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DOE OSTI2024

Recent Advances of PyROS: A Pyomo Solver for Nonconvex Two-Stage Robust Optimization in Process Systems Engineering

The document presents recent algorithmic and implementation advances of the two-stage robust optimization (RO) solver PyROS, and a benchmarking study which demonstrates the utility of PyROS for two-stage RO problems. The advances include extensions of the scope of PyROS to models with uncertain variable bounds, improvements to the initializations of the subproblems used by the underlying cutting set algorithm, and extensions of the uncertainty set interfaces. The benchmarking study is performed on a library of over 8,500 instances, with variations in the nonlinearities, degree-of-freedom partitioning, uncertainty sets, and polynomial decision rule approximations. An amine-based CO2 capture case study is presented to demonstrate the utility of PyROS for large-scale process models. Overall, the results highlight the effectiveness of PyROS for obtaining robust solutions to optimization problems with uncertain equality constraints.

Sherman, Jason↗

DOE OSTI2024

Advanced Perovskite Solar Cells and Modules

The “Advanced perovskite Cells and Modules” research project was the final agreement focused on enhancing perovskite solar cell (PSC) technologies funded by the US Department of Energy's Solar Energy Technologies Office. The project was designed to address three crucial areas in PSC development: stability, manufacturability, and efficiency. The project was then structured around three main tasks, each targeting one of these strategic goals. The team of experienced researchers in these materials worked collaboratively to address the targets outlined in the technical work plan. building on existing PSC research while also exploring promising new concepts arising in the field. An overview of each primary task is summarized below: Task 1 Stability: This first task, aims to identify material characteristics and metrics that can help predict the primary degradation mechanisms impacting PSC stability. This involved developing specific device tests based on hypotheses regarding mechanisms impacting stability, including fast failure procedures to speed up PSC development and improvement. Various strategies to enhance stability, like incorporating additives, post-treatments, novel contact materials etc. were developed using this fast feedback approach. The relationships between indoor and outdoor stresses were also validated. Task 2 Manufacturability: This second task, focused on creating a scalable production process for PSCs. Initially the objective is to establish a best-known method for a 182 cm2 minimodule. However, given resource limitations, these metrics were modified to focus on the other goal of outlined in the TWP. Specifically, this task worked to demonstrate the transferability of this best-known method to another research institution. Work scope in this area was expanded to material purity and understanding of reagent/process relationships. Examination of other difficulties in PSC production and potential solutions for large-scale production were also evaluated. Given challenges observed in process transfer, work to develop data infrastructure and recording tools for processing of material and devices was then also prioritized in this task. Task 3 Efficiency: This task was focused on improvements to PCE, while still considering Task 1 and Task 2 goal. The efforts targeted a PCE greater than 22% with a T95 exceeding 1000 hours at 25°C in a nitrogen environment for lab-scale devices (approximately 0.1 cm2 devices) across a range of solar-relevant perovskite compositions, including wide-gap (around 1.7 eV) and low-gap (around 1.3 eV) materials, using standard metal contacts. This work then provides a foundation for MHP-based tandem efforts undertaken in other projects and the All-MHP tandem efforts outlined in this projects TWP. Work in this project emphasized disseminating its findings through peer-reviewed publications (PRP), conference presentations, and industrial collaborations. Significant products were produced in all these areas, over 53 peer reviewed publications, 32 conference presentations and industrial investment based on NLR assistance on precompetitive challenges. The team also developed significant intellectual property and awards for their technical excellence, innovations and leadership. The team also leveraged traditional and social media platforms to engage with stakeholders and the public.

14 SOLAR ENERGY↗

DOE OSTI2025

High-Resolution Full-Field Structural Microscopy of the Voltage-Induced Filament Formation in VO 2 -Based Neuromorphic Devices

In order to make neuromorphic functions in memristive devices more efficient, information about the structural properties of filament formation at the micro- and mesoscopic scales is necessary. Despite extensive research on VO 2 , a key material due to its filament formation, local operando structural measurements remain challenging and often involve destructive specimen preparation and long rastering times, greatly limiting the scope of experimental studies. Utilizing dark-field X-ray microscopy (DFXM), a fullfield imaging modality, structural signatures of the filament formation process operando are revealed in VO 2 devices. DFXM experiments illustrate that rutile filaments contain isolated monoclinic clusters, indicating structural nonuniformity interior to the filament. The formation of the rutile phase beneath device electrodes was shown to precede filament development, followed by the formation of filament paths guided by nucleation sites within the device. Finally, a medium-term (<30 min) memory mechanism is observed in VO 2 , mediated by sites within the device gap that tend to switch at significantly lower voltages after electrical cycling, a tendency that persists through a brief thermal reset. High spatial resolution, large field-of-view, structure selectivity, and fast signal acquisition of DFXM provided insight into structural features of the filamentary channel and surrounding regions during voltage cycling.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Non-contact imaging of terahertz surface currents with aperture-type near-field microscopy

Terahertz (THz) near-field imaging and spectroscopy provide valuable insights into the fundamental physical processes occurring in THz resonators and metasurfaces on the subwavelength scale. However, so far, the mapping of THz surface currents has remained outside the scope of THz near-field techniques. In this study, we demonstrate that aperture-type scanning near-field microscopy enables non-contact imaging of THz surface currents in subwavelength resonators. Through extensive near-field mapping of an asymmetric D-split-ring THz resonator and full electromagnetic simulations of the resonator and the probe, we demonstrate the correlation between the measured near-field images and the THz surface currents. The observed current dynamics in the interval of several picoseconds reveal the interplay between several excited modes, including dark modes, whereas broadband THz near-field spectroscopy analysis enables the characterization of electromagnetic resonances defined by the resonator geometry.

Norman, Sarah↗

DOE OSTI2025

NIF Enhanced Yield Capability Conceptual Design Review Report

The purpose of the NIF Enhanced Yield Capability (EYC) Conceptual Design Review was to evaluate key aspects of the design and assess readiness to move to the next phase of the project. The NNSA accepted the NIF Integrated Product Review Board (IPRB) process as an appropriate means of conducting the review. The review committee finds that the NIF EYC Design Team has successfully addressed the review scope objectives. No Type 1 action items or liens were identified during the technical review. Some recommendations and observations are recorded below to assist the team.

42 ENGINEERING↗

DOE OSTI2024

Heat Battery for Electrical Grid Energy

In this paper, the fundamental principles from the Georgetown Systems Engineering Fundamentals course will be leveraged to provide a viable solution to the problem of providing cost effective energy storage for renewable electricity generation. As described in the need statement, this is necessary due to the non-dispatchable nature of renewable energy sources. Upon describing the need, several key stakeholders were identified, who may or may not directly interact with the system. They provided several characteristics and capabilities that the system should contain, as well as specific key acceptance criteria which serve as a pass/fail metric for the concept selection process. Out of three different concepts, a Pugh matrix was used to determine that a heat battery system would be the right fit for the scope of work needing to be done.

25 ENERGY STORAGE↗

DOE OSTI2025

NE-COST plug-in: Expanding ACCERT's Capabilities for Life-Cycle Cost Modeling

The Algorithm for the Capital Cost Estimation of Reactor Technologies (ACCERT) is a structured methodology and software tool designed to simplify and standardize cost estimation for nuclear reactor technologies [1]. By utilizing a relational database structure and modular cost estimation algorithms, ACCERT delivers a robust, flexible, and scalable framework for evaluating costs across various reactor types and configurations [2]. The recent integration of the NE-COST plugin further expands ACCERT’s scope by introducing detailed life-cycle cost modeling and probabilistic analysis of uncertainties. This addition enables users to evaluate costs across front-end processes such as uranium enrichment and fabrication, as well as back-end activities including waste disposal and geologic storage. Through Monte Carlo statistical cost simulations, the plugin provides probabilistic insights into cost ranges, offering critical decision-making support for stakeholders including reactor developers, policymakers, and researchers.

Zhou, Jia↗

DOE OSTI2026

Reacting CO 2 with Light Alkanes to Value-Added Products

Catalytic conversion of anthropogenic carbon dioxide (CO 2 ) into value-added products is a promising strategy to mitigate global carbon emissions. Concurrently, the shale gas revolution has provided an abundant supply of light alkanes (methane, ethane, propane, and butane), presenting a unique opportunity to employ these underutilized hydrocarbons as an effective, low-cost hydrogen source for CO 2 reduction. In this Perspective, we summarize past efforts, current state, and future opportunities for reacting CO 2 with light alkanes to generate a diverse range of value-added products. Compared with direct alkane conversion, the introduction of CO 2 fundamentally alters reaction thermodynamics and kinetics, enabling selective C–H and C–C bond activation while suppressing catalyst deactivation from coke formation. Building on decades of research in dry reforming and CO 2 -assisted dehydrogenation, recent advances in catalyst design have enabled CO 2 -assisted dehydrogenation processes that approach chemical equilibrium for the selective production of olefins and syngas. Importantly, advances in catalyst design and reactor engineering have further expanded the product scope beyond gas-phase (syngas and olefins) to include liquid-phase (oxygenates and aromatics), and solid-phase products (carbon nanomaterials). We highlight key catalyst design principles for controlling reaction pathways and discuss major challenges and opportunities in developing selective and versatile platforms for the simultaneous upgrading of CO 2 and light alkanes.

CO2↗

DOE OSTI2024

Shifts in evolutionary lability underlie independent gains and losses of root-nodule symbiosis in a single clade of plants

Abstract Root nodule symbiosis (RNS) is a complex trait that enables plants to access atmospheric nitrogen converted into usable forms through a mutualistic relationship with soil bacteria. Pinpointing the evolutionary origins of RNS is critical for understanding its genetic basis, but building this evolutionary context is complicated by data limitations and the intermittent presence of RNS in a single clade of ca. 30,000 species of flowering plants, i.e., the nitrogen-fixing clade (NFC). We developed the most extensive de novo phylogeny for the NFC and an RNS trait database to reconstruct the evolution of RNS. Our analysis identifies evolutionary rate heterogeneity associated with a two-step process: An ancestral precursor state transitioned to a more labile state from which RNS was rapidly gained at multiple points in the NFC. We illustrate how a two-step process could explain multiple independent gains and losses of RNS, contrary to recent hypotheses suggesting one gain and numerous losses, and suggest a broader phylogenetic and genetic scope may be required for genome-phenome mapping.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

OPEN-Augmented Reality GUI for Bioenergy Crop Phenotyping and Precision Agriculture (Donald Danforth Plant Science Center Final Scientific Technical Report)

The project led by the Donald Danforth Plant Science Center, in collaboration with Arizona State University, George Washington University, and Saint Louis University, has made significant strides in advancing the phenotypic analysis of bioenergy crops through the development of an innovative AI processing pipeline. This initiative was primarily funded by ARPA-E, with additional cost-sharing provided by the participating institutions. The project successfully utilized a variety of sensors—3D scanners, thermal, RGB, and hyperspectral—to refine algorithms for data-driven trait signature identification and improve the classification and visualization of plant traits. The developed AI processing pipeline is capable of handling the complex, multidimensional data characteristic of dynamic agricultural environments. 1) Contributions to understanding: The research has advanced the field of plant phenomics by showcasing the synergistic use of various sensor data to enhance the precision of trait analysis in bioenergy crops. Through the integration of 3D scanners, thermal, RGB, and hyperspectral sensors, the project has developed robust data-driven trait signature algorithms and visualization techniques. These innovations have facilitated detailed monitoring and management of plant traits, providing vital insights into plant growth dynamics and stress responses. Further, the project has broadened our understanding of how machine learning can be effectively applied in multi-sensor environments to refine trait analysis. By leveraging diverse datasets, the research has not only improved the accuracy of phenotypic assessments but also established a versatile methodological framework that can be extended beyond agriculture to other fields requiring detailed phenotypic analysis. 2) Technical effectiveness and economic feasibility: The AI processing pipeline developed in this project demonstrated significant technical effectiveness, achieving high throughput analysis of extensive phenotypic data and meeting targeted accuracies. This system exemplified the capability of advanced machine learning technologies to efficiently manage and analyze large, complex datasets. Economically, the implementation of the project-developed pipelines may offer substantial cost savings across multiple sectors. It enhances data analysis processes and significantly reduces the need for manual data interpretation, thereby decreasing both the time and resources required. 3) Public benefit: The project has significantly broadened the scope of agricultural methodologies to enhance phenotypic analysis, with potential applications in various sectors beyond agriculture. Additionally, the initiative fostered an enriching educational and collaborative environment, significantly enhancing the technical skills of participants. It also made substantial contributions to the scientific community by providing open-access data sets and tools, encouraging ongoing research and development across various disciplines. Overall, the project not only met its scientific goals but also showcased the extensive utility of integrating advanced machine learning and sensor data analysis technologies. These advancements have proven instrumental in driving forward both theoretical research and practical applications, setting a strong foundation for future explorations and innovations in data-driven science.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Emergence of deep eutectic solvents (DES): chemistry, preparation, properties, and applications in biorefineries and critical materials

The emergence of renewable deep eutectic solvents (DES) as clean and efficient catalysts and solvents has created new opportunities for lignocellulosic biorefineries and critical material sectors, including chemical, energy, pharmaceutical, textile, and hydrometallurgical industries. This review provides an in-depth overview of DES, covering their chemistry, classifications, preparation methods, processing characteristics, and recyclability, while highlighting their unique attributes and industry relevant applications. Emphasis is placed on the integration of DES into advanced biorefinery systems, focusing on their tunable physicochemical and thermodynamic properties for biomass pretreatment and the production of value-added products. The review explores how DES can be tuned for selective dissolution of biomass components and evaluates production and valorization of DES-derived biochemicals, with attention to lignin extraction mechanisms and conversion of biomass into bioproducts and biofuels. Beyond biorefineries, the scope extends to DES applications in electrochemical energy devices, where they serve as electrolytes, synthesis media for electrode materials, and leaching agents in battery recycling. The multifunctional roles of DES in pharmaceutical, hydrometallurgical, and textile sectors are also explored for contributions to sustainable processing. Finally, the review identifies future research directions, outlining benefits, challenges, and knowledge gaps, for continued industrial development.

09 BIOMASS FUELS↗

DOE OSTI2026

A Field Guide to Corralling the Chaos: A Conceptual Framework for Using Models to Guide Opportunistic Field Studies of Natural Disturbances

Watersheds regulate biogeochemical processes and provide ecosystem services to human societies, but disturbances can fundamentally alter these processes across space and time. Determining when and where to sample to capture disturbance impacts in watersheds remains a central challenge. Manipulation studies and long-term monitoring are often constrained by scope, and opportunistic studies often lack pre-disturbance data needed to statistically determine disturbance impacts. We identify a persistent knowledge gap: the absence of a clear, transferable framework to guide opportunistic disturbance research where pre-disturbance data collection is not a feasible option. To address this gap, we present a conceptual framework that intentionally integrates modeling and empirical observation in an iterative, stepwise model–experiment workflow. We demonstrate its application through two contrasting case studies: wildfire impacts on headwater streams using a pre-disturbance preparedness approach, and saltwater flooding impacts on coastal forests using an ‘ex-post-facto’ approach. From these applications, we assess strengths, limitations, and the critical role of team science for transferability across disturbance types and study designs. Broadly, this framework offers a scalable path towards more rigorous, timely, and actionable disturbance science that can inform watershed management, hazard risk reduction, and ecosystem resilience.

Coastal Biogeochemistry↗

DOE OSTI2025

A Review of Tank 48H Treatment of Tetraphenylborate with Permanganate

Tank 48H contains roughly 270,000 gallons of radioactive waste material. The waste stored in this tank was to be processed in multiple stages utilizing facilities at the Savannah River Site (SRS) almost 30 years ago. The In-Tank Precipitation Process (ITP) was initiated in Tank 48H, which precipitated highly radioactive cesium-137 using sodium tetraphenylborate (NaTPB). While the process succeeded in precipitating the Cs, Sr, and other actinides, it also generated an unexpectedly large amount of benzene. The evolved benzene created a safety concern and made the waste incompatible with further downstream processing. This halted the ITP, and a new method of treatment was required to continue processing the legacy waste contained in Tank 48H. A myriad of treatment options have been proposed with multiple teams of researchers assembled to work on this highly complex issue over the last few decades. This review investigated one potentially viable treatment option, in-tank oxidation with sodium permanganate. Permanganate has been well known in literature as a strong oxidizing agent for organic compounds, as well as being utilized at the Savannah River Site (SRS) in other processes. A small number of studies have been conducted utilizing waste simulants to evaluate the use of permanganate as an oxidant for tetraphenylborate (TPB). A search of the literature and data from these studies indicates that permanganate could be a viable treatment for destruction of TPB in Tank 48H. While the scoping studies had a small number of individual experiments and nonideal conditions, the permanganate decomposed up to 90% of the TPB. A free hydroxide concentration above 1.0 M is required for tank corrosion control. Simulant studies indicate no decrease in TPB decomposition by permanganate until pH 14. The simulant studies show an increase in TPB decomposition as the temperature of the solution is increased to 40 °C. The post-reaction analysis of previous simulant tests did not look at all of the organic degradation products. Investigations into what these organic products are and in what quantity will help guide determinations as to whether the downstream processing facilities are able to handle the material that will be generated. Study on the time frame for the reaction between permanganate and TPB should be investigated as the literature reports only extend out to two weeks reaction time. The permanganate treatment conditions indicate no corrosion control concerns and a longer timescale reaction may be needed for in-tank treatment. In addition, further study would be useful to identify a lower boundary condition for the ratio of TPB and oxidant. The simulant tests applied large excesses of permanganate, and this may be unnecessary. The size constraint of the tank means that there will be practical limitations on the amount of sodium permanganate that can be added to the tank. The amount of permanganate should be minimized as much as possible while still ensuring decomposition of the TPB to minimize the amount of manganese dioxide solids generated.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

A New Reduced Order Model For The Mechanistic Creep Behavior Of UO 2

This manuscript describes an ongoing NEAMS effort to better determine the performance of advanced nuclear fuels, in particular the creep behavior of doped UO$_2$ for light water reactors. In our previous work, we outlined a method to utilize data generated from lower length scale simulations and implement it into the engineering scale fuel performance analysis. This process has been further refined, and in addition, new data has been used to train the surrogate model which has also been substantially improved since the previous iteration. The new model is compared against the current empirical model used in BISON using both scoping calculations to define the performance over the parameter space and using integral instrumented fuel assessment cases to determine the impact of these models on the overall fuel performance. Suggestions and guidance for future improvements to this method are provided to ensure the model covers relevant parameter space and phenomena.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

RANGERS: Modeling Report on Integrity and Performance Assessment of Engineered Barrier Systems in a Salt Repository for HLW/SNF

The Engineered Barrier System (EBS) plays an important role in ensuring the long-term safety and containment of high-level waste (HLW) and spent nuclear fuel (SNF) in deep geological repositories in salt formation. As part of a multi-barrier system, the EBS works alongside the natural barrier, which is the salt formation itself and the technical barrier comprising the disposal casks. The primary function of the EBS is to maintain containment during a defined period until the backfill used in the repository made of crushed salt, develops its sealing capacity through compaction. Over the time, the backfill eventually compacts to a state of low porosity and permeability, acting as a long-term seal. However, until this process is complete, the EBS must retain its structural and functional integrity. Regulatory guidelines in Germany currently require the EBS to remain effective for up to next ice age, that is expected in 50,000 years. The significant hydro-geological and topographic changes expected during an ice age could make it impossible to accurately predict the hydro-chemical conditions within the repository system at that time. In response to these challenges, BGE TECHNOLOGY GmbH (BGE TEC) and Sandia National Laboratories (SNL) have jointly developed a comprehensive methodology for the design and safety assessment of engineered barrier systems within the scope of the RANGERS project. This methodology is tailored for repositories in salt formations. The developed methodology provides a structured approach for designing and assessing the performance of the EBS in salt-based repositories. It begins with defining a sealing concept based on the geological characteristics of the selected site and the overall repository design. The entire repository system, comprising the geological site, repository infrastructure, and EBS, is then subjected to a Features, Events, and Processes (FEP) analysis, focusing solely on those FEPs that affect the EBS. The derived FEPs help identify the loads and stresses acting on the EBS, which serve as the foundation for conducting an integrity assessment. This analysis helps predict the EBS’s evolution and performance over the regulatory time frame, feeding into integrated performance assessment simulations.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2025

Flux Upcycling of Degraded Layered Cathodes to LiNi x Mn y Co z O 2 (NMCs) with Gradient Transition Metal Distribution

The rising demand for lithium-ion batteries (LIBs) has intensified the need for efficient recycling methods to address both supply chain constraints and environmental impacts. Direct upcycling, distinguished by its ability to achieve both the structural and compositional integrity of cathode materials, has gained prominence as a sustainable alternative to conventional pyrometallurgical and hydrometallurgical processes. However, the current direct upcycling methods are typically limited by incorporating Li and/or Ni, significantly constraining the adaptability across diverse LiNi x Mn y Co z O 2 (NMCs). Here, in this study, a versatile molten salt approach is reported that expands the scope of direct upcycling by enabling simultaneous incorporation of Li, Ni, and Mn. This methodology facilitates flexible conversion among diverse NMC compositions, including non-stoichiometric Co/Mn systems such as upcycling degraded LiCoO 2 (D-LCO), LiNi 1/3 Mn 1/3 Co 1/3 O 2 (D-NMC111), LiNi 0.8 Mn 0.1 Co 0.1 O 2 (D-NMC811) to surface Mn enriched NMC111, LiNi 0.5 Mn 0.3 Co 0.2 O 2 (NMC532), and NMC811, respectively. The gradient transition metal distribution in upcycled products, characterized by Mn-enriched outer layers and Co/Ni-enriched cores enhances the interfacial stability of NMC cathodes, addressing critical challenges in long-term performance and structural integrity. These results highlight the potential of flux methods for advancing the upcycling of spent cathodes and producing high-performance materials for next-generation LIBs applications.

lithium -ion batteries↗

DOE OSTI2025

Sitka Energy Inventory

The City and Borough of Sitka was chosen for an Energy Technology Innovation Partner Project award starting in Fall 2023, the third cohort of the program. The scope of the following work was driven by the city, as well as the city-appointed Sustainability Commission. The community asked for a method to track their reliance on outside fuel sources, as well as the emissions associated with those fuels and other processes in Sitka. The Pacific Northwest National Laboratory (PNNL) provided research and methodology in line with this community driven ask. This project is a community wide inventory, requiring methods to estimate the fuel usage and emissions from various industries. For each estimate, PNNL presents methodologies that can be repeated by the community in future years to understand how the city is changing.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2025

A generalizable machine learning-assisted fast Fourier transform algorithm to simulate the large strain phenomena in polycrystalline materials

Machine learning methods have shown initial promise in constitutive modeling for single crystals or homogenized polycrystals, delivering notable computational efficiency. However, existing machine learning-based constitutive models often lack generalizability, limiting their application across diverse boundary value problems. This study introduces a thermodynamics-informed artificial neural network model to accelerate rate-tangent crystal plasticity fast Fourier transform simulations for cross-scale deformation behaviors of polycrystals under complex loading. Our model integrates microstructural variability and local interactions effectively. To address local effects in each grain, we employ K-means clustering to group Gauss points within the microstructure into clusters assumed to be in similar mechanical states. This approach, based on self-clustering analysis, extends model scope from macroscopic stress response to the granular level, capturing mechanical responses and orientation evolution across grains. This reduces the number of nonlinear problems to solve, with cluster responses propagated throughout each group. The thermodynamics-based artificial neural network-extracted features are further processed using local material state clusters to account for history-dependent deformation and evolving microstructures. Additionally, representative volume element simulations with rate-tangent crystal plasticity fast Fourier transform provide reliable datasets for model training. The proposed model demonstrates high efficiency, accuracy, self-consistency, and enhanced generalizability in predicting strain–stress responses and orientation evolution at both individual grain and aggregate scales under complex loading conditions, such as biaxial tension and arbitrary loading scenarios.

36 MATERIALS SCIENCE↗