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DOE OSTI2024

Life-Cycle Assessment Integration into Scalable Open-Source Numerical Models (LiAISON) for Analyzing Emerging Low-Carbon Technologies

Decarbonizing the industrial sector is a significant challenge in achieving a net-zero greenhouse gas (GHG) emissions economy by 2050 and the Paris Agreement, i.e., a global climate change mitigation target of achieving a maximum average temperature change potential of 1.5 degrees C or less by 2100 with respect to pre-industrial levels. In the United States (US), the industrial sector accounts for 23% of total GHG emissions and is home to a number of hard-to-electrify activities. The chemicals subsector has the single largest subsector emissions profile after direct emissions from fossil fuel combustion and leakage from fossil fuel distribution systems. Within the chemicals subsector, many processes depend on hydrogen or ammonia precursors. Decarbonizing these two commodities would contribute significantly to decarbonizing the industrial sector as hydrogen could also be used for low carbon steel production (e.g., hydrogen-based direct reduction of iron) and other industrial applications. Emerging technologies require the application of prospective life cycle assessment (LCA), which can account for technology (foreground) scaling and process improvements via learning-by-doing, among others. In many cases, the future system context (background) in which the technologies are assumed to operate in is equally relevant. Background scenarios generated by integrated assessment models (IAM) can coherently incorporate potential future dynamics of the energy-climate-human-land system. Further, IAM scenarios are harmonized across socioeconomic and climate change mitigation pathways, which facilitates the comparability of prospective LCAs using different IAMs. We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE). We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Under baseline projections (i.e., no decarbonization goals), neither process reaches parity with the incumbent technology across several environmental metrics. Under the decarbonization scenarios, the underlying sectoral shifts result in declining impacts over time, compared to 2020 levels, except for metal depletion levels, which increase. The background shifts postulate a heavily decarbonized economy and energy system, which help technologies reach parity with SMR between 2040-2050 (RCP2.6) and 2030-2040 (RCP1.9) for global warming. Despite declines across several other metrics over time, neither PtH2 technology break even with SMR by 2100 besides for global warming.

decarbonizing↗

DOE OSTI2024

Electrochemical Imaging of Precisely‐Defined Redox and Reactive Interfaces

Abstract Understanding the diverse electrochemical reactions occurring at electrode‐electrolyte interfaces (EEIs) is a critical challenge to developing more efficient energy conversion and storage technologies. Establishing a predictive molecular‐level understanding of solid electrolyte interphases (SEIs) is challenging due to the presence of multiple intertwined chemical and electrochemical processes occurring at battery electrodes. Similarly, chemical conversions in reactive electrochemical systems are often influenced by the heterogeneous distribution of active sites, surface defects, and catalyst particle sizes. In this mini review, we highlight an emerging field of interfacial science that isolates the impact of specific chemical species by preparing precisely‐defined EEIs and visualizing the reactivity of their individual components using single‐entity characterization techniques. We highlight the broad applicability and versatility of these methods, along with current state‐of‐the‐art instrumentation and future opportunities for these approaches to address key scientific challenges related to batteries, chemical separations, and fuel cells. We establish that controlled preparation of well‐defined electrodes combined with single entity characterization will be crucial to filling key knowledge gaps and advancing the theories used to describe and predict chemical and physical processes occurring at EEIs and accelerating new materials discovery for energy applications.

Edgecomb, Joseph↗

DOE OSTI2024

Electrochemical Imaging of Precisely‐Defined Redox and Reactive Interfaces

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Influence of Fiber Orientation on Deformation of Additive Manufactured Composites

Anisotropy caused by flow-induced fiber orientation of discontinuous fibers within the extrudate in the Extrusion Deposition Additive Manufacturing (EDAM) process gives rise to anisotropic shrinkage in printed parts and thereby, final part deformations. Three fiber orientation states, described by the second-order orientation tensor, were investigated to determine their influence upon final geometry. Two material systems were investigated including a short glass fiber-reinforced polyamide and a short carbon fiber-reinforced polyamide. A curvilinear geometry was modeled and printed virtually in the thermo-mechanical simulation, ADDITIVE3D©. The scale of the printed geometry was in the range of 300–400 mm and contained three semicircular geometry regions connected to linear regions, thereby inducing significant magnification of the spring-in deformation. The predicted deformation of the printed geometry for the three fiber orientation states and two material systems were compared. The deformation predicted for glass fiber-filled polyamide and carbon fiber-filled polyamide of the same fiber orientation states showed comparable deformations. In conclusion, the largest residual deformation was shown to correspond to the orientation tensor with the greatest degree of anisotropy.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Influences of an entrainment–mixing parameterization on numerical simulations of cumulus and stratocumulus clouds

Abstract. Different entrainment–mixing processes can occur in clouds; however, a homogeneous mixing mechanism is often implicitly assumed in most commonly used microphysics schemes. Here, we first present a new entrainment–mixing parameterization that uses the grid mean relative humidity without requiring the relative humidity of the entrained air. Then, the parameterization is implemented in a microphysics scheme in a large eddy simulation model, and sensitivity experiments are conducted to compare the new parameterization with the default homogeneous entrainment–mixing parameterization. The results indicate that the new entrainment–mixing parameterization has a larger impact on the number concentration, volume mean radius, and cloud optical depth in the stratocumulus case than in the cumulus case. This is because inhomogeneous and homogeneous mixing mechanisms dominate in the stratocumulus and cumulus cases, respectively, which is mainly due to the larger turbulence dissipation rate in the cumulus case. Because stratocumulus clouds break up during the dissipation stage to form cumulus clouds, the effects of this new entrainment–mixing parameterization during the stratocumulus dissipation stage are between those during the stratocumulus mature stage and the cumulus case. A large aerosol concentration can enhance the effects of this new entrainment–mixing parameterization by decreasing the cloud droplet size and evaporation timescale. The results of this new entrainment–mixing parameterization with grid mean relative humidity are validated by the use of a different entrainment–mixing parameterization that uses parameterized entrained air properties. This study sheds new light on the improvement of entrainment–mixing parameterizations in models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Distinct Melt Infusion Architectures of Antiperovskite Solid Electrolytes

Antiperovskite solid electrolytes are an emerging class of lithium‐ion conductors distinguished by their unusually low melting points, enabling scalable, low‐temperature processing routes not accessible to most solid electrolytes. In this work, we synthesize phase‐pure chloride (Cl), bromide (Br), and mixed halide (ClBr) variants of antiperovskites and investigate their ionic conductivities in both powder and hot‐pressed forms. Hot pressing significantly enhances conductivity across all compositions, while energy‐dispersive X‐ray spectroscopy (EDS) of the mixed halide system reveals halide surface migration during densification. We further investigate the melt‐infiltration behavior of these electrolytes into substrates relevant to solid‐state battery architectures, including Al and Cu current collectors, conventional NMC and LFP cathodes, and a foamed NMC cathode with a highly porous architecture. The foamed cathode enables deep and uniform electrolyte penetration, highlighting the role of electrode architecture in facilitating melt infiltration. Across all substrates, electrolyte halide chemistry strongly influences wetting behavior, penetration depth, and resulting microstructural morphology. Together, these results establish clear processing–structure relationships for melt‐infiltrated antiperovskite solid electrolytes and demonstrate how electrolyte chemistry and electrode architecture govern interfacial morphology during integration, providing practical guidelines for processing and structural design in solid‐state battery systems.

antiperovskite↗

DOE OSTI2025

Identifying impacts of contact tracing on HIV epidemiological inference from phylogenetic data

Abstract Robust sampling methods are foundational to inferences using phylogenies. Yet the impact of using contact tracing, a type of non-uniform sampling used in public health applications such as infectious disease outbreak investigations, has not been investigated in the molecular epidemiology field. To understand how contact tracing influences a recovered phylogeny, we developed a new simulation tool called SEEPS (Sequence Evolution and Epidemiological Process Simulator) that allows for the simulation of contact tracing and the resulting transmission tree, pathogen phylogeny, and corresponding virus genetic sequences. Importantly, SEEPS takes within-host evolution into account when generating pathogen phylogenies and sequences from transmission histories. Using SEEPS, we demonstrate that contact tracing can significantly impact the structure of the resulting tree, as described by popular tree statistics. Contact tracing generates phylogenies that are less balanced than the underlying transmission process, less representative of the larger epidemiological process, and affects the internal/external branch length ratios that characterize specific epidemiological scenarios. We also examined real data from a 2007–2008 Swedish HIV-1 outbreak and the broader 1998–2010 European HIV-1 epidemic to highlight the differences in contact tracing and expected phylogenies. Aided by SEEPS, we show that the data collection of the Swedish outbreak was strongly influenced by contact tracing even after downsampling, while the broader European Union epidemic showed little evidence of universal contact tracing, agreeing with the known epidemiological information about sampling and spread. Overall, our results highlight the importance of including possible non-uniform sampling schemes when examining phylogenetic trees. For that, SEEPS serves as a useful tool to evaluate such impacts, thereby facilitating better phylogenetic inferences of the characteristics of a disease outbreak. SEEPS is available at https://github.com/MolEvolEpid/SEEPS.

Virology↗

DOE OSTI2021

Enhanced resistance to decay of imprinted nanopatterns in thin films by bare nanoparticles compared to polymer-grafted nanoparticles

We extend a previous study on the influence of nanoparticles on the decay of nanoimprinted polymer film patterns to compare the effects of “bare” silica (SiO 2 ) nanoparticles and SiO 2 nanoparticles with grafted polymer layers having the same chemical composition as the polymer matrix. This method involves nanoimprinting substrate-supported polymer films using a pattern replicated from a digital versatile disc (DVD), and then annealing the patterned polymer nanocomposite films at elevated temperatures to follow the decay of the topographic surface pattern with time by atomic force microscopy imaging after quenching. We quantified the relaxation of the pattern height (“slumping”) and determined the relaxation time τ for this pattern decay process as a function of nanoparticle filler type and concentration to determine how nanoparticle additives influence relative film stability. Attractive interactions between the bare nanoparticles and the polymer matrix significantly enhance the thermal resilience of the nanopatterns to decay, compared to those of the particle brushes, wherein the particle core interactions are screened from the matrix via the brush layer. A novel aspect of this method is that it readily lends itself to in situ film relaxation measurements in a manufacturing context. We observe that the relaxation time of the pattern relaxation exhibits entropy–enthalpy compensation in the free energy parameters governing the pattern relaxation process as a function of temperature, irrespective of the NP system used, consistent with our previous experimental and computational studies.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Creep Deformation and Damage Mechanisms in an Advanced High-Temperature Additively Manufactured Nickel-Base Superalloy

Abstract This research investigates the processing–structure–properties–performance relationship in a novel nickel-base superalloy, ABD ® -900AM, designed for extreme environments. Specifically tailored for additive manufacturing (AM), ABD ® -900AM maintains mechanical integrity at high temperatures and is comparable to other nickel-based superalloys with a 30–40% gamma-prime volume fraction. A comprehensive study was conducted using laser-beam powder bed fusion and electron-beam powder bed fusion methods. Factors such as heat treatment, porosity, build orientation, and hot isostatic pressing were evaluated to understand their effects on microstructure and mechanical performance. Microstructural characterization revealed significant differences in grain size and orientation across build processes and heat treatments. High-temperature mechanical testing indicated that grain size, heat treatment, and orientation significantly influence creep behavior. A super-solvus heat treatment led to recrystallization and grain growth, significantly improving creep properties compared to a near-solvus heat treatment. Various creep mechanisms were identified across different conditions, and creep rupture models were developed for each build process. Post-test microstructural analysis showed grain boundary damage, with differences in creep cavitation morphology under varying stress conditions. It was shown that MC carbides grow at the expense of gamma-prime near grain boundaries, leading to precipitate-free zones in specimens tested at higher temperatures. This study fills a significant gap in fundamental research by offering a deeper insight into the high-temperature mechanical behavior of additively manufactured nickel-base superalloys. It also explores critical research questions regarding the role of carbides and the significance of heat treatment. The insights gained enhance confidence in the industry adoption of ABD ® -900AM and similar alloys for high-temperature applications, bridging the knowledge gap and supporting the development of reliable AM processes for extreme environments.

Bridges, Alex (ORCID:000000030338759X)↗

DOE OSTI2024

Evaluation of data collection bias of third molar stages of mineralisation for age estimation in the living

Abstract Age assessment of the living is a fundamental procedure in the process of human identification, in order to guarantee fair treatment of individuals, which has ethical, civil, legal, and medical repercussions. The careful selection of the appropriate methods requires evaluation of several parameters: accuracy, precision of the method, as well as its reproducibility. The approach proposed by Mincer et al. adapted from Demirjian et al. exploring third molar mineralisation, is one of the most frequently considered for age estimation of the living. Thus, this work aims to assess potential bias in the data collection when applying the classification stages for dental mineralisation adapted by Mincer et al. A total of 102 orthopantomographs, of clinical origin, belonging to individuals aged between 12 and 25 years ($ \bar{\textit x} $ = 20.12 years, SD = 3.49 years; 65 females, 37 males, all of Portuguese nationality) were included and a retrospective analysis performed by five observers with different levels of experience (high, average, and basic). The performance and agreement between five observers were evaluated using Weighted Cohen’s Kappa and the Intraclass Correlation Coefficient. To access the influence of impaction on third molar classification, variables were tested using ordinal logistic regression Generalised Linear Model. It was observed that there were variations in the number of teeth identified among the observers, but the agreement levels ranged from moderate to substantial (0.4–0.8). Upon closer examination of the results, it was observed that although there were discernible differences between highly experienced observers and those with less experience, the gap was not as significant as initially hypothesised, and a greater disparity between the classifications of the upper (0.24–0.49) and lower third molars (>0.55) was observed. When bone superimposition is present, the classification process is not significantly influenced; however, variation in teeth angulation affects the assessment. The results suggest that with an efficient preparation, the level of experience as a factor can be overcome. Mincer and colleague's classification system can be replicated with ease and consistency, even though the classification of upper and lower third molars presents distinct challenges.

de Oliveira Santos, Inês (ORCID:0000000267324347)↗

DOE OSTI2024

Enhancing Site Screening for Underground Hydrogen Storage: Qualitative Site Quality Assessment - SHASTA: Subsurface Hydrogen Assessment, Storage, and Technology Acceleration Project

The global shift towards renewable energy sources to mitigate fossil fuel dependency and meet carbon emission targets by 2050 has underscored the importance of innovative solutions to address energy supply-demand imbalances. Underground Hydrogen Storage (UHS) has emerged as a promising strategy to store excess renewable energy in subsurface formations for future retrieval and utilization. This report focuses on enhancing the site screening process for UHS facilities. By drawing on insights from prior research to identify key criteria influencing site suitability, our objective is to present a comprehensive set of sixteen specific criteria essential for refining the selection of UHS sites. These criteria cover various aspects such as reservoir performance, legal access, regulatory compliance, economic viability, public acceptance, and safety and security considerations. Our proposed methodology allows users to evaluate potential sites using binary responses, transitioning from isolated factors to broader considerations that facilitate a qualitative assessment of site suitability. This method enables comparative analysis and informed decision-making, supporting stakeholders in the site selection process. Our approach is designed as a guiding framework rather than a rigid template for site screening, emphasizing the importance of customizing approaches to individual circumstances. As UHS site development project evolves, adopting a comprehensive selection methodology that integrates holistic evaluations will be essential for ensuring efficient and effective site screening processes tailored to specific project needs.

08 HYDROGEN↗

DOE OSTI2024

Enhancing Site Screening for Underground Hydrogen Storage: Qualitative Site Quality Assessment - SHASTA: Subsurface Hydrogen Assessment, Storage, and Technology Acceleration Project

08 HYDROGEN↗

DOE OSTI2023

MHC-II dynamics are maintained in HLA-DR allotypes to ensure catalyzed peptide exchange

Presentation of antigenic peptides by major histocompatibility complex class II (MHC-II) proteins determines T helper cell reactivity. The MHC-II genetic locus displays a large degree of allelic polymorphism influencing the peptide repertoire presented by the resulting MHC-II protein allotypes. During antigen processing, the human leukocyte antigen (HLA) molecule HLA-DM (DM) encounters these distinct allotypes and catalyzes exchange of the placeholder peptide CLIP by exploiting dynamic features of MHC-II. Here, we investigate 12 highly abundant CLIP-bound HLA-DRB1 allotypes and correlate dynamics to catalysis by DM. Despite large differences in thermodynamic stability, peptide exchange rates fall into a target range that maintains DM responsiveness. A DM-susceptible conformation is conserved in MHC-II molecules, and allosteric coupling between polymorphic sites affects dynamic states that influence DM catalysis. As exemplified for rheumatoid arthritis, we postulate that intrinsic dynamic features of peptide–MHC-II complexes contribute to the association of individual MHC-II allotypes with autoimmune disease.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

wmpy-power: A Python package for process-based regional hydropower simulation

Hydropower is an important source of renewable energy in many parts of the world. The generation potential for a hydropower facility can vary greatly due to fluctuations in precipitation and snowmelt patterns impacting streamflow and reservoir storage. Human activities such as irrigation, manufacturing, and hydration can also influence water availability at nearby and downstream facilities. wmpy-power--the hydropower model described in this work--is process-based, leveraging explicit reservoir storage and release data to address impacts on hydropower from climate change and human adaptive behaviors to inform long-term planning and resource-adequacy considerations.

13 HYDRO ENERGY↗

DOE OSTI2023

Rapid eco‐phenotypic feedback and the temperature response of biomass dynamics

Biomass dynamics capture information on population dynamics and ecosystem-level processes (e.g., changes in production over time). Understanding how rising temperatures associated with global climate change influence biomass dynamics is thus a pressing issue in ecology. The total biomass of a species depends on its density and its average mass. Consequently, disentangling how biomass dynamics responds to increasingly warm and variable temperatures ultimately depends on understanding how temperature influences both density and mass dynamics. Here, we address this issue by keeping track of experimental microbial populations growing to carrying capacity for 15 days at two different temperatures, and in the presence and absence of temperature variability. We develop a simple mathematical expression to partition the contribution of changes in density and mass to changes in biomass and assess how temperature responses in either one influence biomass shifts. Moreover, we use time-series analysis (Convergent Cross Mapping) to address how temperature and temperature variability influence reciprocal effects of density on mass and vice versa. We show that temperature influences biomass through its effects on density and mass dynamics, which have opposite effects on biomass and can offset each other. We also show that temperature variability influences biomass, but that effect is independent of any effects on density or mass dynamics. Last, we show that reciprocal effects of density and mass shift significantly across temperature regimes, suggesting that rapid and environment-dependent eco-phenotypic dynamics underlie biomass responses. Overall, our results connect temperature effects on population and phenotypic dynamics to explain how biomass responds to temperature regimes, thus shedding light on processes at play in cosmopolitan and abundant microbes as the world experiences increasingly warm and variable temperatures.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

A new bioenergy model that simulates the impacts of plant‐microbial interactions, soil carbon protection, and mechanistic tillage on soil carbon cycling

Abstract Advancing our predictive understanding of bioenergy systems is critical to design decision tools that can inform which feedstock to plant, where to plant it, and how to manage its production to provide both energy and ecosystem carbon (C) benefits. Here, we lay the foundation for that advancement by integrating recent developments in the science of belowground processes in shaping the C cycle into a new bioenergy model, FUN‐BioCROP (Fixation and Uptake of Nitrogen‐Bioenergy Carbon, Rhizosphere, Organisms, and Protection). We show that FUN‐BioCROP can approximate the historical trajectory of soil C dynamics as natural ecosystems were successively converted into intensive agriculture and bioenergy systems. This ability relies in part on a novel tillage representation that mechanistically models tillage as a process that increases microbial access to C. Importantly, the impacts of tillage and feedstock choice also influence FUN‐BioCROP simulations of warming responses with no‐till perennial feedstocks, miscanthus, and switchgrass, having more C that is unprotected and susceptible to warming than tilled annual feedstocks like corn–corn–soybean. However, this susceptibility to warming is balanced by a greater potential for increases in belowground C allocation to enhance soil C stocks in perennial systems. Collectively, our model results highlight the importance of belowground processes in evaluating the ecosystem C benefits of bioenergy production.

09 BIOMASS FUELS↗

DOE OSTI2020

Revealing transient powder-gas interaction in laser powder bed fusion process through multi-physics modeling and high-speed synchrotron x-ray imaging

Laser powder bed fusion (LPBF) is an emerging metal additive manufacturing process. The gas-driven powder motions in laser powder bed fusion have significant influence on the build quality. However, the transient powder-gas interaction has not been well understood due to the challenges in quantitative experiment measurements. In this work, the powder-gas interaction for a single pulse laser illuminating on the powder bed is studied. We establish a multi-physics model to simulate the complex liquid/gas flow as well as the gas-driven powder motions, which is substantiated by high-speed synchrotron x-ray imaging. We identify and quantify four characteristic modes of powder-gas interaction in LPBF. The motion of a powder is controlled by one or multiple interaction modes collectively. As revealed by simulations and confirmed by experiments, powders can merge into the molten pool from its rim, be ejected at different divergence angles (powder spattering), or dive into the molten pool to cause significant molten pool fluctuation. Overall, our results provide insights toward the driving forces controlling the dynamic powder behavior, which pave the way for reducing structure defects during the build process.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Densification, microstructure, and mechanical properties of Mo–30W alloys fabricated from conditioned powders

Refractory alloys, such as molybdenum-based systems, are attracting growing interest for applications in extreme environments, such as in the nuclear and aerospace industries. Recent advances in sintering technologies, coupled with mechanical alloying, have enabled the tailored design of these alloys by leveraging powder characteristics to control final microstructures and mechanical properties. In this study, Mo-30W alloys were fabricated using electric field-assisted sintering (EFAS) from ball-milled powders with and without hydrogen treatment to investigate the influence of surface oxides on material properties and sintering behavior. The results revealed that samples processed from as-ball-milled powder contained a high density of oxides within the microstructure, whereas oxide presence was significantly reduced in samples fabricated from hydrogen-treated powders. Interestingly, the two powder types led to opposite trends in grain size distribution: samples from untreated powders exhibited grain refinement from sample periphery to the center, while samples from hydrogen-treated powders showed grain coarsening toward the center. This behavior is attributed to temperature gradients present during sintering due to electrical percolation pathway differences during Joule heating. The powder surface oxides may have influenced the temperature distribution and grain evolution. Microhardness profiles measured along both axial and thickness directions were consistent with the grain size distribution. Furthermore, oxide films on powder surfaces have delayed densification by hindering particle necking and atomic diffusion during sintering.

36 - MATERIALS SCIENCE↗