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DOE OSTI2025

Bridging the Gap in Carbon Free Iron Making: How Hydrogen Affects the Reduction of Iron Ore between 900 and 1590 °C

Hydrogen-based reduction of iron ore for iron and steel production has emerged as a promising alternative to coal and natural gas. Unlike other hydrogen-based iron ore reduction studies, this research focuses on a wide temperature range across 900–1590 °C, encompassing reduction in solid, mixed, and liquid (slag) phases. For a 20 min exposure to hydrogen, the reduction degree increased monotonically from ∼35% at 900 °C to >90% at 1550 °C, except between 1100 °C and 1400 °C, where it stagnated ∼60%. This experimental work challenges the widely accepted notion that higher temperatures enhance the reduction process. Instead, it reveals an overlooked kinetic bottleneck, suggesting complex thermodynamic and mass transfer limitations influenced by phase transformations, diffusion barriers, and microstructural changes. Density functional theory-based molecular dynamics simulations indicate that oxygen diffusivity in BCC iron is 3.88 × 10 –5 cm 2 /s which is ∼5–10 times higher than that in FCC iron. This study reports that this stagnant reduction degree in the mixed solid–liquid phase is due to competition of multiple mechanisms, such as surface- and bulk-diffusion, pore collapse mechanisms, and crystallographic transitions.

08 HYDROGEN↗

DOE OSTI2026

CaloTrilogy: Toward a Breakthrough in One-Step, End-to-End, Physics-Guided Shower Generation for Modern Calorimeters

High-precision calorimeter simulation at current and future colliders imposes rapidly growing computational demands, motivating the development of machine-learning surrogates for traditional Monte Carlo tools such as Geant4. Flow matching and diffusion-based generative models have become leading approaches for high-dimensional fast simulation because of their sample quality, but typically require ${\cal O}(100)$ function evaluations at inference and often rely on auxiliary networks to constrain global observables, compromising streamlined end-to-end generation. We introduce a unified framework that improves the balance between speed, shower quality, and physics fidelity. The method combines: (i) an average velocity field integrator that enables sampling in one or a few evaluations; (ii) a learned generative prior in shower space, constructed from data rather than random noise; and (iii) physics-guided loss terms that impose inductive biases on key observables during training. These elements are training time regularizers, preserving end-to-end inference with no additional cost. With only one or a few evaluation steps, the model achieves shower quality competitive with state-of-the-art flow and diffusion approaches, tested on several public high granularity calorimeter datasets. The results demonstrate inter-layer shower structure consistent with the underlying physics, providing a strong candidate for future fast simulation workflows.

Jiang, Cheng [Edinburgh U.]↗

DOE OSTI2022

Ultrafast Metal Electrodeposition Revealed by In Situ Optical Imaging and Theoretical Modeling towards Fast–Charging Zn Battery Chemistry

Metallic Zn is a preferred anode material for rechargeable aqueous batteries towards a smart grid and renewable energy storage. Importantly, understanding how the metal nucleates and grows at the aqueous Zn anode is a critical and challenging step to achieve full reversibility of Zn battery chemistry, especially under fast-charging conditions. Here, by combining in situ optical imaging and theoretical modeling, we uncover the critical parameters governing the electrodeposition stability of the metallic Zn electrode, that is, the competition among crystallographic thermodynamics, kinetics, and Zn 2+ -ion diffusion. Moreover, steady-state Zn metal plating/ stripping with Coulombic efficiency above 99 % is achieved at 10-100 mA cm -2 in a reasonably high concentration (3 M) ZnSO 4 electrolyte. Significantly, a long-term cycling-stable Zn metal electrode is realized with a depth of discharge of 66.7% under 50 mA cm -2 in both Zn || Zn symmetrical cells and MnO 2 || Zn full cells.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

How the Hydrophobic Interface between a Perfluorosulfonic Acid Polymer and Water Vapor Controls Membrane Hydration

Stable hydration in perfluorinated polyelectrolyte membranes such as Nafion is essential to maintain good ion conductivity and manage permeation, especially in vapor-fed devices where water content depends on relative humidity in a gas stream. Extensive studies in the literature have shown that Nafion hydration in water vapor is controlled by its interfacial transport resistance. Nafion forms a fluorine-rich layer at the polymer-gas interface, and it has been proposed that this layer blocks water transport due to its hydrophobicity. To develop a molecular-level description of the physics underlying transport resistance in this system, we have performed a computational reaction-diffusion kinetics study of water evaporation from Nafion. Two distinct models are examined, one mimicking the blocking function proposed in the literature and the other assuming that there is no blocking, treating instead water evaporation as a dynamic balance between uptake from the gas and desorption from the polymer surface. Simulation results are compared to time-dependent infrared data over a range of 100-0% relative humidity from the literature. Only the dynamic model successfully reproduces experimental observations. This indicates that the physical nature of interfacial transport resistance is not slow diffusion across an interfacial layer; rather, it is due to the competition between dehydration and rehydration. The simulation data provide details on the accompanying water distributions throughout the membrane and on interfacial kinetics, showing that they are characterized by strong fluctuations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Frustration-induced diffusive scattering anomaly and dimension change in FeGe 2

Magnetic frustration, arising from the competition of exchange interactions, has received great attention because of its relevance to exotic quantum phenomena in materials. In the current work, we report an unusual checkerboard-shaped scattering anomaly in FeGe 2 , far from the known incommensurate magnetic satellite peaks, by inelastic neutron scattering. More surprisingly, such phenomenon appears as spin dynamics at low temperature, but it becomes prominent above Néel transition as elastic scattering. Here, a model Hamiltonian that includes an intraplane next-nearest neighbor was proposed and such anomaly is attributed to the near-perfect magnetic frustration and the emergence of unexpected two-dimensional magnetic order in the quasi-one-dimensional FeGe 2 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2022

Proper orthogonal decomposition based reduced-order modeling of flux-Limited gray thermal radiation

Here, in this work, a proper orthogonal decomposition (POD) based reduced-order model (ROM) is developed to solve gray, flux-limited thermal radiation diffusion. We focus on the variable opacity radiation penetration benchmark posed by Olson, Auer, and Hall. The T -3 relationship for opacity in conjunction with high-temperature radiation penetrating an initially cold material produces a strong thermal radiation shock. This class of problems is particularly challenging for standard POD-based reduced-order modeling due to the nonlinearities presented by 1) the T 4 source term, and 2) flux-limited diffusion operator. To address these challenges and develop a cost competitive ROM, we employ a “hyper-reduction” technique through discrete empirical interpolation (DEIM) and allow for adaptive reduced-order projections through principal interval decomposition (PID). Performance of the proposed methodology is quantified by comparing the cost savings and accuracy relative to a full-order computation. Reference solutions and snapshot data are obtained through a full-order calculation performed by the University of Chicago maintained astrophysics code, FLASH. For consistency and potential extensibility, the developed ROM is also implemented in FLASH. We find that in the initialization regime, where the thermal radiation wave is initially created by the warming of the material, this class of problems is highly reducible and suitable for POD-based ROMs. However, the strong convective nature of the wave propagation regime is less reducible and more challenging to create an efficient ROM.

42 ENGINEERING↗

DOE OSTI2024

Identifying multiple synergistic factors on the susceptibility to stress relaxation cracking in variously heat-treated weldments

The 347H austenitic stainless steel has been widely used for pressure vessels and pipeline (PVP) applications due to its excellent creep and corrosion resistance, which fit ideally to the harsh conditions in petrochemical industries, fossil fuel or nuclear power plants, and modern energy storages. However, a failure mode has been commonly observed with cracks emerging at the heat affected zone (HAZ) of weldments during post-weld heat treatment (PWHT) or under intermediate to high temperature service conditions. This phenomenon is termed as Stress Relaxation Cracking (SRC) since the purpose of PWHT is to relieve the welding-induced residual stress fields, or as Stress Age Cracking (SAC) if failure happens during service. A leading literature explanation of this failure suggests that the residual stress relaxation and the precipitation dissolution and/or re-precipitation occur in the same temperature range, which can lead to locally high strains and thus to crack at the grain boundaries. Since in situ spatial measurements of residual stress fields, microstructural evolution, and failure processes are nearly infeasible, this work recourses to a micromechanical finite element framework that models the high temperature failure as the nucleation and growth of grain boundary cavities, whereas various parameters such as thermomechanical loading history and its evolution, the competition of grain-interior dislocation creep and grain-boundary diffusion in failure lifetime, and microstructural heterogeneities (such as the precipitate free zone near grain boundaries) can be quantitatively incorporated. It can be concluded from these microstructure-explicit simulations that an accurate knowledge of residual stress evolution and a carefully calibrated set of material constitutive parameters are the essential prerequisites for lifetime predictions. The understanding of individual governing factors also leads to a mechanistic interpretation of the observed SRC susceptibility C-curves. In conclusion, these results suggest that the criticality of residual stress evolution, but not the precipitation-induced local strains, be the leading factor for SRC.

347H stainless steel weldments↗

DOE OSTI2024

Understanding and controlling water-organic co-transport in amorphous microporous materials

The transport of molecules in microporous material is a significant and active area of research in separation applications. The movement of vapor/liquid molecules in a high-loading condition in microporous spaces is especially challenging to interrogate. This project aims to understand and control the transport of complex water and organic solvent mixtures in varying structures of microporous carbon molecular sieve (CMS) and activated carbon membranes. Modeling of transport behavior in such carbonaceous samples using computational modeling is difficult due to their amorphous structure. Therefore, this research intends to study the transport mechanism of water-organic mixtures by experimentally revealing fundamental transport properties, such as guest sorption amounts as well as diffusion and permeation rates. Considering the different size and guest-host affinity of water and organic solvent molecules, the objective of this research is to understand the structural conditions within the ultramicropores and micropores that generate different types of molecular transport and selection mechanisms within such complex systems. Carbonaceous materials are developed using tailored pyrolysis techniques to pyrolyze polymeric precursors, including polyvinylidene chloride (PVDC),polyvinylidene fluoride (PVDF), polymer of intrinsic microporosity (PIM) -1, and fully aromatic polyamide. The initial stage of the research will focus on the microscopic diffusion and sorption studies of pure component water, xylene isomers, and n,n- dimethylformamide within various carbons. Additional structural investigation on CMS, such as gas physisorption and neutron scattering studies, will be executed to gain deeper insight into these structure-transport relationships. Scanning electron microscopy and X-ray photoelectron microscopy are also used to further characterize these materials. The research will progress to probe mutual diffusion of complex water-organic mixtures within various CMS microstructures. Competitive sorption and permeation studies of the binary mixtures in different microstructural CMS will be followed. The obtained binary mixture transport parameters were used to predict binary water-organic mixtures transport.

36 MATERIALS SCIENCE↗

DOE OSTI2021

A novel physics-based and data-supported microstructure model for part-scale simulation of laser powder bed fusion of Ti-6Al-4V

The elasto-plastic material behavior, material strength and failure modes of metals fabricated by additive manufacturing technologies are significantly determined by the underlying process-specific microstructure evolution. In this work a novel physics-based and data-supported phenomenological microstructure model for Ti-6Al-4V is proposed that is suitable for the part-scale simulation of laser powder bed fusion processes. The model predicts spatially homogenized phase fractions of the most relevant microstructural species, namely the stable β-phase, the stable α s -phase as well as the metastable Martensite α m -phase, in a physically consistent manner. In particular, the modeled microstructure evolution, in form of diffusion-based and non-diffusional transformations, is a pure consequence of energy and mobility competitions among the different species, without the need for heuristic transformation criteria as often applied in existing models. The mathematically consistent formulation of the evolution equations in rate form renders the model suitable for the practically relevant scenario of temperature- or time-dependent diffusion coefficients, arbitrary temperature profiles, and multiple coexisting phases. Due to its physically motivated foundation, the proposed model requires only a minimal number of free parameters, which are determined in an inverse identification process considering a broad experimental data basis in form of time-temperature transformation diagrams. Subsequently, the predictive ability of the model is demonstrated by means of continuous cooling transformation diagrams, showing that experimentally observed characteristics such as critical cooling rates emerge naturally from the proposed microstructure model, instead of being enforced as heuristic transformation criteria. Eventually, the proposed model is exploited to predict the microstructure evolution for a realistic selective laser melting application scenario and for the cooling/quenching process of a Ti-6Al-4V cube of practically relevant size. Numerical results confirm experimental observations that Martensite is the dominating microstructure species in regimes of high cooling rates, e.g., due to highly localized heat sources or in near-surface domains, while a proper manipulation of the temperature field, e.g., by preheating the base-plate in selective laser melting, can suppress the formation of this metastable phase.

Inverse parameter identification↗

DOE OSTI2021

Experimental and computational study of the microporous layer and hydrophobic treatment in the gas diffusion layer of a proton exchange membrane fuel cell

Enabling fuel cell operation at high current density is critical for developing competitive alternative power system to replace internal combustion engine. However, liquid water management continues to be a challenge for high humidity or high current density operation. Water condensation in the porous media hinders efficient oxygen transport to the catalyst layer, which in turns, reduces fuel cell performance. To improve water management capability, the gas diffusion layer is often impregnated with Polytetrafluoroethylene (PTFE) and coated with a thin microporous layer, which have shown to improve fuel cell performance, especially under wet conditions. However, the fundamental mechanism that drives the performance enhancement is still not well understood. In this work, the effects of PTFE impregnation and MPL were studied using both experimental and computational techniques. Both limiting current and polarization tests under dry and wet operating condition are conducted to study the oxygen transport resistance and fuel cell performance. In addition, a 2-D, two-phase, multi-physics PEMFC model is developed to simulate performance and gain a fundamental understanding of local water saturation and oxygen concentration. The combined results show that 5 wt% PTFE impregnation with MPL significantly enhances liquid water management, which enables higher current density operation of a fuel cell.

25 ENERGY STORAGE↗

DOE OSTI2025

How transparent is graphene? A surface science perspective on remote epitaxy

Remote epitaxy is the synthesis of a single crystalline film on a graphene-covered substrate, where the film adopts epitaxial registry to the substrate as if the graphene is transparent. Despite many exciting applications for flexible electronics, strain engineering, and heterogeneous integration, an understanding of the fundamental synthesis mechanisms remains elusive. Here we offer a perspective on the synthesis mechanisms, focusing on the foundational assumption of graphene transparency. We identify challenges for quantifying the strength of the remote substrate potential that permeates through graphene, and propose Fourier and beating analysis as a bias-free method for decomposing the lattice potential contributions from the substrate, from graphene, and from surface reconstructions, each at different frequencies. We highlight the importance of graphene-induced reconstructions on epitaxial templating, drawing comparison to moiré epitaxy. We highlight the role of the remote potential in tuning surface diffusion and adatom kinetics on graphene, which are crucial for navigating the competition between remote epitaxy and defect-seeded mechanisms like pinhole epitaxy. In light of this weak remote potential, we re-evaluate the current state-of-the-art experimental evidence, highlighting why it remains challenging to experimentally validate a ‘remote’ epitaxy mechanism that cannot be explained by alternatives, such as pinhole-seeded epitaxy or serial van der Waals epitaxy. We end with one experimental example that, to out knowledge, cannot be explained by competing mechanisms: a different long-range epitaxial relationship for GdPtSb films grown on graphene/sapphire, compared to direct epitaxy on sapphire. We suggest for future experiments that directly measure the remote potential and impact of tuneable growth kinetics.

epitaxy↗

DOE OSTI2022

Plasma thermal-chemical instability of low-temperature dimethyl ether oxidation in a nanosecond-pulsed dielectric barrier discharge

Plasma stability in reactive mixtures is critical for various applications from plasma-assisted combustion to gas conversion. To generate stable and uniform plasmas and control the transition towards filamentation, the underlying physics and chemistry need a further look. Here, this work investigates the plasma thermal-chemical instability triggered by dimethyl-ether (DME) low-temperature oxidation in a repetitive nanosecond pulsed dielectric barrier discharge. First, a plasma-combustion kinetic mechanism of DME/air is developed and validated using temperature and ignition delay time measurements in quasi-uniform plasmas. Then the multi-stage dynamics of thermal-chemical instability is experimentally explored: the DME/air discharge was initially uniform, then contracted to filaments, and finally became uniform again before ignition. By performing chemistry modeling and analyzing the local thermal balance, it is found that such nonlinear development of the thermal-chemical instability is controlled by the competition between plasma-enhanced low-temperature heat release and the increasing thermal diffusion at higher temperature. Further thermal-chemical mode analysis identifies the chemical origin of this instability as DME low-temperature chemistry. This work connects experiment measurements with theoretical analysis of plasma thermal-chemical instability and sheds light on future chemical control of the plasma uniformity.

repetitive nanosecond pulses↗

DOE OSTI2026

Iron Oxide Reduction Rate Affects Iron Product Morphology

Magnetite concentrates from different parts of the Mesabi Range, exhibiting varying tendencies to encapsulate, were reduced using thermogravimetric analysis (TGA) and a high-temperature confocal scanning laser microscope (CSLM). Gas-phase mass-transfer conditions were intentionally varied by employing two reactors with different geometries: the TGA produced significantly slower reduction, whereas the CSLM setup yielded reduction rates up to 20 times faster under mass-transfer-controlled conditions. A preliminary mechanism is proposed to explain the transition from a porous iron product to a dense encapsulating layer. Encapsulation is interpreted as the outcome of competition between pore creation, driven by the reduction rate, and pore elimination, driven by surface diffusion. When pore formation is insufficient to counteract pore coarsening, a dense iron layer develops and restricts further reduction.

encapsulation↗

DOE OSTI2022

Designing optimal core–shell MOFs for direct air capture

Metal–organic frameworks (MOFs), along with other novel adsorbents, are frequently proposed as candidate materials to selectively adsorb CO 2 for carbon capture processes. However, adsorbents designed to strongly bind CO 2 nearly always bind H 2 O strongly (sometimes even more so). Given that water is present in significant quantities in the inlet streams of most carbon capture processes, a method that avoids H 2 O competition for the CO 2 binding sites would be technologically valuable. Here, in this paper, we consider a novel core–shell MOF design strategy, where a high-CO 2 -capacity MOF “core” is protected from competitive H 2 O-binding via a MOF “shell” that has very slow water diffusion. We consider a high-frequency adsorption/desorption cycle that regenerates the adsorbents before water can pass through the shell and enter the core. To identify optimal core–shell MOF pairs, we use a combination of experimental measurements, computational modeling, and multiphysics modeling. Our library of MOFs is created from two starting MOFs-UiO-66 and UiO-67-augmented with 30 possible functional group variations, yielding 1740 possible core–shell MOF pairs. After defining a performance score to rank these pairs, we identified 10 core–shell MOF candidates that significantly outperform any of the MOFs functioning alone.

42 ENGINEERING↗

DOE OSTI2026

Ion correlations explain kinetic selectivity in diffusion-limited solid-state synthesis reactions

Establishing viable solid-state synthesis pathways for novel inorganic materials remains a major challenge in materials science. Previous pathway design methods using pairwise reaction approaches have navigated the thermodynamic landscape with first-principles data but lack kinetic information, limiting their effectiveness. This gap leads to suboptimal precursor selection and predictions, especially for reactions forming competing phases with similar formation energies, where ion diffusion is a critical influence. Here we demonstrate an inorganic synthesis framework by incorporating machine learning-derived transport properties through ‘liquid-like’ product layers into a thermodynamic cellular reaction model. In the Ba–Ti–O system, known for its competitive polymorphism, we obtain accurate predictions of phase formation with varying BaO:TiO2 ratios as a function of time and temperature. We find that diffusion–thermodynamics interplay governs phase compositions, with cross-ion transport coefficients critical for predicting diffusion-limited selectivity. This work bridges length scales and timescales by integrating solid-state reaction kinetics with first-principles thermodynamics and spatial reactivity.

Atomistic models↗

DOE OSTI2024

Cost‐Effective Layered Oxide – Olivine Blend Cathodes for High‐Rate Pulse Power Lithium‐Ion Batteries

Abstract Sustainability and supply‐chain concerns require lithium‐ion batteries (LIBs) free from critical minerals, such as nickel and cobalt. While recent advances provide encouraging signs that cobalt can be removed, the question remains how much Ni can be removed from Co‐free layered oxide cathodes before sacrificing critical performance metrics. This study highlights the effect of reducing Ni by benchmarking several Co‐free cathodes with decreasing Ni content. Keeping the energy density the same by increasing the charge voltage, cathodes below 80% Ni content exhibit worsened capacity fade due to increasing oxygen release and electrolyte decomposition. Charge transfer and diffusion kinetics are also hindered with increasing Mn content and exacerbated by resistive surface phases formed at high voltages, rendering lower‐Ni, Co‐free cathodes less competitive than high‐Ni cathodes for high energy and power applications. It is demonstrated blending layered oxide with olivine as an effective alternative to deliver energy density and cycling stability comparable to lower‐Ni cathodes with moderate charging voltages. Blending with 30 wt% olivine LiMn 0.5 Fe 0.5 PO 4 (LMFP) virtually eliminates the diffusion limitation of layered oxides at low state‐of‐charge, with enhanced pulse power characteristics rivaling the high‐Ni counterparts. Cathode blending can further reduce the overall Ni content and cost without the performance limitations of lower‐Ni, Co‐free cathodes.

Lee, Steven↗

DOE OSTI2025

Modeling Protein–Protein and Protein–Ligand Interactions by the ClusPro Team in CASP16

ABSTRACT In the CASP16 experiment, our team employed hybrid computational strategies to predict both protein–protein and protein–ligand complex structures. For protein–protein docking, we combined physics‐based sampling—using ClusPro FFT docking and molecular dynamics—with AlphaFold (AF)‐based sampling, followed by AF‐based refinement. Our method produced numerous high‐accuracy complex models, including cases where AF alone failed, underscoring the critical role of physics‐based sampling alongside deep learning‐based refinement. For protein–ligand docking, we integrated the ClusPro LigTBM template‐based approach with a machine learning‐based confidence model for rescoring. The method preserves conserved interaction fragments derived from homologous complexes, followed by local resampling using physics‐based sampling and a diffusion model. Our template‐based strategy achieved a mean lDDT‐PLI of 0.69 across 233 targets, which was highly competitive. These results demonstrate that combining physics‐based modeling with AI‐driven refinement can significantly enhance the accuracy of both protein–protein and protein–ligand structure predictions.

Ashizawa, Ryota [Department of Applied Mathematics↗

DOE OSTI2024

SEI Formation and Lithium-Ion Electrodeposition Dynamics in Lithium Metal Batteries via First-Principles Kinetic Monte Carlo Modeling

The stabilization and enhanced performance of lithium metal batteries (LMBs) depend on the formation and evolution of the Solid Electrolyte Interphase (SEI) layer as a critical component for regulating the Li metal electrodeposition processes. This study employs a first-principles kinetic Monte Carlo (kMC) model to simulate the SEI formation and Li + electrodeposition processes on a lithium metal anode, integrating both the electrochemical electrolyte reduction reactions and the diffusion events giving place to the SEI aggregation processes during battery charge and discharge processes. The model replicates the competitive interactions between organic and inorganic SEI components, emphasizing the influence of the cycling regime. Results indicate that grain boundaries within the SEI facilitate faster lithium-ion transport compared to crystalline regions, crucial for improving the performance and stability of LMBs. The findings underscore the importance of dynamic SEI modeling for further development of next-generation high-energy-density batteries.

25 ENERGY STORAGE↗