computed. This work explores a computational fluid dynamics approach for butterfly valve performance factors using the open-source Multiphysics Object Oriented Simulation Environment (MOOSE) framework. While MOOSE is often used in the nuclear energy modeling and simulation community for simulations ranging from fuel characterization to heat pipe simulation, this work employs the MOOSE open-source Navier–Stokes solver capability for simulating butterfly valve performance factors and compares those to experimentally measured results from the Advanced Test Reactor at Idaho National Laboratory at Reynolds numbers in the order of 10 6 for the partially opened configuration. The MOOSE framework results are compared against experimentally measured butterfly valve performance factors across five valve opening angles using meshes with order 10 4 – 10 5 elements. This validation serves to enable MOOSE-based multiphysics simulations incorporating the open-source Navier–Stokes module.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Influence of initial conditions on data-driven model identification and information entropy for ideal mhd problems

Data-driven methods of model identification are able to discern governing dynamics of a system from data. Such methods are well suited to help us learn about systems with unpredictable evolution or systems with ambiguous governing dynamics given our current understanding. Many plasma problems of interest fall into these categories as there are a wide range of models that exist, however each model is only useful in a certain regime and often limited by computational complexity. To ensure data-driven methods align with theory, they must be consistent and predictable when acting on data whose governing dynamics are known. Weak Sparse Identification of Nonlinear Dynamics (WSINDy) is a recently developed data-driven method that has shown promise in learning governing dynamics from data with high noise levels [1]. This work examines how WSINDy acts on ideal MHD test problems as the initial conditions are varied and specifies limiting requirements for successful equation identification. Furthermore, it is hard to recover the governing dynamics from data that emphasize a single dominant behavior. In these low information cases, Shannon information entropy is able to pick up on the redundancies in the data that affect recoverability.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Node Distortions in UiO-66 Inform Negative Thermal Expansion Mechanisms: Kinetic Effects, Frustration, and Lattice Hysteresis

In metal–organic frameworks (MOFs) the interplay between the dynamics of individual components and how these are constrained by the extended lattice can yield unusual emergent phenomena. For the archetypal Zr-MOF, UiO-66, we explore the cooperative dynamics of a Zr-node transformation that gives rise to negative thermal expansion (NTE). Here, using in situ synchrotron X-ray scattering, with powder diffraction and pair distribution function (PDF) analyses, we identify lattice hysteresis and a thermal ramp-rate-dependence of the thermal expansion. Specifically, kinetic trapping of distorted node states formed at high temperature, leads to broad variability in the apparent thermal expansion which ranges from large positive to large negative thermal expansion with coefficients of thermal expansion (CTE) from +45 to –80 × 10 –6 K –1 . Time-resolved relaxation studies at selected temperatures suggest that when equilibrated UiO-66 is intrinsically NTE, with a CTE of –35 × 10 –6 K –1 . Kinetic trapping of the node-distorted state following high temperature activation has broad implications for characterization and applications of these Zr-MOFs; the nonequilibrium node state depends on the thermal history of the sample with quench vs slow cooling likely to impact gas binding, pore volume, and accessible catalytic sites.

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

Toward first principles-based simulations of dense hydrogen

Accurate knowledge of the properties of hydrogen at high compression is crucial for astrophysics (e.g., planetary and stellar interiors, brown dwarfs, atmosphere of compact stars) and laboratory experiments, including inertial confinement fusion. There exists experimental data for the equation of state, conductivity, and Thomson scattering spectra. However, the analysis of the measurements at extreme pressures and temperatures typically involves additional model assumptions, which makes it difficult to assess the accuracy of the experimental data rigorously. On the other hand, theory and modeling have produced extensive collections of data. They originate from a very large variety of models and simulations including path integral Monte Carlo (PIMC) simulations, density functional theory (DFT), chemical models, machine-learned models, and combinations thereof. At the same time, each of these methods has fundamental limitations (fermion sign problem in PIMC, approximate exchange–correlation functionals of DFT, inconsistent interaction energy contributions in chemical models, etc.), so for some parameter ranges accurate predictions are difficult. Recently, a number of breakthroughs in first principles PIMC as well as in DFT simulations were achieved which are discussed in this review. Here we use these results to benchmark different simulation methods. We present an update of the hydrogen phase diagram at high pressures, the expected phase transitions, and thermodynamic properties including the equation of state and momentum distribution. Furthermore, we discuss available dynamic results for warm dense hydrogen, including the conductivity, dynamic structure factor, plasmon dispersion, imaginary-time structure, and density response functions. We conclude by outlining strategies to combine different simulations to achieve accurate theoretical predictions that are based on first principles.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Real-Time GPU-Accelerated OFDR With an Integrated Auxiliary Interferometer

A GPU-accelerated optical frequency domain reflectometry (OFDR) system with an improved integrated auxiliary interferometer is proposed. Unlike conventional approaches that require separate auxiliary interferometers and multiple detection channels, the proposed OFDR system embeds this functionality directly into the signal via an intentional beat component. This enables self-calibration of laser nonlinearity while maintaining a cost-effective hardware configuration. Building on this simplified configuration, the system leverages GPU acceleration with an NVIDIA RTX 4070 Ti to achieve real-time performance, delivering high-throughput signal processing for continuous OFDR interrogation. The signal processing pipeline comprises signal capture, resampling for nonlinearity compensation, and frequency shift computation, all optimized for parallel execution. Hardware benchmarking demonstrates substantial acceleration over CPU implementations, achieving up to a 45× speedup for resampling and frequency shift computations and enabling processing latencies below 30 ms. Thermal response validation is conducted under two complementary scenarios: localized heating using a water bath and cryogenic-temperature conditions using liquid nitrogen. Under localized heating, the system achieves an accuracy of 0.249 °C with a thermal sensitivity of 5.971 GHz/°C, while cryogenic-temperature validation demonstrates a frequency shift response with a sensitivity of 2.383 GHz/°C and an accuracy of 2.04 °C. The high acceleration of the proposed GPU-accelerated OFDR system and its accuracy are achieved by exploiting CUDA-based stride indexing, enabling efficient parallel segmentation and processing of large datasets without additional memory copies. The benchmarking results confirm the robustness, accuracy, and deployability of the proposed OFDR system across a wide temperature range, establishing it as a practical platform for real-time distributed fiber sensing in structurally dynamic environments.

Harb, Salah [Lawrence Berkeley National Laboratory↗
DOE OSTI2025

Coarsening dynamics of Ising-nematic order in a frustrated Heisenberg antiferromagnet

We study the phase ordering dynamics of the classical antiferromagnetic 𝐽 1 −𝐽 2 (nearest-neighbor and next-nearest-neighbor couplings) Heisenberg model on the square lattice in the strong frustration regime (𝐽 2 /𝐽 1 > 1/2). While thermal fluctuations preclude any long-range magnetic order at finite temperatures, the system exhibits a long-range spin-driven nematic phase at low temperatures. The transition into the nematic phase is further shown to belong to the two-dimensional Ising universality class based on the critical exponents near the phase transition. Our large-scale stochastic Landau-Lifshitz-Gilbert simulations find a two-stage phase ordering when the system is quenched from a high-temperature paramagnetic state into the nematic phase. In the early stage, collinear alignments of spins lead to a locally saturated Ising-nematic order. Once domains of well-defined Ising order are developed, the late-stage relaxation is dominated by curvature-driven domain coarsening, as described by the Allen-Cahn equation. The characteristic size of Ising-nematic domains scales as the square root of time, similar to the kinetic Ising model described by the time-dependent Ginzburg-Landau theory. Our results confirm that the late-stage ordering kinetics of the spin-driven nematic, which is a vestigial order of the frustrated Heisenberg model, belongs to the dynamical universality class of a nonconserved Ising order. Interestingly, the system shows no violation of the superuniversality hypothesis under weak bond disorder. The dynamic scaling invariance is preserved in the presence of weak bond disorder. Here, we also discuss possible applications of our results to materials for which vestigial Ising-nematic order is realized.

Antiferromagnets↗
DOE OSTI2026

Atomic-scale vacancy engineering unlocks basal-plane catalytic activity in metallic WSe 2 for reversible oxygen electrocatalysis

Two-dimensional metallic transition metal dichalcogenides offer high electrical conductivity and large surface areas for electrocatalysis, yet their inherent basal planes are catalytically inert. Here, we present an atomic-scale vacancy engineering strategy to activate the basal surfaces of metallic WSe 2 for reversible oxygen electrocatalysis. This approach, based on intentionally designed substitutional metal doping, promotes the spontaneous formation of selenium vacancies while preserving the metallic 1 T′ phase, thereby creating highly reactive and oxygen-affinitive sites. Density functional theory calculations reveal that these vacancy-mediated metal complexes dramatically lower the energy barriers for initial oxygen adsorption, enabling dissociative oxygen adsorption. Operando and ex-situ spectroscopic analyses confirm that vacancy-mediated metal complexes transform into dynamic Se/W-oxide intermediates under operating conditions. Se/W-oxides on the surface experimentally and theoretically prove electrocatalytic activity and reversibility. Applying this strategy in lithium–oxygen batteries, the basal-plane activated WSe 2 shows high discharge capacities (9868 mA h g −1 , corresponding to 3947 mA h g$^{-1}_{cathode}$), impressive cycle retention over 550 cycles at 1000 mA h g −1 , and outstanding rate–capability over a wide current–density range (100–3000 mA g −1 ) during 256 cycles.

2D materials↗
DOE OSTI2024

Conducting polymer-based electrochemical sensors: Progress, challenges, and future perspectives

Conducting polymers are promising due to their unique properties, such as excellent electrical and optical properties, physical and chemical stability, high conductivity, and effective redox properties with high-temperature stability and biocompatibility. Due to these properties, conducting polymers are useful in diverse applications like sensors, batteries, oil industries, biosensors, biomedicines, catalysis, cancer treatment, etc. This review article aims to discuss the recent trends and analysis of conducting polymer-based electrochemical sensors in diverse areas with all required sensor characteristics, such as the derived limit of detection, utilized techniques for the sensing analysis and derived linear dynamic range with the stability of the sensors. Conducting polymers and their nanocomposites-based electrochemical sensors have demonstrated exceptional capabilities towards detecting various biomolecules, heavy metals, pesticides, and viruses like SARS-COV-2. Incorporation of redox mediators, use of conducting hydrogels, and molecular imprinting are promising strategies for better performance of the derived sensor. The article has demonstrated the existing challenges and limitations and provided solutions in the field. In the future, conducting polymers-based electrochemical sensors can be utilized in wearable sensors and integrated with IoT devices for better reach in real-time applications. They can also be made more accessible with precise control and data output by following specific methodologies. Utilizing green and sustainable conducting polymers can be crucial in advancing eco-friendly practices in the future. Conducting polymer-based electrochemical sensors has affectivity in neurochemical and pathogen sensing, which is essential for brain function and mental health.

42 ENGINEERING↗
DOE OSTI2025

Dissipation Pathways in a Photosynthetic Complex

Determining how energy flows within and between molecules is crucial for understanding chemical reactions, material properties, and even vital processes such as photosynthesis. While the general principles of energy transfer are well established, elucidating the specific molecular pathways by which energy is funneled remains challenging, as it requires tracking energy flow in complex molecular environments. Here, we demonstrate how photon excitation energy is partially dissipated in the light-harvesting Fenna–Matthews–Olson (FMO) complex, mediating the excitation energy transfer from light-harvesting chlorosomes to the photosynthetic reaction center in green sulfur bacteria. Specifically, we isolate the contribution of the protein and specific vibrational modes of the pigment molecules to the energy dynamics. For this, we introduce an efficient computational implementation of a recently proposed theory of dissipation pathways for open quantum systems, based on second-order perturbation theory in the electronic couplings. Using it and a state-of-the-art FMO model with highly structured and chromophore-specific spectral densities, we demonstrate that energy dissipation is dominated by low-frequency modes (<800 cm –1 ) as their energy range is near-resonance with the energy gaps between electronic states of the pigments. We identify the most important modes for dissipation to be in-plane breathing modes (∼200 cm –1 ) of the bacteriochlorophylls in the complex. Conversely, far-detuned intramolecular vibrations with higher frequencies (>800 cm –1 ) play no role in dissipation. Interestingly, the FMO complex first needs to borrow energy from the environment to release excess photonic energy, indicating that the energy exchange between the system and thermal environment is not strictly unidirectional in time but involves a transient thermally activated step. Beyond their fundamental value, these insights can guide the development of artificial light-harvesting devices and, more broadly, engineer environments for chemical and quantum control tasks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Expanded View of NMR Spin–Lattice Relaxation in Fluorine-Containing Ionic Liquids

Fluorine-containing anions are widely used in ionic liquids due to their unique physicochemical properties. However, the local dynamics of both cations and anions and their associated relaxation mechanisms remain incompletely understood. Here, we present a 1 H and 19 F spin–lattice relaxation rate (R1) study as a function of frequency over a broad frequency range from 30 kHz to 800 MHz for ionic liquids containing BF 4 – , PF 6 – , TFSI – , and FSI – anions and EMIM + cation. By combining experimental R 1 H and R 1 F NMR dispersion (NMRD) profiles with relaxation models for both dipolar spin interactions and chemical shift anisotropy (CSA) contributions, we demonstrate that CSA is needed to accurately describe the R 1 F relaxation behavior above ∼300 MHz, the extent of which depends on the anion structure. These findings challenge the long-standing assumption that dipolar contribution is the main source of 19 F relaxation in these systems and highlight the importance of including CSA to accurately interpret 19 F relaxation in ionic liquids, particularly at high frequencies. This work provides new insights into the molecular dynamics of fluorine-containing species.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

In-situ probing of the Fischer-Tropsch reaction on Co single crystal surfaces up to 1 bar

The surface chemistry of the Fischer-Tropsch catalytic reaction over Co has still several unknows. Here, we report an in-situ X-ray photoelectron spectroscopy study of Co$(0001)$ and Co$(10\bar{1}4)$, and in-situ high energy surface X-ray diffraction of Co$(0001)$ during the Fischer-Tropsch reaction at 0.15 bar - 1 bar and 406 K - 548 K in a H 2 /CO gas mixture. We find that these Co surfaces remain metallic under all conditions and that the coverage of chemisorbed species ranges from 0.4–1.7 monolayers depending on pressure and temperature. The adsorbates include CO on-top, C/-C x H y and various longer hydrocarbon molecules, indicating a rate-limiting direct CO dissociation pathway and that only hydrocarbon species participate in the chain growth. The accumulation of hydrocarbon species points to the termination step being rate-limiting also. Furthermore, we demonstrate that the intermediate surface species are highly dynamic, appearing and disappearing with time delays after rapid changes in the reactants’ composition.

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

ELM-free enhanced D α H-mode with near zero NBI torque injection in DIII-D tokamak

Enhanced D α H-mode (EDA H-mode), an ELM-free H-mode regime, and the concomitant quasi-coherent mode (QCM) are explored in neutral beam heated, lower single null plasmas with near zero external torque injection. This regime exhibits good energy confinement (H 98y2 ~ 1) with β N ~ 2, high density, regime access at low input power, and no ELMs. New time–resolved measurements of electron and ion density, temperature, plasma rotation, and radial electric field as well as turbulence, flows, thermal and particle transport, and linear instability calculations examining the dynamics of the QCM are presented. Measurements using multiple fluctuation diagnostics reveal the QCM to be a separatrix spanning mode, peaking just inside the separatrix, existing in a wide range of k ⊥ ρ s ~ 0.1–1.2 with multiple harmonics, and propagating with a very small phase velocity in the plasma frame, where k ⊥ is the binormal wavenumber and ρ s is the ion sound radius. Linear gyrokinetic simulations of this EDA H-mode discharge with CGYRO indicate that the trapped electron mode (TEM) and electron temperature gradient mode are the dominant instabilities in the radial region where QCM is also unstable. Qualitative analysis indicates that the properties of TEM are consistent with the experimentally observed characteristics of the QCM. These similarities suggest that the QCM is consistent with a TEM instability existing in the edge region of the EDA H-mode plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Test and characterization of finely segmented pixel CZT detectors for future hard x-ray missions

The NuSTAR (Nuclear Spectroscopic Telescope Array) mission was launched in 2012, and it has successfully deployed the first orbiting telescopes to focus high energy X-ray (3 - 79 keV) light, providing a wealth of new information on high-energy X-rays sources. Follow-up missions, such as the proposed HEX-P, BEST, and FORCE, could perform a deeper black hole census providing a more refined measurement of black hole spins, allowing for greater knowledge about supermassive black holes. Here, these missions are motivated by the recent breakthroughs in the hard X-ray mirror technologies, where mirrors, either made of monolithic silicon segments, or made directly or via replication of shells, demonstrate the feasibility of making hard X-ray mirrors with angular resolutions of 5-10 arc-seconds Half Power Diameter (HPD) compared to the NuSTAR’s 1 arc-minute HPD. Such a high angular resolution requires matched detectors with higher degree of segmentation to fully benefit from the achievable improved spatial resolution. In the above framework, the HEXID ASIC, a novel pixelated front-end suitable for reading out a finely segmented CZT sensor with 150 μm pixel pitch in a hexagonal arrangement has been developed. This readout pixelated chip is capable of processing photon-generated charge packets over a large dynamic range (from 2 keV up to 180 keV), while keeping a low input noise (ENC <20 e - ). In this work, the initial characterization of the ASIC prototype will be presented.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Transplatformer: translating toxicogenomic profiles between generations of platforms

Background Transcriptomic profiling technologies have advanced the analysis of biological and toxicological responses. However, substantial differences in probe design, dynamic range, gene coverage, and preprocessing pipelines across platforms introduce artifacts that limit cross-study integration and hinder the reuse of historical datasets. We aim to develop computational methods for accurate cross-platform translation to maximize the value of legacy resources. Results We present TransPlatformer a deep learning framework for translating gene expression profiles across heterogeneous toxicogenomics platforms. TransPlatformer employs a novel attention-based architecture to map high-dimensional fold-change vectors from legacy microarray technologies to current platforms. Models are trained and evaluated using DrugMatrix, spanning three technological generations. We investigate mixed-tissue, single-tissue, and cross-tissue training paradigms and benchmark performance against multilayer perceptron and matrix-completion baselines. In mixed-tissue training, TransPlatformer achieves a greater than 50% reduction in mean absolute error (0.043 vs. 0.09) and nearly doubles Pearson correlation ( ≈ 0.71 vs. 0.37) relative to baseline methods. Importantly, TransPlatformer preserves rare but biologically meaningful over- and under-expressed signals, with mean absolute error below 0.22. Single-tissue models yield further improvements for well-represented organs, such as a 10% reduction in liver mean absolute error, while underscoring the need for data augmentation strategies in low-sample tissues.ra Conclusions TransPlatformer provides an effective and scalable computational solution for cross-platform transcriptomic translation. By enabling biologically faithful harmonization of gene expression data, the proposed approach facilitates the reuse of legacy toxicogenomics datasets, enhances downstream biomarker discovery, and supports more reproducible predictive modeling in toxicology.

59 BASIC BIOLOGICAL SCIENCES↗