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DOE OSTI2026

Collaborative: Fundamental studies of how water influences the synthesis and behavior of zeolite catalysts for reactions in the circular carbon economy (Final Technical Report)

This project established a computational framework to predict and interpret how synthesis conditions control active site location in MFI zeolites and how those site distributions influence catalytic reactivity. The Hibbitts Group led the theoretical effort, applying periodic DFT calculations to quantify (i) SDA–framework–heteroatom interactions during crystallization and (ii) the energetics and mechanisms of arene methylation reactions within distinct MFI environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Storage Field Development Plan: One Earth Energy

This Storage Field Development plan presents the Storage Complex characterization results, construction, monitoring, and operational plans, and costs associated with the proposed One Earth Sequestration Carbon Capture and Storage (OES-CCS) site in McLean County, Illinois, near Gibson City. The proposed storage complex, known as the Mt. Simon Storage Complex, comprises the Cambrian Mt. Simon Sandstone reservoir and the primary seal, the Cambrian Eau Claire Formation. The lowermost Underground Source of Drinking Water (USDW) identified for the site is the Ordovician St. Peter Sandstone. Geologic characterization of the Mt. Simon Storage Complex at the OES-CCS site was performed by the Illinois Storage Corridor CarbonSAFE Phase III project, which also prepared and submitted three UIC Class VI applications to construct three injection wells; the permit applications were submitted and are in the federal EPA review process. A characterization well, OEE #1, was drilled to collect site-specific data. These data were analyzed and used to develop the UIC Class VI applications. The OEE #1 well will be converted to an in-zone monitoring (IZM) well for the injection phase. The proposed buildout for the OES-CCS site includes (1) three injection wells (OES #1, OES #2, and OES #3), (2) two IZM wells, (3) two above confining zone (ACZ) monitoring wells, one of which will be used to monitor the lowermost USDW, (4) capture and compression facilities, and (5) transportation facilities, i.e., pipelines. A pre-operational testing program was proposed in the Class VI permit application and will be employed at the site pending approval. Additional pre-injection (baseline), syn-injection, and post-injection monitoring and site care procedures will be followed by OES to ensure that injection activities are protective of human health and the environment. Injection is scheduled to begin in 2025, distributed across the three injection wells in accordance with the permit operating conditions. One Earth Sequestration intends to inject up to 90 million tonnes of CO 2 over a period of approximately 20 years. Injection will begin at approximately 0.5 million tonnes of CO 2 annually and ramp up to a maximum of 4.5 million tonnes annually. Daily injection rates are expected to range from 1,400 to 1,500 tonnes per day initially and reach a maximum of approximately 4,225 tonnes per day, depending on site geology and injectivity at each injection well location, and CO 2 availability. The costs associated with the OES-CCS project include pre-operational costs (e. g. additional seismic data acquisition and well drilling), capture and transportation facility and equipment costs, predicted field operating expenditures (OpEx), and decommissioning and post-injection site care (PISC) costs. The risks associated with project activities, such as site construction, injection operations, and verification of secure storage were evaluated, and mitigation strategies proposed to alleviate those risks.

09 BIOMASS FUELS↗

DOE OSTI2025

Exploring the Effects of Varying Pre-Chamber Geometry in a Heavy-Duty Natural Gas Optical Engine under Dilution Conditions

Pre-chamber combustion is an advanced ignition strategy that has been shown to enhance spark ignition (SI) combustion stability in natural gas (NG) engines by providing distributed ignition sites from turbulent jets and enhancing main-chamber turbulence. Pre-chamber combustion has been proven especially advantageous compared to SI in ultra-lean and dilute operating conditions. This work involves experimental investigation of the effects of varying passive pre-chamber nozzle configuration on pre-chamber and main chamber combustion under simulated exhaust gas recirculation (EGR) dilution (0 and 20%) conditions in a heavy-duty, single-cylinder, optically accessible NG engine at stoichiometric fuel-air ratio. Pre-chamber nozzle configurations include four pre-chambers with constant nozzle area to pre-chamber volume ratio (A/V) with different nozzle sizes and orientations and one configuration with larger nozzles. The optical engine is operated in a skip-fire sequence consisting of 18 motored cycles followed by two consecutive fired cycles to elucidate the effect of combustion residuals (internal EGR) on combustion evolution. Pressure-based diagnostics are used to monitor pre-chamber and subsequent main chamber combustion, and optical diagnostics include high-speed OH* chemiluminescence to visualize the development of pre-chamber jets and the resulting ignition of the main chamber charge. Heat release analysis of the in-cylinder pressure data indicates that a faster pre-chamber pressure rise does not always translate into faster main-chamber combustion. The pre-chamber with the smallest nozzle diameter produced the highest pre-chamber pressure rise and fastest combustion under non-diluted conditions. However, dilution delays the main chamber ignition for smaller nozzles despite a comparable rise in pre-chamber pressure compared to configurations with larger nozzles. This effect is more pronounced for cycles with in-cylinder combustion residuals in addition to external dilution. Additionally, it was observed that pre-chambers with swirling nozzles have a faster pressure rise in the pre-chamber and main chamber under dilute conditions. Optical diagnostics suggest that the main reason for the delay between the pre-chamber pressure rise and main-chamber combustion lies in jet quenching and delayed re-ignition, which can even lead to misfire if jets emitted from small nozzles combined with dilution fail to re-ignite.

Dhotre, Akash [University Of Minnesota-Twin Cities↗

DOE OSTI2026

Machine learning-based interatomic potential development and phase transition analysis of ferroelectric hafnium dioxide

The ferroelectric phase (𝑃⁢𝑐⁢𝑎⁢2 1 , which is in orthorhombic symmetry) of hafnium dioxide (HfO 2 ) has gained much attention due to its potential applications in nanoelectronics and advanced memory devices. However, its complex phase behavior under external stimuli, such as pressure and temperature, remains a subject of intense investigation. This study focuses on developing a machine learning-based interatomic potential (MLIP) that is trained with data from density-functional theory (DFT) calculations to simulate phase transitions and mechanical properties of HfO 2 . The developed MLIP predicts lattice parameters, equations of state, bulk and shear moduli, and elastic constants that closely align with DFT predictions for several phases and at various pressures. Once validated, the MLIP is used to investigate the phase transitions of ferroelectric HfO 2 (𝑃⁢𝑐⁢𝑎⁢2 1 ) under both isobaric and constant stress conditions at elevated temperatures ranging from 200 to 2500 K. We used several complementary methods, including local symmetry identification, radial distribution function, and x-ray diffraction characterization, to identify interesting phase transitions among several competitive hafnia phases predicted from our simulations. The suggested methods uniformly reveal that under pure deviatoric condition, the system favors a transition from the orthorhombic 𝑃⁢𝑐⁢𝑎⁢2 1 phase to a tetragonal (𝑃⁢4 2 /𝑛⁢𝑚⁢𝑐) phase, whereas a zero stress condition drives the system from the 𝑃⁢𝑐⁢𝑎⁢2 1 phase to another orthorhombic (𝑃⁢𝑏⁢𝑐⁢𝑛) phase. These findings provide crucial insights into stress and temperature-induced phase behavior of hafnia, guiding future experimental and theoretical studies for optimizing hafnia-based ferroelectric devices.

Ferroelectric HfO2↗

DOE OSTI2026

Enabling Grid-Forming Control with Fault Ride-Through in Unbalanced Distribution Networks

Distribution networks are often unbalanced, causing oscillatory responses in inverter control designed for balanced conditions. Here, to address this problem, this paper proposes a novel time-domain transformation appropriate for inverter control and enables the decomposition of three-phase unbalanced signals into constant positive and negative components. Relations useful for calculating unbalanced active and reactive power are derived from first principle, providing insight into vector products of unbalanced three-phase signals. Furthermore, a grid-forming control effective under unbalanced conditions is developed, which delivers superior performance while meeting UNIFI1 specifications for grid-forming control under unbalanced conditions. specifications applicable to category 4 inverter-based resource, like setting and regulating frequency/voltage, providing voltage support, sharing active power, injecting negative sequence current, and riding through faults. A current limiter is proposed for safe fault ride-through and integrates with the grid-forming control featuring frequency/voltage droop controllers and current and voltage control loops. The transformation of interconnected inverters is formulated and stability of the proposed control analyzed to support robust parameter selections. The effectiveness of the proposed transformation and grid-forming control is demonstrated through analytical results and real-time simulation of a IEEE 123 distribution network on the Real-Time Digital Simulator. Comparison with existing methods shows that the proposed strategy satisfies the UNIFI specifications with a much better performance.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Measurement of Local Impedance Characteristics of In-Plane PEM Electrolyzer Component Features via Segmented Cell

Segmented cells are a class of advanced diagnostic devices that enable the measurement of current distribution within the active area of an electrochemical cell, allowing for the evaluation of localized impacts from operating conditions, flow fields and component inhomogeneities. Segmented cell devices have been applied to support R&D efforts for the advancement of polymer electrolyte membrane fuel cell technologies and more recently proton exchange membrane water electrolysis (PEMWE). Beyond current density distributions, segmented cells have been successfully deployed to collect the distribution of other relevant parameters such as high frequency resistance and electrode potentials. Very recently, a promising impedance method has been reported for water electrolysis where a one-dimensional segmented cell is coupled to a multichannel potentiostat, to enable the measurement of local cell impedances, further expanding the diagnostic capabilities of the segmented cell. In this study, we will present recent efforts to accurately measure local impedance characteristics for a PEMWE cell using a two-dimensional segmented cell device coupled with a multichannel potentiostat. The distribution of local resistances, i.e. high frequency, charge transfer, mass transport and catalyst layer, and iR-free overpotentials were successfully measured after eliminating sources of random and systematic error. We will discuss the application of this diagnostic on a cell containing a 1 cm feature simulating an ionomer skin. The results from these tests give insights if such an irregularity needs to be classified as a defect, and highlight the usefulness of coupling impedance spectroscopy with segmented cells for holistic spatial diagnostics of electrochemical devices.

08 HYDROGEN↗

DOE OSTI2025

A dynamic pricing method to manage the impact of EV charging on the grid using RL

This work addresses the challenge of managing electrical vehicle (EV) charging loads on distribution feeders with the increase in deployment of fast charging stations. To mitigate the adverse impacts on feeder health, a novel dynamic grid-informed pricing approach is proposed. This approach leverages reinforcement learning (RL) to determine hourly charging prices based on real-time grid conditions. A synthetic environment was developed to train the reinforcement learning agent. A model of an IEEE 34-bus distribution feeder with EV charging stations has been developed in OpenDSS utilizing Caldera for realistic EV charging profiles. Test cases demonstrate that the dynamic pricing strategy achieves higher energy delivery to the EV end user at a lower cost compared to constant pricing methods, while lowering voltage deviations and congestion. This approach offers more granular price adjustments, responding dynamically to feeder conditions and potentially improving grid stability and efficiency. The communication architecture to implement this dynamic pricing method is described. This research contributes to the development of smart grid-informed charging solutions that can reduce the cost of charging to the end user while also helping the grid.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Violation of energy conditions and the gravitational radius of the proton

The energy-momentum tensor (EMT) of the proton encodes fundamental information about its mass, pressure, and shear distributions. Using recent lattice QCD data for the gravitational form factors, we show that the Breit-frame Wigner EMT may be of Hawking-Ellis type IV in the proton’s core. Such EMT violates all pointwise energy conditions and lacks a causal rest frame so that the usual mechanical picture fails at short distances. We define the —a new hadronic observable—marking the scale where the EMT becomes ordinary (type I) and the classical interpretation is restored. We also derive from the averaged null energy condition nonperturbative, model-independent quantum field theory constraints on gravitational form factors.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Resolving local ordering and structure in Mn x Ge 1- x Te alloys through thermodynamic ensembles of pair distribution functions

Characterizing local bonding environments in complex materials is essential for understanding and optimizing their properties. Equally as important is the ability to predict local motifs as a function of synthesis conditions, enhancing chemists’ ability to design properties into materials. In this study, we present an approach to leverage statistical mechanics to generate temperature- and energy-informed ensemble averaged pair distribution functions (PDFs). This method, which we have named Thermodynamic Ensemble Averages of PDFs for Ordering and Transformations (TEAPOT), utilizes density functional theory (DFT) to relax supercells while incorporating energetic penalties for local order, enabling accurate and computationally efficient analysis of local structure. We apply this method to the neutron PDF measurements of the pseudobinary MnTe–GeTe (MGT) alloy, demonstrating its capability to resolve complex local distortions and chemical ordering. Our results reveal detailed insights into phase transformations and local distortions driven by Mn substitution. For compositions that globally present as rock salt, our analysis reveals that Ge coordination geometry is heavily impacted by synthesis temperature. We propose that high temperature synthesis conditions promote a lowered Ge polyhedra distortion, promoting high charge carrier mobility due to the alignment of local and global structure. Incorporating statistical mechanics and computation into experimental analysis thus guides synthesis of tailored local structure.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Spatiotemporal and Statistical Mapping of Transition Metal Equilibria in Alkaline Media

Transition metal dissolution and redeposition (D/R) kinetics in alkaline media play a critical role in various chemical and electrochemical processes. Competitive reaction kinetics between different transition metals can modulate individual metal behavior in these processes. To date, these phenomena have remained largely unmeasured, and even when captured, they are difficult to statistically characterize due to their dynamic nature, simultaneous occurrence, and spatially heterogeneous nature. Here, in this study, we develop a statistical analysis framework based on in situ and operando X-ray fluorescence microscopy (XFM) to investigate the relative D/R kinetics of multiple transition metals in alkaline media. By employing statistical analysis, we quantify the spatial distribution of D/R species and assess the rate at which the system reaches equilibrium under varying reaction conditions. We show that pH does not simply change the rate of dissolution and redeposition, but reorganizes the cross-element kinetic correlations among Ni, Fe, and Mn and accelerates the spatial equilibration of D/R events, as quantified through correlation analysis, reaction-rate estimation, probability function distributions, and texture-based monitoring statistics. Additionally, we demonstrate how modifying the solvent environment can influence D/R kinetics, providing a pathway for tuning materials synthesis and process optimization. Our study offers valuable insights into the complex interplay between different transition metals and provides a reliable statistical framework for spatial analysis of diverse imaging data sets, enabling deeper extraction of latent information across multiple modalities.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Raman scattering of rhenium for secondary pressure calibration

With the increasing number of 100 s GPa experiments in the diamond anvil cell (DAC), improved accuracy in secondary pressure calibrations to extreme pressures is essential. The rhenium equation of state has been proposed as a pressure calibrant via x-ray diffraction with potentially broad applications as it is commonly used as a gasket material in DAC experiments. In this work, we conducted Raman spectroscopy experiments on rhenium in the DAC and report the pressure shift of the E2g mode, a refined high-pressure C44 and mode-Grüneisen parameter above 200 GPa. We used flat, beveled, and toroidal diamond anvils under quasi-hydrostatic and non-hydrostatic conditions. By measuring the E2g mode from the culet edge to the center, we analyzed pressure distribution based on culet type and distance from the anvil center. The shift in the E2g mode can be expressed as a function of pressure, and diamond edge measurements appear reliable across all anvil types. Comparing the center and edge pressures reveals anvil cupping, offering insights into predicting or preventing anvil failure during materials properties measurements at extreme conditions.

Diamond anvil cells↗

DOE OSTI2024

Adaptive Protection and Validated Models to Enable Deployment of High Penetrations of Solar PV (PV-MOD)

The availability and validation of various PV models in commercial tools differ, with some models not yet thoroughly validated for advanced inverter functionalities and reliable performance under weak system conditions. Many existing models do not fully incorporate new inverter control functions, which can affect system stability. The increasing deployment of solar PV and other inverter-based resources (IBRs), including distributed energy resources (DERs), is influencing the reliable operation of protection schemes in distribution systems and microgrids. Emerging adaptive protection schemes (APS) offer new opportunities for protecting these systems during varying configurations and DER operating conditions, though their demonstration and validation remain limited. Adaptive protection schemes face similar challenges, as they are typically designed for specific configurations. There is a growing need for tools and methodologies to streamline the deployment of adaptive protection for safe and reliable DER integration. The project main objective was to develop and validate high-fidelity generic models of solar PV facilities for stability, protection, EMT, and QSTS analyses. This objective was achieved, and these models can now be integrated into commercial software tools, enabling utilities, vendors, and developers to study high-penetration PV systems more confidently. The project also demonstrated advanced applications of these models, including the design and deployment of adaptive protection schemes in high-penetration field applications and microgrids, supporting grid safety and reliability. Several milestones were reached by the end of the project. A sophisticated inverter test plan was developed, and inverters representative of the North American marketplace were selected. EPRI and NREL tested various inverters, conforming to IEEE standards. Improvements were made to existing generic models of IBR units, IBR plants, and aggregated feeders for various analyses. The first generic electromagnetic transient (EMT) model for a solar PV plant was developed, conforming to IEEE Std 2800™-2022 and validated against laboratory measurements of a 2.2 MVA large-scale battery energy storage system (BESS) inverter. That model was then used to produce reference responses illustrating examples of validated and verified IBR plant models that pass or fail tests for technical minimum capability and performance as specified in the IEEE standard. The developed, tested, and validated generic models can be used for transmission planning, stability assessments, expansion planning, and evaluating potential future IBR interconnection requirements. They can also support interconnection screens and conformity assessments of IBR plants, including solar PV. The project significantly contributed to the ongoing standardization and model-based representation and verification of IBR responses. The project further addressed challenges of common distribution protection schemes with increasing deployment of DER by developing, validating, and demonstrating adaptive protection schemes (APS) that can improve the reliable and safe integration of DER into distribution systems. New APS were designed using improved DER models for three common distribution systems: a radial feeder, a meshed network, and a microgrid. Modeling and hardware-in-the-loop (HIL) testing of the APS were conducted, successfully showing their effectiveness and selectivity. Proof-of-concept field demonstration was achieved for two APS, i.e., one on a radial feeder and another one in a microgrid. Field demonstration could not be achieved for the APS on a meshed network, primarily due apprehension of one utility partner and also due to limited access to the protective algorithms in the network protectors. Guidelines developed from the lessons learned in the project lay out the general process followed in the design, installation, and commissioning of APS for various distribution systems. Distribution utility partners’ apprehension about field demonstration of the new APS were addressed—with varying success—by taking a stepped risk-management approach of modeling of a wide range of sensitivities first, performing in-depth proof-of-concept testing in the laboratory including HIL next, and finally deliberately implementing and commissioning the actual protection equipment and algorithms into parts of—or in parallel operation to—the three real distribution systems. Future work should include pilot projects that further show the acceptable performance of the developed APS before these schemes be rolled out more widely. Inclusion of both utility and original equipment manufacturers (OEMs) in future projects could increase chances of successful field demonstration. Despite challenges in achieving the field demonstration goal of the project for all three APS, the research significantly contributed to the innovation of adaptive protection solutions for scalable and reliable DER integration into distribution systems. This project significantly enhances the understanding of the impact of using appropriate inverter models on distribution and transmission (T&D) systems. By addressing the limitations of existing generic models, the project introduces high-fidelity models for stability, protection, electromagnetic transient (EMT), and quasi-static time series (QSTS) analyses. These models, integrated into commercial software tools, enable utilities, vendors, and developers to confidently study high-penetration PV systems. The project also demonstrates advanced applications, including adaptive protection schemes (APS) for distribution systems and microgrids, ensuring grid safety and reliability. The technical effectiveness and economic feasibility of the methods are evident through the development and validation of sophisticated inverter test plans and the selection of representative inverters. Testing by EPRI and NREL on retail, commercial, and utility-scale inverters, conforming to IEEE standards, underscores the robustness of the models. Improvements to existing generic models for various analyses further enhance their validity and applicability. The project also identifies gaps in common distribution protection schemes and designed new APS using improved DER models, demonstrating their effectiveness through modeling and hardware-in-the-loop (HIL) testing. The project’s benefits to the public are manifold. By advancing the standardization and model-based representation of IBR response, it supports transmission planning, stability assessments, and future IBR interconnection requirements. The generic models can facilitate better communication between transmission planners and developers, supporting expected IBR plant capability and performance. Additionally, the development of APS for radial feeders, meshed networks, and microgrids supports the integration of distributed energy resources (DERs) into distribution systems, enhancing grid reliability and safety. The project’s emphasis on thorough testing and simplicity in design ensures practical and scalable solutions for DER integration.

14 SOLAR ENERGY↗

DOE OSTI2025

A Dynamic Pricing Method to Manage the Impact of EV Charging on the Grid Using RL

EV charging, dynamic pricing, grid-informed chargi↗

DOE OSTI2026

Magnetic flux distribution, quasiparticle spectroscopy, and quality factors in Nb films for superconducting qubits

Niobium is a practical material platform for superconducting microwave circuits; however, device-level performance can vary significantly depending on film growth and processing conditions. We compare three epitaxial Nb films grown on $c-$plane sapphire substrates under nominally identical conditions, except for the deposition temperature. To correlate internal quality factors, $Q_{\mathrm {i}}$, with material properties, we combine magneto-optical imaging of magnetic flux distribution with quasiparticle spectroscopy via measurements of the London penetration depth, $λ(T)$. In the low-$Q_{\mathrm i}$ film, there is a lesser ability to screen the magnetic field and an irregular temperature variation of $λ(T)$, implying the existence of localized in-gap states. High $Q_{\mathrm i}$ films show the opposite trend. We conclude that our measurements provide an efficient method for characterizing and optimizing superconducting films for quantum informatics applications.

Datta, Amlan [Ames Lab; Iowa State U.]↗

DOE OSTI2024

Revealing Decision Conservativeness Through Inverse Distributionally Robust Optimization

This paper introduces Inverse Distributionally Robust Optimization (I-DRO) as a method to infer the conservativeness level of a decision-maker, represented by the size of a Wasserstein metric-based ambiguity set, from the optimal decisions made using Forward Distributionally Robust Optimization (F-DRO). By leveraging the Karush-Kuhn-Tucker (KKT) conditions of the convex F-DRO model, we formulate I-DRO as a bi-linear program, which can be solved using off-the-shelf optimization solvers. Additionally, this formulation exhibits several advantageous properties. We demonstrate that I-DRO not only guarantees the existence and uniqueness of an optimal solution but also establishes the necessary and sufficient conditions for this optimal solution to accurately match the actual conservativeness level in F-DRO. Furthermore, we identify three extreme scenarios that may impact I-DRO effectiveness. Our case study applies F-DRO for power system scheduling under uncertainty and employs I-DRO to recover the conservativeness level of system operators. Numerical experiments based on an IEEE 5-bus system and a realistic NYISO 11-zone system demonstrate I-DRO performance in both normal and extreme scenarios. An extended version of this paper with additional analyses is available at li2024revealing.

distributionally robust optimization↗

DOE OSTI2026

Reproducible benchmark for the SNAP 8 experimental reactor at operating conditions

This work presents fully reproducible multiphysics benchmark models of the Systems for Nuclear Auxiliary Power (SNAP) 8 Experimental Reactor at operating conditions with coolant flow. Wet experiment (with coolant, at power) validation benchmarks are presented using both deterministic (Serpent-Griffin) and Monte-Carlo (OpenMC-Cardinal) multiphysics frameworks coupled with thermal-hydraulic solvers in MOOSE. Reactivity coefficient measurements including fuel temperature, isothermal temperature, and power coefficients show good agreement with experiments, with discrepancies within experimental uncertainty. Reactivity worth experiments for coolant, samarium, and xenon poisoning are reproduced with differences under 200 pcm. Comparison between Serpent-Griffin and OpenMC-Cardinal frameworks reveal multiphysics coupling introduces positive reactivity effects (100-200 pcm) compared to uniform temperature and density fields at nominal operating conditions. Comparison between Serpent-Griffin and reference Serpent solution shows that power distributions maintain consistent radial and axial peaking behavior. All models, assumptions, thermophysical and thermomechanical properties, and material definitions are thoroughly documented with cited references; model inputs and model generating scripts are stored in the snapReactors GitHub repository.

SNAP↗

DOE OSTI2026

Correlation between microstructure and residual stress formation in friction stir welded armor steels characterized by neutron diffraction

Friction stir welding (FSW) is a solid-state joining process that minimizes the heat-affected zone (HAZ) compared with fusion-based arc welding, making it well suited for joining martensitic armor steels where hardness and ballistic resistance are critical. This study investigates residual stress formation in three defect-free FSW butt-joint configurations relevant to armored-vehicle fabrication: similar rolled homogeneous armor (RHA–RHA, Case 1), similar high-hardness armor (HHA–HHA, Case 2), and dissimilar HHA–RHA (Case 3) joints produced under temperature-controlled conditions (770 °C). Neutron diffraction was employed to quantify the magnitude and spatial distribution of residual stresses in the longitudinal, transverse, and normal directions and to correlate them with weld microstructure and hardness. Tensile residual stresses were concentrated in the softened HAZ, reaching approximately 300 MPa for Case 2 and 400 MPa for Case 1 (≈50–70 % of the base-metal yield strength; ∼581 MPa for RHA and ∼566 MPa for HHA), while compressive residual stresses dominated the stir zone. The spatial extent of tensile stresses scaled with the width of the softened HAZ, which was largest in the dissimilar HHA–RHA joint and smallest in the HHA–HHA joint. Full-width-at-half-maximum (FWHM) analysis revealed low microstrain in overtempered HAZ regions and high microstrain in the stir zone associated with severe plastic deformation and fresh martensite formation. This work demonstrates that residual stress evolution in FSW of martensitic armor steels is governed not primarily by peak temperature or thermal contraction, as inferred from fusion-welding analogies, but by the competition between transformation-induced volumetric expansion and tempering-induced stress relaxation. The relative dominance of these mechanisms is shown to depend on alloy hardenability and local thermal history, leading to more extensive HAZ softening and broader tensile stress regions in the lower-hardenability RHA steel. These findings establish a transferable mechanistic framework for optimizing solid-state joining strategies in high-strength steels and other transformation-hardening alloys beyond armor applications.

Friction stir welding↗

DOE OSTI2025

Fast jet tagging with MLP-Mixers on FPGAs

We explore the innovative use of MLP-Mixer models for real-time jet tagging and establish their feasibility on resource-constrained hardware like FPGAs. MLP-Mixers excel in processing sequences of jet constituents, achieving state-of-the-art performance on datasets mimicking Large Hadron Collider conditions. By using advanced optimization techniques such as High-Granularity Quantization and Distributed Arithmetic, we achieve unprecedented efficiency. These models match or surpass the accuracy of previous architectures, reduce hardware resource usage by up to 97%, double the throughput, and half the latency. Additionally, non-permutation-invariant architectures enable smart feature prioritization and efficient FPGA deployment, setting a new benchmark for machine learning in real-time data processing at particle colliders.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗