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DOE OSTI2022

Scaling Building Energy Audits through Machine Learning Methods on Novel Drone Image Data

Building energy audits are time-consuming and labor-intensive. This paper describes a new method using machine learning (ML) techniques on novel data sources (drone images) to improve the identification of building characteristics and retrofit opportunities, and thereby reduce the effort for audits. The new ML method includes: (1) Building footprint extraction using line extraction, polygonization, and polygon-merging, (2) Building envelope extraction using PIX4d modeling software to reconstruct a building 3D model, (3) Visualization tool for viewing images from the 3D model, (4) Window-to-wall ratio (WWR) using state-of-art deep neural network semantic segmentation, (5) Envelope thermal anomaly detection using an unsupervised machine learning clustering algorithm, and (6) Rooftop energy equipment detection based on an object detection algorithm. The testing of this method involved a comparison of additional ML-generated information overlaid on current ‘state-of-practice’ audit and remote assessment baselines using evaluation metrics: labor time and associated cost, marginal benefits of using ML-generated information in workflows for audits and remote assessments, integration potential with existing processes and tools, and replicability/scalability of the method. In two test buildings in California that had comprehensive drawings and meter data available, the ML method effectively generated a building footprint, envelope, rooftop equipment, WWR, and locations of envelope thermal anomalies. Projected target segments of the ML method are sites with minimal drawings and energy data, and underserved sectors such as multistoried housing, disadvantaged communities, and schools for which the ML method can enable identification of building asset characteristics and prioritization of envelope retrofits and decentralized energy equipment retrofits.

Singh, Reshma↗

DOE OSTI2024

Mortar-based Cohesive Zone Model with Application to TRISO Particle Debonding

The U.S. Department of Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program aims to develop predictive capabilities by applying computational methods to the analysis and design of advanced reactor and fuel cycle systems. This program has been providing engineering-scale support for the development of BISON, a high-fidelity and high-resolution fuel performance tool. This report outlines work towards the development of an integrated, mortar-based cohesive zone framework with mechanical contact. We model debonding of tri-structural isotropic (TRISO) layers using a mortar approach, extending the framework used for mechanical contact, using weighted quantities. A bilinear mixed mode traction approach, already used in Jiang et al. (2021), is applied analogously herein to model debonding between TRISO particle layers. The examples include the debonding of the inner pyrolytic carbon (IPyC) from the silicon carbide (SiC) layers, as well as partial and full debonding of the buffer from the IPyC layers. Both 2D and 3D examples are utilized to demonstrate the superior numerical performance of the new mortar approach, which allows for modeling arbitrarily meshed interfaces (i.e., non-matching discretizations).

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Thermo-mechanical deterioration and molecular degradation of 3D-printed methacrylate-based polymer in various chemical environments

The advancement of additive manufacturing (AM) has accelerated the development of stereolithographic (SLA) photo-curable resins, particularly methacrylate-based polymers, due to the ability to their high-resolution, robust mechanical properties, and suitability. However, their long-term performance in chemical environments remains poorly understood. This study investigates the extent and mechanisms of degradation on an SLA-printed methacrylate-based polymer subjected to various chemicals, including polar and non-polar solvents, as well as strongly acidic aqueous solutions over a 12-week accelerated aging period. A comprehensive analytical approach incorporating swelling kinetics, surface morphology, tensile and dynamic mechanical analysis (DMA), Fourier-transform infrared (FTIR) spectroscopy, and mass spectrometry (MS) was employed to characterize chemical absorption, structural integrity, and leached products. Results reveal that degradation severity is governed by both the polarity and reactivity of the chemical environment. Notably, exposure to 6 mol L -1 HNO₃ induced the most severe deterioration, with over threefold higher swelling compared to other media, and significant reductions in tensile strength, tensile modulus, and glass transition temperature (T g ). In contrast, specimens aged in non-polar solvents (xylene and dodecane) exhibited negligible chemical interaction and retained mechanical performance. FTIR and MS analyses identified acid-catalyzed hydrolysis of ester groups as prominent degradation pathways in acidic media, while diffusion-controlled plasticization prevailed in polar solvents. Furthermore, this study provides valuable insights into the chemical stability of SLA-printed polymers and develops predictive degradation profiles that are crucial for designing durable polymer systems for advanced industrial use.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Magnetic field driven emergent phenomena: Insights from magneto-optics and nanoscopy

This review explores magnetic field-driven emergent phenomena across various material systems, emphasizing the pivotal roles of magneto-optical and nanoscopy techniques. We examine fundamental aspects of Landau electrodynamics in both 2D and 3D systems, including quantum Hall and topological magnetoelectric effects in graphene and topological insulators. Particularly attention is given to magnetic excitations and magnetopolaritons, such as surface magnon polaritons, magnetoplasmons, and magnetoexcitons in novel quantum materials, including quantum magnets and hybrid heterostructures. Advanced imaging techniques, such as scattering-type scanning near-field optical microscopy (SNOM) and microwave impedance microscopy, are showcased for their capability to resolve these phenomena with microscopic and nanoscopic resolution. These insights are complemented by discussions of advanced experimental approaches, including cryogenic environments, ultrafast pump-probe techniques, and the integration of magnetic fields into near-field optical methodologies. We further investigate the potential of these imaging techniques for unraveling complex magnetic orders, quantum phases, and correlated electronic behaviors. Finally, we offer perspectives on future research directions and highlight emerging opportunities in the evolving field of optical magneto-nanoscopy.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Challenges for density functional theory in simulating metal–metal singlet bonding: A case study of dimerized VO2

VO2 is renowned for its electric transition from an insulating monoclinic (M1) phase, characterized by V–V dimerized structures, to a metallic rutile (R) phase above 340 K. This transition is accompanied by a magnetic change: the M1 phase exhibits a non-magnetic spin-singlet state, while the R phase exhibits a state with local magnetic moments. Simultaneous simulation of the structural, electric, and magnetic properties of this compound is of fundamental importance, but the M1 phase alone has posed a significant challenge to the density functional theory (DFT). In this study, we show none of the commonly used DFT functionals, including those combined with on-site Hubbard U to treat 3d electrons better, can accurately predict the V–V dimer length. The spin-restricted method tends to overestimate the strength of the V–V bonds, resulting in a small V–V bond length. Conversely, the spin-symmetry-breaking method exhibits the opposite trends. Each of these two bond-calculation methods underscores one of the two contentious mechanisms, i.e., Peierls lattice distortion or Mott localization due to electron–electron repulsion, involved in the metal–insulator transition in VO2. To elucidate the challenges encountered in DFT, we also employ an effective Hamiltonian that integrates one-dimensional magnetic sites, thereby revealing the inherent difficulties linked with the DFT computations.

Chemistry↗

DOE OSTI2024

Prediction of transport in the JET DTE2 discharges with TGLF and NEO models using the TGYRO transport code

Abstract The JET Deuterium-Tritium-Experiment Campaign 2 (DTE2) has demonstrated the highest-ever fusion energy production. To forecast the transport dynamics within these discharges, the TGLF and NEO models within the TGYRO transport code were employed. A critical development in this study is the new quasilinear transport model, TGLF-SAT2, specifically designed to resolve discrepancies identified in JET deuterium discharges. This model accurately describes the saturated three-dimensional (3D) fluctuation spectrum, aligning closely with a database of nonlinear CGYRO turbulence simulations, thereby enhancing the predictive accuracy of TGYRO simulations. In validating against the JET DTE2 discharges across two primary operating scenarios, TGYRO effectively predicted the temperature profiles within a broad radial window ( ρ ∼ 0.2–0.85), though with minor ion temperature discrepancies near the core. However, a consistent underprediction of electron density profiles by 20% across the simulation domain was noted, indicating areas for future refinement. To achieve a self-consistent steady-state solution based on the JET DTE2 discharges, an integrated modeling workflow TGYRO-STEP within the OMFIT framework was introduced. This workflow iterates among the core transport, the pedestal pressure and the MHD equilibrium, ultimately yielding a converged solution that significantly reduces dependence on experimental boundary conditions for temperature and density profiles. The integrated simulation results show negligible differences in electron density and temperature profiles compared to standalone TGYRO modeling, while the ion temperature profile is lower due to the updated boundary condition in TGYRO-STEP. The application of the TGYRO-STEP workflow to JET DTE2 discharges serves as a crucial test to validate its robustness and highlights its limitations, providing valuable insights for its potential future application in ITER and Fusion Power Plant deuterium and tritium prediction modeling.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Southwest Regional Partnership on Carbon Sequestration: Phase III (Final Scientific/Technical Report)

The Southwest Regional Partnership on Carbon Sequestration (SWP) is one of 7 regional partnerships formed in 2003 under the U.S. Department of Energy’s (DOE) Regional Carbon Sequestration Partnerships (RCSPs) initiative. The overall purpose of the initiative was to help determine and implement the technology, infrastructure, and regulations most appropriate to promote carbon storage in different regions of the country. Covering Arizona, Colorado, New Mexico, Oklahoma, Utah, and parts of Texas, Wyoming, and Kansas, the SWP evaluated regional carbon storage and utilization potential and focused on technologies and sites that could complement the region’s strong position in energy production. The project progressed through three phases: • Phase I (2003–2005): Characterized regional geologic formations and CO 2 sources, assessed sequestration potential, and identified pilot test sites. • Phase II (2005–2013): Conducted small-scale field tests to validate sequestration methods, including geologic and terrestrial projects. • Phase III (2008–2022): Demonstrated large-scale CO 2 injection at a commercial oil field to test monitoring, verification, and long-term storage strategies. This report covers Phase III. The final project site, the Farnsworth Unit (FWU) in Texas, provided real-world testing of reservoir characterization, monitoring, and risk evaluation tools and processes that could be used in any commercial scale carbon capture, utilization, and storage (CCUS) project. Extensive data collection and analysis helped refine best practices for reservoir characterization, injection monitoring, and storage verification. The SWP contributed to national databases, DOE best practice manuals, and regional geological assessments to support future sequestration efforts. Key lessons learned include the importance of robust data management, strategic site selection, regulatory navigation, and effective industry collaboration. The project’s findings will inform ongoing and future carbon storage initiatives. Task 1 (Regional Characterization) • The SWP continued to participate in national outreach efforts and NATCARB. • The SWP evaluated multiple potential sites before selecting the FWU as the primary field test location. Task 2 (Public Outreach and Education) • The SWP contributed to national databases, DOE best practice manuals, and regional geological assessments to support future sequestration efforts. Task 3 (Permitting and Regulatory Compliance) • The SWP ensured compliance with federal and state regulations, including National Environmental Policy Act (NEPA) requirements. • The SWP obtained all necessary permits for drilling, injection, and monitoring activities. Task 4 (Site Characterization and Planning) • The SWP developed work plans for four key activities: characterization, simulation, monitoring and verification, and risk evaluation. • The SWP collected and synthesized legacy data from multiple sources to build initial static geological models and dynamic reservoir models demonstrating project feasibility. • The SWP conducted an initial risk evaluation and developed mitigation plans. Task 5 (Field Operations and Data Collection) • The SWP drilled, logged, and cored three characterization wells to gather critical subsurface data. • The SWP conducted multiple geophysical surveys, including 3D seismic, crosswell seismic, and vertical seismic profiling, to improve reservoir characterization. Task 6 (Monitoring and Verification) • The SWP performed extensive geological characterization using data from characterization wells and seismic surveys. • The SWP established a surface monitoring network to track CO 2 flux in soil gas, groundwater chemistry, and near-surface atmospheric CO 2 levels. • The SWP built and refined reservoir models to study the effects of relative permeability on simulation behavior and improve calibration with experimental data. Task 7 (Risk Assessment and Model Refinement) • The SWP conducted multiple studies to evaluate reservoir integrity, predict CO 2 plume behavior and improve predictive modeling capabilities. • The SWP refined geological models and used them to enhance the accuracy of simulation models. • The SWP continued quantitative risk assessment of top-ranked risks and strengthened the link between qualitative and quantitative risk methodologies.

02 PETROLEUM↗

DOE OSTI2021

Light Regulation of Phytoplankton Growth in San Francisco Bay Studied Using a 3D Sediment Transport Model

In San Francisco Bay (SFB), light availability is largely determined by the concentration of suspended particulate matter (SPM) in the water column. SPM exhibits substantial variation with time, depth, and location. To study how SPM influences light and phytoplankton growth, we coupled a sediment transport model with a hydrodynamic model and a biogeochemical model. The coupled models were used to simulate conditions for the year of 2011 with a focus on northern SFB. For comparison, two simulations were conducted with ecosystem processes driven by SPM concentrations supplied by the sediment transport model and by applying a constant SPM concentration of 20 mg l –1 . The sediment transport model successfully reproduced the general pattern of SPM variation in northern SFB, which improved the chlorophyll-a simulation resulting from the biogeochemical model, with vertically integrated primary productivity varying greatly, from 40 g[C] m –2 year –1 over shoals to 160 g[C] m –2 year –1 in the deep channel. Primary productivity in northern SFB is influenced by euphotic zone depth ( Ze ). Our results show that Ze in shallow water regions (<2 m) is mainly determined by water depth, while Ze in deep water regions is controlled by SPM concentration. As a result, Ze has low (high) values in shallow (deep) water regions. Large (small) differences in primary productivity exist between the two simulations in deep (shallow) water regions. Furthermore, we defined a new parameter F light for “averaged light limitation” in the euphotic zone. The averaged chlorophyll-a concentration in the euphotic zone and F light share a similar distribution such that both have high (low) values in shallow (deep) water regions. Our study demonstrates that light is a critical factor in regulating the phytoplankton growth in northern SFB, and a sediment transport model improves simulation of light availability in the water column.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Joint ptycho-tomography with deep generative priors

Abstract Joint ptycho-tomography is a powerful computational imaging framework to recover the refractive properties of a 3D object while relaxing the requirements for probe overlap that is common in conventional phase retrieval. We use an augmented Lagrangian scheme for formulating the constrained optimization problem and employ an alternating direction method of multipliers (ADMM) for the joint solution. ADMM allows the problem to be split into smaller and computationally more efficient subproblems: ptychographic phase retrieval, tomographic reconstruction, and regularization of the solution. We extend our ADMM framework with plug-and-play (PnP) denoisers by replacing the regularization subproblem with a general denoising operator based on machine learning. While the PnP framework enables integrating such learned priors as denoising operators, tuning of the denoiser prior remains challenging. To overcome this challenge, we propose a denoiser parameter to control the effect of the denoiser and to accelerate the solution. In our simulations, we demonstrate that our proposed framework with parameter tuning and learned priors generates high-quality reconstructions under limited and noisy measurement data.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Implementation of Smart Materials for Actuation of Traditional Valve Technology for Hybrid Energy Systems

The ever-changing nature of the power industry will require the implementation of hybrid energy systems. Integration of tightly coupled components in hybrids often involves the diversion of exhaust gas flow. An innovative smart material actuation technology is proposed to replace traditional electro-mechanical actuated valve mechanisms with lighter and less expensive actuators. A shape memory alloy (SMA) spring-actuated valve was designed for high-temperature service to demonstrate the promise of smart materials in control valve applications. With SMA springs only generating a maximum force of 3.2 N, an innovative valve design was necessary. To demonstrate the concept, a 3-inch Nominal Pipe Size valve was designed, and 3D printed using the stereolithography technique. Increasing the electrical current to actuate the SMA springs reduced actuation time. The maximum current of 10 A produced the lowest actuation time of 2.85 s, with an observed maximum stroke rate of more than 100 stroke completion %/s (considering actuation open/close as 100% stroke) at the midrange. The final assembly of the valve was estimated to provide a cost reduction of more than 30% and a weight reduction of more than 80% compared to the other available automatic valves in the present market.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Improved Measurements of Galaxy Star Formation Stochasticity from the Intrinsic Scatter of Burst Indicators

Abstract Measurements of short-timescale star formation variations (i.e., “burstiness” or star formation stochasticity) are integral to our understanding of star formation feedback mechanisms and the assembly of stellar populations in galaxies. We expand upon the work of Broussard et al. by introducing a new analysis of galaxy star formation burstiness that accounts for variations in the Q sg = E B − V stars / E B − V gas distribution, a major confounding factor. We use Balmer decrements from the MOSFIRE Deep Evolution Field (MOSDEF) survey to measure Q sg , which we use to construct mock catalogs from the Santa Cruz Semi-Analytic Models and Mufasa cosmological hydrodynamical simulation based on 3D-HST, Fiber Multi-Object Spectrograph (FMOS)-COSMOS, and MOSDEF galaxies with H α detections. The results of the mock catalogs are compared against observations using the burst indicator η = log 10 ( SFR H α / SFR NUV ) , with the standard deviation of the η distribution indicating burstiness. We find decent agreement between mock and observed η distribution shapes; however, the FMOS-COSMOS and MOSDEF mocks show a systematically low median and scatter in η in comparison to the observations. This work also presents the novel approach of analytically deriving the relationship between the intrinsic scatter in η , scatter added by measurement uncertainties, and observed scatter, resulting in an intrinsic burstiness measurement of 0.06–0.16 dex.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Wyoming CarbonSAFE: Advancing Commercialization of Low-Carbon Energy Technologies in Fossil-Rich Wyoming

Wyoming’s Powder River Basin (PRB) is the most prolific coal producer and exporter in the United States and the State of Wyoming’s largest oil-producing basin. In addition to being a leading energy producer, the PRB is the site of research programs whose aim is to develop and integrate low-carbon technologies into existing fossil fuel energy industries. Much of the PRB’s low-carbon research is focused around Dry Fork Station (DFS), which is the newest coal-fired power station in the western US. Currently, DFS hosts five carbon capture projects, including pilot-scale capture projects that utilize different capture technologies and a full front-end engineering and design (FEED) study, a commercial CO 2 pipeline for nearby CO 2 -enhanced oil recovery industry, and is also co-located with the Wyoming Integrated Test Center, which is a host facility for unconventional carbon utilization research (i.e. flue gas carbon-to-products innovations). DFS is also the host site for the Wyoming CarbonSAFE project. Wyoming CarbonSAFE, funded by the Department of Energy/National Energy Technology Laboratory, is a multi-phased program (currently in Phase II) whose core objective is developing and validating storage sites within a complex capable of storing 50 million metric tonnes of CO 2 over a 30 year project period using carbon capture, utilization and storage (CCUS). This paper will provide an overview of the project to-date, showing that CarbonSAFE goals are achievable with respect to geologic, environmental, regulatory, CO 2 source and economic conditions, and why the State of Wyoming offers one of the more favorable environments to advance the commercialization studies. In 2019, the project team designed and completed a ~10,000 foot stratigraphic test well just south of DFS. From this well, the team collected over 600 feet of core, fluid samples from target injection zones, and a full petrophysical log suite. In addition, legacy 2D seismic lines were acquired and a 3D seismic survey was acquired in the fall of 2020. The objective of these field activities has been to identify and characterize target storage reservoirs and associated caprock. This complex has several reservoirs that could meet commercial injection goals, and over 4000 feet of associated caprock. Simulations of site performance suggest that stacked injection provides the most effective storage strategy, and would necessitate several sites within the greater complex to meet final project injection goals. Other work within this project includes the development of a business-case around proximal fields with CO 2 -enhanced oil recovery potential and existing tax credits, assessment of regulatory conditions, including pore space ownership and Class VI injection well permitting requirements, implementation of a robust public outreach Electronic copy available at: https://ssrn.com/abstract=3821220 GHGT-15 McLaughlin 2 program, and surface site characterization activities that have focused on environmental factors. In the PRB and at DFS, the State of Wyoming and other entities have made carbon management a priority of its future energy industry by providing a regulatory and business framework that is favorable to advancing these technologies. These endeavors will become more realistic with the successful implementation of Wyoming CarbonSAFE, and its ability to secure and validate commercial-scale CCUS at the center of Wyoming’s premier low-carbon research efforts.

McLaughlin, Fred↗

DOE OSTI2026

Local Pair Natural Orbital-Based Coupled-Cluster Theory through Full Quadruples (DLPNO–CCSDTQ)

In this work, we implement a local pair natural orbitalbased coupled-cluster method through the full treatment of quadruple excitations (CCSDTQ). The domain-based local pair natural orbital (DLPNO) approach, which has successfully been applied to lower levels of coupled-cluster theory, is utilized in our algorithm, and thus our algorithm is called DLPNO-CCSDTQ. For simplicity in the working equations and in the implementation, we t 1 -dress the twoelectron integrals as well as Fock matrix elements. Our method can recover CCSDTQ-CCSDT and CCSDTQ-CCSDT(Q) energy differences on the order of 0.01−0.05 kcal mol −1 , even at a loose quadruples natural orbital (QNO) occupation number cutoff of 3.33 × 10 −6 . To highlight the capabilities of our code and its potential future applications, we showcase computations that would be intractable with canonical CCSDTQ, such as the benzene dimer, (H 2 O) 17 , and adamantane. With sufficient computing resources, computations up to 15 heavy atoms (40 atoms overall) may be feasible for fully bonded 3D systems.

Cluster chemistry↗

DOE OSTI2026

Numerical Modeling & Optimization of the iProTech Pitching Inertial Pump (PIP) Wave Energy Converter (WEC) (CRADA Final Report)

This project represents a continuation of the collaboration between iProTech and NLR to simulate, optimize and design the iProTech Pitching Inertial Pump (PIP) device. The objectives of this TEAMER project are twofold: 1. Refining the physical characteristics of the existing iProTech PIP WEC-Sim model to enhance the model’s fidelity and include controllable components. Key model enhancements target the inclusion of Coulomb friction, the introduction of a controllable bypass valve, and the replacement of traditional check valves with advanced motorized ones. 2. Exploring traditional and advanced control algorithms. From traditional methods like latching control to cutting-edge reinforcement learning (RL) algorithms, the goal is to ensure the PIP device's adaptability and optimal performance across a range of ocean conditions. NLR is tasked with augmenting the WEC-Sim model and implementing the control algorithms, culminating in performance comparison analyses. iProTech will update their existing 3D models, advise on model improvements, and determine crucial system metrics. WEC-Sim, developed in MATLAB/SIMULINK with Simscape Multibody, is the main piece of software that will be used in this project. Coupled with the MATLAB RL Toolbox, it offers a robust platform for in-depth simulation and optimization of the iProTech PIP device. Building on previous work to explore the PIP design space and optimize its geometry, mass distribution, center of gravity and other key parameters, this project aims to refine iProTech’s existing numerical models and develop effective control algorithms that can seamlessly integrate into their future hardware testing campaigns.

16 TIDAL AND WAVE POWER↗

DOE OSTI2021

Diii-D Research Advancing The Physics Basis For Optimizing The Tokamak Approach To Fusion Energy

DIII-D physics research addresses critical challenges for operation of ITER and the next generation of fusion energy devices. This is done through a focus on innovations to provide solutions for high performance long pulse operation, coupled with fundamental plasma physics understanding and model validation, to drive scenario development by integrating high performance core and boundary plasmas. Substantial increases in off-axis current drive efficiency from an innovative top launch system for EC power, and in pressure broadening for Alfven eigenmode control from a co-/counter-Ip steerable off-axis neutral beam, all improve the prospects for optimization of future long pulse/steady state high performance tokamak operation. Fundamental studies into the modes that drive the evolution of the pedestal pressure profile and electron vs. ion heat flux validate predictive models of pedestal recovery after ELMs. Understanding the physics mechanisms of ELM control and density pumpout by 3D magnetic perturbation fields leads to confident predictions for ITER and future devices. Validated modeling of high-Z shattered pellet injection for disruption mitigation, runaway electron dissipation, and techniques for disruption prediction and avoidance including machine learning, give confidence in handling disruptivity for future devices. With this physics understanding and suite of actuators, a high poloidal beta optimized-core scenario with an internal transport barrier that projects nearly to Q=10 in ITER at 9 MA was coupled to a detached divertor, and a near Super H-mode optimized-pedestal scenario with co-Ip beam injection, was coupled to a radiative divertor. The Hybrid core scenario was achieved directly, without the need for internal flux pumping, using off-axis current drive actuators, and a controller to avoid mode locking and disruptions in the ITER baseline scenario, based on plasma response to probing 3D fields, was demonstrated. Finally innovative tokamak operation using a negative triangularity shape showed many attractive features for future pilot plant operation.

Fenstermacher, M.↗

DOE OSTI2025

Zwitterionic Photocurable Resin for High‐Resolution 3D Printing of Ultralow‐Fouling Microstructures

High‐resolution 3D printing technologies are enabling a new generation of microstructured materials for applications where biocompatibility is critical. However, most conventional 3D‐printable resins yield materials that exhibit trade‐offs between antifouling properties and mechanical robustness, limiting their applicability in living systems. In nature, zwitterionic surface groups form tightly bound hydration layers that act as effective barriers against protein and cell attachment. Inspired by this strategy, a zwitterionic acrylamide‐based photoresist—carboxybetaine di‐methacrylamide (CBDA)—is developed for projection‐based vat photopolymerization, enabling the fabrication of complex microarchitectures with exceptional antifouling properties. The bifunctional monomer allows the formation of dense, cross‐linked networks that resist swelling while maintaining a high density of zwitterionic groups. Printed structures exhibit strong resistance to protein and cell adhesion, as confirmed by porcine blood assays, alongside robust mechanical performance. As a demonstration, a tubular structure featuring a negative Poisson's ratio lattice is printed to showcase structural fidelity and versatility. This resin formulation offers a broadly applicable strategy for fabricating microscale devices and surfaces where antifouling performance and structural integrity are both essential—spanning biomedical interfaces, soft robotics, and beyond.

3D printing↗

DOE OSTI2025

Predicting metal-binding proteins and structures through integration of evolutionary-scale and physics-based modeling

Metals are essential elements in all living organisms, binding to approximately 50% of proteins. They serve to stabilize proteins, catalyze reactions, regulate activities, and fulfill various physiological and pathological functions. While there have been many advancements in determining the structures of protein-metal complexes, numerous metal-binding proteins still need to be identified through computational methods and validated through experiments. Here, to address this need, we have developed the ESMBind workflow, which combines evolutionary scale modeling (ESM) for metal-binding prediction and physics-based protein-metal modeling. Our approach utilizes the ESM-2 and ESM-IF models to predict metal-binding probability at the residue level. In addition, we have designed a metal-placement method and energy minimization technique to generate detailed 3D structures of protein-metal complexes. Our workflow outperforms other models in terms of residue and 3D-level predictions. To demonstrate its effectiveness, we applied the workflow to 142 uncharacterized fungal pathogen proteins and predicted metal-binding proteins involved in fungal infection and virulence.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Plasma–surface interaction in the stellarator W7-X: conclusions drawn from operation with graphite plasma-facing components

W7-X completed its plasma operation in hydrogen with island divertor and inertially cooled test divertor unit (TDU) made of graphite. A substantial set of plasma-facing components (PFCs), including in particular marker target elements, were extracted from the W7-X vessel and analysed post-mortem. The analysis provided key information about underlying plasma–surface interactions (PSI) processes, namely erosion, transport, and deposition as well as fuel retention in the graphite components. The net carbon (C) erosion and deposition distribution on the horizontal target (HT) and vertical target (VT) plates were quantified and related to the plasma time in standard divertor configuration with edge transform ι = 5/5, the dominant magnetic configuration of the two operational phases (OP) with TDU. The operation resulted in integrated high net C erosion rate of 2.8 mg s -1 in OP1.2B over 4809 plasma seconds. Boronisations reduced the net erosion on the HT by about a factor 5.4 with respect to OP1.2A owing to the suppression of oxygen (O). In the case of the VT, high peak net C erosion of 11μm at the strike line was measured during OP1.2B which converts to 2.5 nm s -1 or 1.4 mg s -1 when related to the exposed area of the target plate and the operational time in standard divertor configuration. PSI modelling with ERO2.0 and WallDYN-3D is applied in an interpretative manner and reproduces the net C erosion and deposition pattern at the target plates determined by different post-mortem analysis techniques. This includes also the 13 C tracer deposition from the last experiment of OP1.2B with local 13 CH 4 injection through a magnetic island in one half module. The experimental findings are used to predict the C erosion, transport, and deposition in the next campaigns aiming in long-pulse operation up to 1800 s and utilising the actively cooled carbon-fibre composite (CFC) divertor currently being installed. The CFC divertor has the same geometrical design as the TDU and extrapolation depends mainly on the applied plasma boundary. Extrapolation from campaign averaged information obtained in OP1.2B reveals a net erosion of 7.6 g per 1800 s for a typical W7-X attached divertor plasma in hydrogen.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗