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DOE OSTI2025

Print-and-Plate Architected Electrodes for Electrochemical Transformations Under Flow

Flow cell electrodes are typically composed of porous carbon materials, such as papers, felts, and cloths. However, their random architecture hinders the fundamental characterization of electrode structure-performance relationships during in situ operation of porous electrochemical flow systems. This work describes a “print-and-plate” method that combines direct ink writing of micro-periodic lattices with a two-step metal plating process that converts them into highly conductive (sheet resistance 40 mΩ sq -1 ) electrodes. Their operando performance is assessed in an anthraquinone disulfonic acid half-cell using widefield electrochemical fluorescence microscopy, where output current and fluorescence intensity are in excellent agreement. The pressure drop associated with flow through three electrode designs is determined via simulations from which the most efficient design is identified and manufactured via print-and-plate. Confocal fluorescence microscopy is then used to create a 3D map of the state of charge (SOC) inside this print-and-plate electrode. The experimental state of the charge map is in good agreement with computational predictions. The rapid design, simulation, and fabrication of print-and-plate electrodes enable fundamental investigations of how architected porosity affects electrochemical performance under flow.

3D-printing↗

DOE OSTI2025

Tuning the Properties of Lignin‐Derived Deep Eutectic Solvents for Biomass Processing

Lignin-derived deep eutectic solvents (DESs) have been investigated as sustainable green media for biomass processing. However, the properties and processability of DESs have not been fully understood with the chemical structures of their constituents for biomass fractionation. Here, in this article, the properties of the phenolic DESs are discussed with different numbers of functional groups, such as –OCH 3 and –CHO in their hydrogen bond donor (HBD) structures. The formation of DES is significantly related to the hydrogen bond between its constituents, identified by nuclear magnetic resonance (NMR) analysis and density functional theory calculation (DFT). Lower viscosity and net basicity of DES are achieved with fewer –OCH 3 on HBD structures, resulting in enhanced processability and fractionation efficiency. The thermal stability of the DES is also influenced by the –OCH 3 and –CHO of HBD, as indicated by its onset temperature. The recyclability of the phenolic DES is confirmed by the fractionation performance of the recycled DES. Understanding the structural impacts of DES constituents on the properties and performance is crucial for designing solvents in biorefinery applications.

Ryu, Jiae [State University of New York (SUNY), Sy↗

DOE OSTI2025

Uncertainty in inventories for life cycle assessment: State‐of‐the‐art, challenges, and new technologies

Uncertainty is a critical factor that can hinder the quality and potential applications of life cycle assessment (LCA) results. A prominent source of uncertainty stems from the life cycle inventory (LCI) data. Various methodologies exist to estimate the uncertainty associated with LCI data, primarily based on the widely used structured pedigree matrix approach or the computationally intensive Monte Carlo simulation. This perspective review explores how new technologies (e.g., computational algorithms and data collection methods) from data science and related fields can contribute to identifying, quantifying, and reducing uncertainty in LCI modeling. A brief overview of the sources of uncertainty in LCI modeling and how they are addressed in current LCA practice is provided. Additionally, several new technologies are identified, and the potential benefits of their implementation in reducing uncertainties in LCI modeling are discussed. This perspective review concludes by identifying potential areas that require further development for these technologies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

A Corrected Score Function Framework for Modelling Circadian Gene Expression

Many biological processes display oscillatory behaviour based on an approximately 24 h internal timing system specific to each individual. One process of particular interest is gene expression, for which several circadian transcriptomic studies have identified associations between gene expression during a 24 h period and an individual's health. A challenge with analysing data from these studies is that each individual's internal timing system is offset relative to the 24 h day-night cycle, where day–night cycle time is recorded for each collected sample. Laboratory procedures can accurately determine each individual's offset and determine the internal time of sample collection. However, these laboratory procedures are labour-intensive and expensive. Here, in this paper, we propose a corrected score function framework to obtain a regression model of gene expression given internal time when the offset of each individual is too burdensome to determine. A feature of this framework is that it does not require the probability distribution generating offsets to be symmetric with a mean of zero. Simulation studies validate the use of this corrected score function framework for cosinor regression, which is prevalent in circadian transcriptomic studies. Illustrations with data from three circadian transcriptomic studies further demonstrate that the proposed framework consistently mitigates bias relative to using a score function that does not account for this offset.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Effective data sampling strategies and boundary condition constraints of physics-informed neural networks for identifying material properties in solid mechanics

Material identification is critical for understanding the relationship between mechanical properties and the associated mechanical functions. However, material identification is a challenging task, especially when the characteristic of the material is highly nonlinear in nature, as is common in biological tissue. In this work, we identify unknown material properties in continuum solid mechanics via physics-informed neural networks (PINNs). To improve the accuracy and efficiency of PINNs, we develop efficient strategies to nonuniformly sample observational data. We also investigate different approaches to enforce Dirichlet-type boundary conditions (BCs) as soft or hard constraints. Finally, we apply the proposed methods to a diverse set of time-dependent and time-independent solid mechanic examples that span linear elastic and hyperelastic material space. The estimated material parameters achieve relative errors of less than 1%. As such, this work is relevant to diverse applications, including optimizing structural integrity and developing novel materials.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Generalizable machine learning potentials for quantum-accurate predictions of non-equilibrium behavior in 2D materials

Machine learning interatomic potentials (ML-IAPs) are emerging as transformative tools in materials modeling, promising quantum-level accuracy at a fraction of the computational cost. However, their ability to generalize beyond equilibrium configurations and to reliably capture defect- and temperature-driven behavior remains underexplored. Here, we develop and benchmark two state-of-the-art ML-IAPs, Spectral Neighbor Analysis Potential (SNAP) and Allegro, on a comprehensive dataset for monolayer MoSe₂. Using density functional theory (DFT) as the reference, we evaluate their performance in capturing stress–strain behavior, phase transition energetics, defect evolution, edge stability, and fracture toughness. Allegro, a deep equivariant neural network potential, surpasses both SNAP and the classical Tersoff potential in accuracy, efficiency, and transferability. Importantly, both ML potentials accurately reproduce experimental fracture measurements and ab initio predictions of inversion domain formation—phenomena well beyond their training sets. Our findings establish ML-IAPs as viable replacements for traditional force fields in the study of non-equilibrium mechanical phenomena, enabling large-scale, high-fidelity simulations in 2D materials and beyond. In conclusion, this work provides a broadly applicable framework for data-driven modeling of structural and functional transformations under extreme conditions.

2D materials↗

DOE OSTI2026

An adaptive model-free robotic force control strategy for hydrodynamic real-time hybrid simulation of floating offshore wind turbines

Real-time hybrid simulation (RTHS) - a cyber-physical testing approach - promises to enhance the simulation fidelity of the model-scale experiments used to prototype floating offshore wind turbines (FOWTs). In hydrodynamic RTHS (hydro-RTHS), actuators emulate aerodynamic forces on model-scale FOWT specimens subjected to physical waves in a hydrodynamic laboratory. Robotic arms are promising candidates for actuation in hydro-RTHS due to their compact multi-degree-of-freedom (DOF) capabilities. Unlike classical RTHS for seismic applications, which typically relies on displacement control, hydro-RTHS requires 6-DOF force control on newly designed floating prototypes in a model-scale setting, which presents significant challenges, including modeling uncertainties, directional asymmetry, configuration drift, bandwidth limitations, and time-varying delays. To mitigate these constraints without extensive pre-test calibration, this study proposes an adaptive model-free robotic force control strategy that combines task-space explicit force control with a secondary joint-space pose-keeping task. The Adaptive Feedforward Compensator (AFC) is integrated into the force control loop to compensate for time-varying delay. Experimental testing was conducted using a Franka Emika Panda robotic arm with a 1:50 scale FOWT specimen under operational wind and wave conditions. Results demonstrate stable and consistent 6-DOF force tracking. Effective delay compensation was observed, with low-frequency delay reductions ranging from 71.4% to 91.8% and improvements in low-frequency surge force tracking of 25.0% to 52.1%. This study enhances robotic actuation performance in hydro-RTHS and introduces a force control strategy that supports reliable robotic operation in uncertain floating environments. Future work will explore disturbance-observer mechanisms to further enhance wave rejection capabilities under extreme wind and wave conditions.

17 WIND ENERGY↗

DOE OSTI2025

Policy implications of net-zero emissions: A multi-model analysis of United States emissions and energy system impacts

Many countries, subnational jurisdictions, and companies are setting net-zero emissions goals; however, questions remain about strategies to reach these targets, policy measures, technology gaps, and economic impacts. Here, we investigate the potential policy implications of reaching economy-wide net-zero CO 2 emissions across the United States by 2050 using results from a multi-model comparison with 14 energy-economic models. Model results suggest that achieving net-zero CO 2 targets depends on policies that accelerate deployment of zero- and low-emitting technologies that have seen rapid cost reductions in recent years (including wind, solar, battery storage, and electric vehicles) as well as relatively nascent options (including carbon capture and storage, advanced biofuels, low-carbon hydrogen, advanced nuclear, and long-duration energy storage). While net-zero policies are likely to lower fossil fuel consumption, including considerable coal and petroleum reductions, achieving net-zero emissions does not necessarily mean phasing out all fossil fuels. Model results indicate that the Inflation Reduction Act’s energy and climate provisions amplify near-term decarbonization but that net-zero policies have larger impacts on long-run outcomes. Stringent climate policy can have large fiscal impacts on tax revenue and government spending—revenues from carbon pricing and subsidies for carbon removal range from 0.1 % to 3.7 % of GDP in 2050 across models. Each dollar per metric ton carbon price leads to a 0.06 % to 0.31 % reduction in economy-wide CO 2 emissions relative to a reference scenario with current policies. Spending on energy across the economy decreases relative to today for many models under reference and net-zero policies, especially as a share of GDP, due primarily to end-use electrification and energy efficiency.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Bioenergy pathways within United States net-zero CO 2 emissions scenarios in the Energy Modeling Forum 37 study

The Energy Modeling Forum 37 study is organized around carbon dioxide (CO 2 ) mitigation scenarios reaching net-zero CO 2 emissions by 2050 in the United States. Here, this paper summarizes the potential contribution of bioenergy use in the electric power, transportation, industrial, and buildings sectors toward meeting that target based on model results. Thirteen modeling teams reported bioenergy consumption in the Reference and Net Zero scenarios. Consumption of bioenergy increased over time in the Reference scenario, from an average across models of 3.2 exajoules (EJ) in 2020 to 3.8 EJ in 2050. Average bioenergy consumption in 2050 increased further to 7.3 EJ in the Net Zero scenario. All scenarios that reach net-zero emissions required some form of carbon dioxide removal to offset emissions that are difficult to reduce. Carbon dioxide removal using bioenergy with CO 2 capture and storage (BECCS) varies widely across models, up to 1000 Mt CO 2 in 2050. Some models rely instead on direct air carbon capture and storage (DACCS), up to 2200 Mt CO 2 , and others use a combination of BECCS and DACCS. Model results show a strong inverse relationship between the amounts of BECCS and DACCS deployed. All modeling teams assumed a carbon sink from land use, land use change, and forestry, further offsetting a portion of emissions from fossil fuels and industry that are expensive to eliminate. Bioenergy consumption in 2050 decreased by an average of 1.5 EJ across eight models in a Net Zero+ scenario relative to the Net Zero scenario, due in part to a lower equilibrium carbon price resulting from optimistic cost assumptions for all energy technologies.

09 BIOMASS FUELS↗

DOE OSTI2025

Transportation in net-zero emissions futures: Insights from the EMF-37 model intercomparison study

Transportation is currently the largest source of U.S. anthropogenic CO 2 emissions, at about a third of the total. Achieving net-zero emissions by mid-century will require substantial reductions in transportation emissions across passenger and freight travel. Here we leverage a model intercomparison study to explore the role of transportation in scenarios achieving net-zero economy-wide CO 2 emissions by 2050. We find the transport sector is poised to play the most significant role in reducing demand-side emissions, mostly driven by technology substitution, as modeling results suggest a limited role for mode shifting and for reduced use of personal car travel in the U.S. Among various technology solutions, models show agreement that passenger on-road vehicles will largely transition to electric vehicles (EVs), while solutions to decarbonize heavier travel modes are more diverse and include greater use of liquid biofuels and hydrogen. Research should continue to investigate the evolution of on-road electrification, the role of biofuels and hydrogen across heavier travel modes, and the role of mode shifting and travel behavior change to support personal transportation decarbonization at national and regional scales to temper the rapid growth in clean fuel and electricity demand.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2025

A microstructural signature of the coesite-quartz transformation: New insights from high-pressure experiments and EBSD

Ultra-high pressure (UHP) metamorphism is difficult to identify in continental crust as few petrological barometers are suitable for dominantly felsic lithologies. In such cases, burial to extreme depths is commonly identified through the preservation of coesite, a high-pressure polymorph of SiO 2 that typically forms at depths exceeding ∼ 100 km (i.e., > 2 GPa pressure). Unfortunately, coesite readily transforms to quartz upon exhumation, meaning that UHP terranes may often be overlooked. While some studies have suggested that quartz may inherit an orientation signature indicative of former coesite, both the specific nature of this signature and the conditions favouring its development remain uncertain. Here, to address this problem, we combine electron backscatter diffraction analysis of natural and experimental samples to explore microstructural evolution across the coesite-quartz phase transformation. We demonstrate that neighbouring domains of quartz commonly feature an 84 ± 4° rotation of [c] axes around the pole of a common {m} plane. This orientation relationship is a product of epitaxy, whereby the {$11\bar{2}2$} Japan twin plane in quartz nucleates on the (010) plane in coesite. In supercell simulations, the nucleation of Japan twins can be explained by the energetically favourable alignment of quartz tetrahedra on parental coesite tetrahedra. Through experiments, we demonstrate that this signature emerges over a broad range of conditions, regardless of the availability of nucleation sites (e.g., grain boundaries) or the density of crystal lattice defects (e.g., dislocations). Overall, our work provides a quantitative and unambiguous tool for identifying UHP terranes from quartz in isolation.

Coesite↗

DOE OSTI2025

Measurements of a LYSO crystal array from threshold to 100 MeV

We report measurements of ten custom-made high-homogeneity LYSO crystals. The investigation is motivated by the need for a compact, high-resolution, and fast electromagnetic calorimeter for a new rare pion decay experiment. Each 2.5 x 2.5 x 18 cm 3 crystal was first characterized for general light yield properties and then its longitudinal response uniformity and energy resolution were measured using low-energy gamma sources. The ten crystals were assembled as an array and subjected to a 30–100 MeV positron beam with excellent momentum definition. The energy and timing resolutions were measured as a function of energy, and the spatial resolution was determined at 70 MeV. An additional measurement using monoenergetic 17.6 MeV gammas produced through a p-Li resonance was later made after the photosensors used in positron testing were improved. Here, as an example of the results, the energy resolution at 70 MeV of (1.52 ± 0.03) % is more than two times better than reported results using previous generation LYSO crystals.

Electromagnetic calorimeter↗

DOE OSTI2025

Source characterization of a detector for heavy and superheavy nuclei

A new focal plane detector system for the Berkeley Gas-filled Separator (BGS) was designed, constructed, and tested offline with various α-decay and conversion-electron sources. The SuperHeavy RECoils (SHREC) detector comprises sets of double-sided silicon strip detectors arranged in an open-faced cuboid geometry. Alongside the detector upgrade new digital data acquisition electronics have been commissioned offline. This setup aims to detect separated recoiling heavy and superheavy nuclei as well as their correlated radioactive decay paths with improved energy resolution and overall sensitivity.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Phase-Imaging Ion-Cyclotron-Resonance mass spectrometry with the Canadian Penning Trap at CARIBU

The Canadian Penning Trap mass spectrometer (CPT) has conducted precision mass measurements of neutron-rich nuclides from the CAlifornium Rare Isotope Breeder Upgrade (CARIBU) of the Argonne Tandem Linac Accelerator System (ATLAS) facility at Argonne National Laboratory using the Phase-Imaging Ion-Cyclotron-Resonance (PI-ICR) technique for over half a decade. Here, in this study, we discuss the CPT system, and methods to improve accuracy and precision in mass measurement using PI-ICR including some optimization techniques and recently studied systematic effects.

Penning trap mass spectrometry↗

DOE OSTI2025

Ab initio calculations of scattering and fusion reactions

We review recent advancements achieved within the ab initio no-core shell model with continuum (NCSMC), a unified first-principle (or, ab initio) approach to nuclear bound and continuum states. We highlight its application to reactions of astrophysical interests, including the 7 Be(p, γ) 8 B solar fusion and α-α scattering, and to the structure of the exotic 12 Be nucleus. Furthermore, our findings provide a solid foundation for integrating ab initio calculations with experimental measurements, allowing for more precise evaluations of key thermonuclear reaction rates at astrophysical energies, and offer new insights into the factors that contribute to the emergence of clustering.

Quaglioni, Sofia [Lawrence Livermore National Labo↗

DOE OSTI2025

What's new? An ab initio investigation of the 3 He-4He radiative capture into 7 Be

The 3 He$(α, γ)$ 7 Be radiative capture reaction plays an important role in the creation of elements in stars and in the production of solar neutrinos. It is difficult to experimentally measure this fusion cross section at energies relevant to solar processes because of Coulomb repulsion. Therefore, theory is needed to perform extrapolations from higher energies (where experimental fusion measurements are feasible) to the astrophysical regime. Here, we present the first microscopic calculations of 3 He$(α, γ)$ 7 Be with explicit inclusion of three-nucleon forces. With the incorporation of experimental bound-state and scattering information, our calculation of the astrophysical S factor agrees quantitatively with experimental data.

Physics - Nuclear physics and radiation physics↗

DOE OSTI2025

Evidence for metal sources, fluid-mixing processes, and S isotope recycling within the feeder zone of an Irish type Zn-Pb deposit

The origin and evolution of fluids in Irish-type Zn-Pb deposits remains debated, particularly regarding the mobility of metals such as Cu and Ni, sources of sulphur, and the role of fluid mixing and replacement. The Lisheen Zn-Pb deposit, Ireland, offers a well-defined natural laboratory to investigate these questions. While most studies have focused on the Waulsortian Limestone Formation, the primary sulphide host, less is known about mineralisation in underlying units, such as the Lisduff Oolite Member (LOM). The LOM displays enrichment in Cu and Ni and displays intense replacement textures compared to other hosts at Lisheen, making it an ideal target for studying metal mobility and sulphur recycling in carbonate-hosted systems. Through characterising and studying LOM-hosted sulphides, valuable insights into mineralisation processes, especially related to Cu-Ni metals, can be defined. This study integrates petrography, EMPA, and in situ sulphur isotope (δ 34 S) analysis to investigate sulphide paragenesis, mineral chemistry, and fluid evolution across LOM ore zones. Results reveal a multistage mineralising system involving extensive replacement of early pyrite (Py0, δ 34 S = −28.4 to −21.9 ‰) by sphalerite and galena, with zoned pyrite (Py1) enriched in As-Cu-Ni-Tl. The δ 34 S values and trace element trends indicate mixing between hydrothermal and bacteriogenic sulphur-rich fluids, with evidence for sulphur recycling during replacement. Pyrite textures and compositions capture this evolving fluid regime, with trace element enrichment linked to paragenetic stage. The steel ore region, adjacent to major fault intersections, records intense hydrothermal fluid interaction, hosting Ni- and As-rich phases such as nickeline, gersdorffite, and arsenopyrite. These findings highlight the importance of structural controls and fluid mixing in metal transport and deposition, positioning the LOM as a key stratigraphic unit for understanding ore-forming processes in Irish-type systems. These results have implications for targeting similar carbonate-hosted systems globally, especially where deeper or structurally complex ore zones remain underexplored.

58 - GEOSCIENCES↗

DOE OSTI2025

Impact of melt viscosity on filler dispersion in elastomeric nanocomposites

Compounding of commercial nanocomposites usually involves the addition of viscosity enhancers such as binder resins in ink jet inks, and paints. Contrary to this, plasticizers such as process oils are added to reduce the melt viscosity and ease processability of reinforced elastomers. Nanofillers such as silica and carbon black are typically added to reinforce rubber and enhance performance of automotive tire treads. Filler dispersion has traditionally been qualitatively (indirectly) assessed by measuring the properties of reinforced elastomers. While dispersion can be quantified by examining filler agglomeration through surface roughness measurements and microscopy, the size-scale dependence for these hierarchical fillers has usually been ignored. Here, we have recently devised a method to quantify nano-scale dispersion of fillers using Ultra small-angle X-ray scattering (USAXS) techniques. This method is advantageous since it directly links the controllable processing/compounding parameters such as the mixing speed, mixer geometry, residence time (or mixing duration), melt density, flow gap distance, and melt viscosity to nano-scale dispersion. While our previous studies have explored the impact of different processing parameters, this study specifically investigates the impact of melt viscosity on nano-scale filler dispersion in elastomer compounds. Commercially available polybutadienes with different Mooney viscosities were used in conjunction with different grades and amounts of process oils to modify the melt viscosity.

Carbon black↗