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DOE OSTI2024

A Generation-Storage Coordination Dispatch Strategy for Power System Based on Causal Reinforcement Learning

In the backdrop of global energy transformation, power systems integrating high proportions of renewable energy sources are facing unprecedented challenges in operational stability and dispatch efficiency. To address these challenges, this study introduces a generation-storage coordination real-time dispatch strategy based on Causal Power System Dynamic Reinforcement Learning (CPSDRL). Diverging from traditional reinforcement learning approaches, CPSDRL innovatively incorporates causal inference within the state prediction model - the crux of model-based reinforcement learning - thereby establishing the Power Causal Dynamic Model (PCDM). Assisted by the prior knowledge of power systems, the model significantly enhances prediction accuracy and reliability through a two-stage training process. Utilizing PCDM, this study further applies a direct policy search algorithm to optimize the real-time dispatch strategy. Experimental results indicate that the proposed method improves the stability of generation-storage coordination real-time dispatch and exhibits competitive advantages in sample efficiency and computational speed, compared to traditional model-based and model-free reinforcement learning algorithms. This method is expected to enhance the practicality and adaptability of causal reinforcement learning techniques in power system scheduling and control.

causal reinforcement learning↗

DOE OSTI2024

Air Classification of Forestry Residues for Fast Pyrolysis

Understanding critical biomass attributes through efficient fractionation is crucial for advancing sustainable pyrolysis for renewable energy and chemical production. This study investigates the intricate relationship between biomass preprocessing and pyrolysis product yields, employing the air classification technique for the treatment of loblolly pine residues with varying moisture content. A comprehensive exploration of the physicochemical properties of air-classified loblolly pine informs a sophisticated pyrolysis simulation model. Given the complex and multifaceted nature of biomass pyrolysis, operating across diverse temporal and spatial scales, a pyrolysis kinetics-based CFD–DEM simulation method is employed to predict product yields. Results showed that the elevated moisture content amplifies particle adhesiveness, necessitating augmented air velocities for effective separation, thereby influencing the efficiency of the separation process. While carbon and hydrogen contents exhibit relative stability across diverse moisture contents and blower frequencies, the oxygen content undergoes noticeable changes. For example, the oxygen contents were measured as 29.2 and 38.6 wt% in the light fraction of 30% moisture content sample at blower frequencies of 10 and 20 Hz, respectively. An intriguing finding emerges from pyrolysis simulation, indicating that a lower blower frequency in air classification moderately enhances bio-oil yield and significantly improves its quality, particularly in terms of water content. For instance, the water content in the bio-oil was about 1.5% and 10% in the heavy and light fractions, respectively from 10% moisture sample under 15 Hz blower frequency.

09 - BIOMASS FUELS↗

DOE OSTI2025

Predicting interface structure using the minima hopping method

Here, we adapt the minima hopping method (MHM) to the problem of interfacial structure prediction and apply it to study a canonical problem, the tilt grain boundaries in SrTiO 3 . Our method employs a hybrid approach by first exploring the potential energy surface (PES) of different grain boundary samplings with an empirical force field, among which the fifteen candidates with lower energies are then refined using ab initio density functional theory (DFT) calculations. During the exploratory stage, we bias the search using a local order parameter to primarily sample various reconstructions in the vicinity of the interface, while preserving the crystallinity of the bulk regions. We further enhance the search by incorporating initial structures with rigid body displacements to account for translational variations between bulk phases, enabling the MHM to effectively generate both stoichiometric and nonstoichiometric SrTiO 3 Σ⁢3(111)[110] and Σ⁢3(112)[110] grain boundaries. From an algorithmic standpoint, MHM outperforms earlier studies based on genetic algorithms (GA) by identifying more stable interfacial structures of several SrTiO 3 grain boundaries. The performance of the present implementation of the MHM approach is primarily limited by exploring an approximate description of the PES with a rather simple Buckingham potential. This limitation leads to variations in performance when compared to approaches utilizing more advanced surrogate PES models, such as direct DFT-PES sampling or GA with the embedded atom method (EAM). Despite the present limitations, the MHM approach is able to yield interfacial structures with comparable or lower interfacial energies in specific cases, such as Σ⁢3(111)[110] Γ=1, ±0.5 and Σ⁢3(112)[110] Γ= ±1, −2, underscoring the robustness of the MHM approach even with a simple approximation of the DFT PES. The MHM interfacial structure prediction method thus offers an efficient approach to understanding the grain boundaries and heterointerfaces at the atomic scale, providing an important prerequisite for effective materials design.

density functional theory↗

DOE OSTI2026

Conversion of real-world aluminum scrap streams into high-performance Al–Mg–Si–Cu automotive alloys using shear assisted processing and extrusion

The conversion of post-consumer aluminum (Al) scrap into usable Al alloys without adding primary Al is challenging because of excess impurities. In this work, >99% post-consumer Twitch, used beverage cans (UBCs), and remelt scrap ingots (RSIs) were used as feedstock materials. As-cast and solution heat-treated feedstock billets were extruded using Shear Assisted Processing and Extrusion (ShAPE) at ~510°C, followed by press quenching. To explore the development of the microstructure, texture, and underlying mechanisms and how they contribute to the overall strengthening in as-extruded and artificially aged samples, scanning electron microscopy (SEM) and electron backscatter diffraction (EBSD) were used to collect microstructure and texture data. The enhanced strength and ductility were corroborated with the microstructural features and crystallographic texture. Simple shear $\textrm{A}/\bar{\textrm{A}}$, $\textrm{A}_1^*/\textrm{A} _2^*$ texture components along with weak $\textrm{C}$ and $\textrm{B}/\bar{\textrm{B}}$ texture components were formed during extrusion; the texture was strengthened after heat treatment. The refined second-phase particles helped to retain the deformed microstructure and texture. The contributions of dislocation and precipitate strengthening were maximized when billets were solution-heat-treated prior to extrusion. This is attributed to the formation of effective supersaturated solid solutions during the ShAPE process, which precipitate out during the peak age treatment. Overall, the highest yield strength of 305 MPa, ultimate tensile strength of 350 MPa, and elongation of 12% were achieved in artificially aged samples, which are comparable to those of Al 6082-T6.

Al alloy↗

DOE OSTI2025

Determination of a suitable molar absorption coefficient (ε) for lignin analysis of fibrous plants using the CASA method

In this study, the benchmarking and applicability of the CASA method for the analysis of fibrous plants, such as flax, hemp, and jute, is evaluated. Lignin is a phenolic biopolymer present in plant cell walls and is composed of three primary monomeric units, designated G, S, and H. Various factors, such as the genetic variability, influence the relative proportions of these units in plant samples. Recently, the cysteine-assisted sulfuric acid (CASA) method has been introduced as a rapid method for the quantification of lignin in wood samples. The aim of this study is to establish a suitable molar absorption coefficient (ε, L·g –1 ·cm –1 ) to adapt the CASA method for use with annual plant fibers. This investigation was motivated by the technical advantages of the CASA method, including higher throughput, lower reaction temperatures, and ecological benefits due to the absence of carcinogenic, mutagenic, or reprotoxic (CMR) substances and the need for minimal sample quantities. In this method, lignin solubilization is facilitated by cysteine, which is an amino acid that enhances the reaction kinetics, using a one-hour incubation period. However, as with any spectrophotometric technique, the CASA method depends on a molar absorption coefficient (ε) that varies according to the ratio of the aromatic units within the polymer. To evaluate the suitability of CASA for quantifying lignin in economically significant plant fibers, we investigate the impact of the unit ratios on the accuracy of ε. The results are compared with those of two widely recognized lignin analytical methods: the Klason method, which is a gravimetric reference method, and the acetyl bromide soluble lignin method, which is the most commonly used spectrophotometric approach. The final ε obtained in this study reveals a relative difference in lignin content ranging from –8 % to +9 % based on a comparison between the CASA and Klason methods across different industrial hemp varieties. As a result, using known G:S ratios in annual fibrous plants, ε can be estimated from our results.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Radial burnup characteristics of spent fuel pellets by zirconium analysis

Resonance ionization mass spectrometry is a powerful tool for in-situ measurements of elemental ratios in micrometer-sized spent fuel samples. By measuring the concentration of the fission product Zr we provide a framework for determining fuel burnup while simultaneously considering the 239 Pu fission fraction. Here, the analyzed spent fuel samples were taken from different fuels and distances from the fuel pellets’ edge. Results show a burnup enhancement at the edge of a fuel pellet of 180–220% compared to the center of the pellet. By comparing the concentration of the anthropogenic 93 Zr to the naturally occurring Zr isotopes, any influence of non-fissiogenic Zr or disturbing neutron capture reactions can be ruled out. This established 93 Zr as a new tool to measure fuel burnup.

Burnup↗

DOE OSTI2025

Age hardening response of Cu-30Ni alloys: The role of Si microalloying additions

Cu-30Ni alloys offer high strength and excellent corrosion resistance for maritime applications. While primarily a solid solution system, industrial alloys typically include microalloying additions of Fe, Mn, Nb and/or Si to enable age hardening. However, an understanding of the microstructural evolution during age hardening remains incomplete. Here, we conduct systematic ageing treatments and report the resulting hardness and microstructures. The Cu-30Ni alloy with Si aged at 650 °C for 6 h demonstrates significantly enhanced Vickers hardness, reaching ∼201 HV 1 compared to 103 HV 1 for the as-homogenised sample. Si-rich clusters and γ′ precipitates are identified, with their composition, size, and volume fraction quantified to determine their strengthening contributions. First-principles atomistic simulations elucidate the underlying formation mechanisms of these clusters and precipitates, highlighting the critical role of Si in driving their nucleation and growth. This study advances the design of high-strength, Cu alloys with the potential for corrosion resistance in demanding maritime environments.

Age hardening↗

DOE OSTI2025

Unveiling Feedstock Variability: Insights into Corn Stover Conversion - Part I: Physicochemical Properties and Self-Degradation

Transforming agricultural waste into biofuels and bioproducts is crucial to advancing a low-carbon bioeconomy. However, the inherent variability in the composition and quality introduces uncertainties in the conversion efficiency and poses challenges in process development. Through integrating a high-throughput conversion system, material characterization techniques, and advanced data analysis tools, this study investigates the variability of corn stover and its subsequent impacts on carbohydrate conversion. The findings reveal that indoor storage substantially reduces the moisture and ash content and soil contamination, while other properties remain largely unchanged. Self-degradation due to microbial activity during storage decreases the carbohydrate content of corn stover but enhances glucose and xylose yields. A negative correlation is observed between sugar yields and lignin content across samples with varying ash and moisture content. The inhibitory effect of lignin diminishes in self-degraded samples likely due to the disrupted cell wall structure. Although self-degradation slightly increases cellulose crystallinity, no strong correlation was observed between the crystallinity and sugar yield. Hot water pretreatment under mild conditions effectively mitigates inherent variability, consistently improving the sugar yield from corn stover by up to 50%. By elucidating the feedstock variability and its impact on convertibility, these findings offer valuable insights into appropriate feedstock handling and management, highlighting potential strategies to address variability challenges.

09 BIOMASS FUELS↗

DOE OSTI2025

Constraints on f ( R ) gravity from thermal-Sunyaev-Zel’dovich-effect-selected SPT galaxy clusters and weak lensing mass calibration from DES and HST

We present constraints on the f ( R ) gravity model using a sample of 1005 galaxy clusters in the redshift range 0.25–1.78 that have been selected through the thermal Sunyaev-Zel’dovich effect from South Pole Telescope data and subjected to optical and near-infrared confirmation with the multicomponent matched filter algorithm. We employ weak gravitational lensing mass calibration from the Dark Energy Survey Year 3 data for 688 clusters at z < 0.95 and from the Hubble Space Telescope for 39 clusters with 0.6 < z < 1.7 . Our cluster sample is a powerful probe of f ( R ) gravity, because this model predicts a scale-dependent enhancement in the growth of structure, which impacts the halo mass function (HMF) at cluster mass scales. To account for these modified gravity effects on the HMF, our analysis employs a semianalytical approach calibrated with numerical simulations. Combining calibrated cluster counts with primary cosmic microwave background temperature and polarization anisotropy measurements from the Planck 2018 release, we derive robust constraints on the f ( R ) parameter f R 0 . Our results, log 10 | f R 0 | < − 5.32 at the 95% credible level, are the tightest current constraints on f ( R ) gravity from cosmological scales. This upper limit rules out f ( R ) -like deviations from general relativity that result in more than a ∼ 20 % enhancement of the cluster population on mass scales M 200 c > 3 × 10 14 M ⊙ . Published by the American Physical Society 2025

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Understanding the Role of Extrinsic Impurities in Bulk Nb SRF Cavities

High gradient and high quality factor superconducting radiofrequency (SRF) cavities are essential for efficient particle acceleration in next-generation accelerators. This work demonstrates that the superconducting performance of bulk niobium can be enhanced through a controlled introduction of interstitial oxygen and nitrogen. Thermal and chemical surface treatments modify the concentration and distribution of these impurities, enabling systematic tuning of SRF cavity performance. By combining cavity RF measurements with quantitative materials characterizations, we isolate the impact of impurity concentration on BCS surface resistance and identify the mechanisms by which interstitial impurities alter the superconducting properties of niobium. We find that nitrogen is an order of magnitude more effective than oxygen in reducing BCS resistance at 16 MV/m and that the reduction arises from a combination of mean free path optimization and superconducting gap enhancement. Using these insights, we develop a predictive model that estimates cavity performance directly from room temperature sample material studies, reducing the reliance on full-scale cryogenic tests for surface treatment development. We then apply this model to explore co-doping strategies, demonstrating that combining interstitial oxygen and nitrogen achieves a synergistic reduction in BCS resistance. These results establish co-doping as a viable path for the development of surface-engineered niobium for future high quality factor SRF applications.

Hu, Hannah [Chicago U.]↗

DOE OSTI2024

Adaptive Scalpel Scanning Probe Microscopy for Enhanced Volumetric Sensing in Tomographic Analysis

Controlling nanoscale tip‐induced material removal is crucial for achieving atomic‐level precision in tomographic sensing with atomic force microscopy (AFM). While advances have enabled volumetric probing of conductive features with nanometer accuracy in solid‐state devices, materials, and photovoltaics, limitations in spatial resolution and volumetric sensitivity persist. This work identifies and addresses in‐plane and vertical tip‐sample junction leakage as sources of parasitic contrast in tomographic AFM, hindering real‐space 3D reconstructions. Novel strategies are proposed to overcome these limitations. First, the contrast mechanisms analyzing nanosized conductive features are explored when confining current collection purely to in‐plane transport, thus allowing reconstruction with a reduction in the overestimation of the lateral dimensions. Furthermore, an adaptive tip‐sample biasing scheme is demonstrated for the mitigation of a class of artefacts induced by the high electric field inside the thin oxide when volumetrically reduced. This significantly enhances vertical sensitivity by approaching the intrinsic limits set by quantum tunneling processes, allowing detailed depth analysis in thin dielectrics. The effectiveness of these methods is showcased in tomographic reconstructions of conductive filaments in valence change memory, highlighting the potential for application in nanoelectronics devices and bulk materials and unlocking new limits for tomographic AFM.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Enhancing approximate modular Bayesian inference by emulating the conditional posterior

In modular Bayesian analyses, complex models are composed of distinct modules, each representing different aspects of the data or prior information. In this context, fully Bayesian approaches can sometimes lead to undesirable feedback between modules, compromising the integrity of the inference. The “cut-distribution” prevents unwanted influence between modules by “cutting” feedback. The direct sampling (DS) algorithm is standard practice for approximating the cut-distribution, but it can be computationally intensive, especially when the number of imputations required is large. An enhanced method is proposed, the Emulating the Conditional Posterior (ECP) algorithm, which leverages emulation to increase the number of imputations. Through numerical experiment it is demonstrated that the ECP algorithm outperforms the traditional DS approach in terms of accuracy and computational efficiency, particularly when resources are constrained. Here, it is also shown how the DS algorithm can be improved using ideas from design of experiments. Some practical recommendations are given for algorithm choice in modular Bayesian analyses.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Direct and rapid uranium isotopic analysis of environmental sample swipes via microextraction – LS-APGD/Orbitrap mass spectrometry

Accurate and precise isotopic analysis of actinides collected on environmental sample swipes from within nuclear facilities is an important safeguarding measure for detecting undeclared materials and activities. Traditional isotope ratio (IR) analysis of actinides using a bulk digestion approach can be laborious and time-consuming. Recently, direct analysis of environmental swipe samples using a microextraction approach has been explored as an alternative to conventional bulk digestion methods. The present study further evaluates this approach for accurate and precise isotopic analysis of uranium (U) in cotton swipe samples using the liquid sampling-atmospheric pressure glow discharge (LS-APGD)/Orbitrap-FTMS Booster detection system. The instrumental parameters were optimized, and quantitative capabilities were demonstrated through excellent linearity (R2 = 0.99) across a deposited mass range of 1 to 500 ng, with a limit of detection of 90 pg (in a 2 × 4 mm region) for total U; well below typical U concentrations (ng–mg range) in environmental sample swipes. The 235U/238U ratio showed excellent accuracy (−0.3% relative difference from the certificate value), with ∼20× improvement over previous microextraction-Orbitrap methods. Precision (∼1% relative standard deviation) was also greatly enhanced by ∼5×. This study also demonstrates that figures of merit achieved with neat U solution were not highly degraded when various external interfering elements/matrices were introduced. Finally, the developed method was successfully applied to analyze practical swipe samples representative of laboratory and outdoor environments. The presented figures of merit and applicability to practical samples further validate the capability of the platform for rapid analysis (<7 minutes) of environmental swipe samples.

Shrestha, Suraj [Clemson University, SC]↗

DOE OSTI2024

Supersonic hot jet ablative testing and analysis of boron nitride nanotube hybrid composites

Boron nitride nanotubes (BNNTs) are high-strength, high-modulus nanotubes with high thermal and oxidative stabilities. Two hybrid composites were prepared with satin weave carbon fiber (CF) and resole-type phenolic resin: one with surface layers of BNNTs and one with alternating interlayers of BNNTs. The samples were subjected to hot jet tests that simulate realistic high-pressure-temperature conditions to understand the behavior of BNNTs under high-pressure erosion. Adding BNNTs to CF/phenolic laminates enhanced the ablation resistance by reinforcing the char material and mitigated localized thermal damage. Hybrid laminates exhibited up to 14% lower weight loss, 55% increase in flexural modulus, higher thermal diffusivity, and improved char yield and microstructure compared to CF/phenolic samples. The surface layer hybrid had many surviving nanotubes reinforcing the char and crystalline oxide structures that could mitigate further oxygen diffusion. Further, various characterization methods were used to deduce possible mechanisms and their products, indicating that BNNTs could serve as growth templates for direct crystalline boron oxide formation. Overall, hybrid BNNT/CF/phenolic laminates displayed better ablation resistance and favorable microstructure evolution under high-pressure conditions.

42 ENGINEERING↗

DOE OSTI2024

Dimensionality crossover to a two-dimensional vestigial nematic state from a three-dimensional antiferromagnet in a honeycomb van der Waals magnet

The effects of fluctuations and disorder, which are substantially enhanced in reduced dimensional-ities, can play a crucial role in producing nontrivial phases of matter such as vestigial orders char-acterized by a composite order parameter. However, fluctuation-driven magnetic phases in low dimensions have remained relatively unexplored. Here we demonstrate a phase transition from the zigzag antiferromagnetic order in the three-dimensional bulk to a Z 3 vestigial Potts-nematicity in two-dimensional few-layer samples of van der Waals magnet NiPS 3 . Our spin relaxometry and op-tical spectroscopy measurements reveal that the spin fluctuations are enhanced over the gigahertz to terahertz range as the layer number of NiPS 3 reduces. Monte Carlo simulations corroborate the experimental finding of 3-fold rotational symmetry breaking, but show that translational symmetry is restored in thin layers of NiPS 3 . Furthermore, our results show that strong quantum fluctuations can stabilize an unconventional magnetic phase after destroying a more conventional one.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2026

Emission in closely packed Eu (TTA) 3 (DPT) and opportunities for magnetic dipole enhancement

Ultra-thin Langmuir-Blodgett films of amphiphilic complex EuTTA (DPT) with tri-valent Eu ions are highly luminescent even when deposited directly on metal. Emission kinetics obtained in bulk samples and Langmuir-Blodgett films are very different for dense and diluted systems. Here, the experiments indicate a collective emitter behavior in dense systems, which is also sensitive to metal or dielectric environments. In another experiment, using metal-emitter layer-metal structures with EuTTA(DPT) we observe significant modifications of the emission line shapes and a dramatic change in magnetic-to-electric dipole branching ratio with 10-fold relative enhancement of magnetic dipole emission.

Luminescence↗

DOE OSTI2024

Unconventional spin-orbit torques from sputtered MoTe 2 films

Materials with strong spin-orbit coupling and low crystalline symmetry are promising for generating large unconventional spin-orbit torques (SOTs), such as in-plane fieldlike (FL) torques and out-of-plane dampinglike (DL) torques, which can effectively manipulate and deterministically switch an out-of-plane magnetization without the need for additional external in-plane magnetic fields. Here, we report SOTs generated by magnetron-sputtered 1⁢T' MoTe 2 /Permalloy (Py; Ni 80 ⁢Fe 20 )/MgO heterostructures using both spin-torque ferromagnetic resonance (ST-FMR) and second harmonic Hall measurements. We observed unconventional FL and DL torques in our samples due to spins polarized normal to the interface of MoTe 2 and Py layers, and studied the influence of crystallographic order and MoTe 2 layer thickness on the SOTs. By comparing the Raman spectra of 1⁢T' MoTe 2 samples prepared in different ways, we found a tensile strain in sputtered MoTe 2 films, which might further enhance the generation of unconventional torques by reducing the symmetry of 1⁢T' MoTe 2 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2025

Characterization of the Multi-Coincident Bismuth Germanate Oxide Spectrometer at the Nuclear Counting Facility

A multi-detector γ-ray spectroscopy system including 3 high-purity germanium (HPGe) detectors has been developed at the Nuclear Counting Facility at Lawrence Livermore National Laboratory. This system operates not only in conventional singles γ-ray detection mode but also incorporates features like coincidence and anti-coincidence techniques. These advanced detection modes can significantly enhance the system’s sensitivity, making it a powerful tool for isotope identification and quantification, especially for complex samples with high background and overlapping peaks. In this re port, we present a comprehensive performance characterization of the Multi-Coincident Bismuth Oxide Spectrometer (MCBOS) using a variety of sample types, including 60 Co, 48 Sc, and mixed fission product samples. Each sample provides unique tests for the MCBOS capabilities. Additionally, a GEANT4 model of the MCBOS has been generated to aid with the characterization of the system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗