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DOE OSTI2022

Restructuring and integrity of molecular catalysts in electrochemical CO 2 reduction

Electrocatalysts that start a reaction as molecules do not always end the reaction as molecules, and even when they do, they might not be molecules during catalysis. In this Perspective, we discuss knowledge learned from the study of Cu-based molecularly structured electrocatalysts––including metal coordination complexes, metal-organic frameworks, single-atom catalysts, and polymeric materials––that restructure under electrochemical CO 2 reduction reactions. Recent reports are summarized with an emphasis on the nature and significance of post-mortem and in situ characterization for the proper identification of active sites. We demonstrate that molecular and material structures determine whether electrocatalysts restructure and how they restructure, that understanding of restructuring processes can help us identify active sites for catalysis, and that this knowledge can be leveraged to design precatalysts that generate highly active catalysts under reaction conditions. In addition, we provide recommended practices for studying the integrity of heterogeneous molecular catalysts during and after CO 2 reduction reactions.

CO2 reduction↗

DOE OSTI2021

Initial framework for engineering-scale statistical creep-fatigue modeling

This report describes the integration of new solid and interface-cohesive mechanics systems into MOOSE. The purpose of these new systems is to support the ability of MOOSE to run full-field crystal plasticity finite element method simulations of key material processes in high temperature metallic materials. These simulations could be used to help accurately predict the performance of key high temperature structural materials in future advanced nuclear reactor components. Previous work implemented preliminary versions of many of these systems in MOOSE Apps. The current work reports on their integration into the main MOOSE tensor mechanics module along with associated improvements to the basic formulations and numerical implementations. Finally, the report provides an example of the full-field crystal plasticity simulations now possible in MOOSE, including examples of realistic geometries requiring millions of degrees of freedom to resolve the microstructural features and macroscale geometry.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2026

Triggerable adhesives with infinite working life for large area application

Oak Ridge National Laboratory (ORNL) Manufacturing Demonstration Facility (MDF) entered a User Proposal with Perseus Materials in Knoxville, TN. By reinventing how composites are made, we unlock a new era of structural materials: faster to produce, easier to assemble, and strong enough for real-world scale. Perseus Materials was targeting the wind turbine industry to make large adhesive joints for composite turbine blades without the limitations of cure time and room temperature cure without the needs to have work times. The triggerable aspect would increase manufacturing rates for composite wind turbine blades.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Adhesion in thermomechanically processed seaweed-lignocellulosic composite materials

The increasing concerns associated with petroleum-derived polymers motivate the development of sustainable, renewably sourced alternatives. In ubiquitous applications such as structural materials for infrastructure, the built environment as well as packaging, where natural materials such as wood are used, we rely on nonrenewable and nondegradable polymers to serve as adhesives. In wood panels, such as medium density fiberboards (MDFs), formaldehyde-based resins are predominantly used to bond wood fibers and to provide strength to the materials. To further mitigate the environmental impact of construction materials, more sustainable adhesives need to be investigated. Here, in this article, we introduce Ulva seaweed as an adhesive to enable cohesion and strength in hot-pressed wood panels. Upon hot-pressing, powdered Ulva flows in between the wood particles, generating a matrix, which provides strong binding. We show that the flexural strength of Ulva-bonded wood biocomposites increases with increasing Ulva concentrations. At an Ulva concentration of 40 wt%, our composites reach an average elastic modulus of 6.1 GPa, and flexural strength of 38.2 MPa (compared to 4.7 GPa and 22.6 MPa, respectively, for pure wood compressed at the same pressing conditions). To highlight the bonding mechanisms, we performed infrared and x-ray photoelectron spectroscopy and identified indications of fatty acid mobility during hot-pressing. In addition, we demonstrate that the presence of Ulva improves other properties of the composites such as water resistance and fame retardancy. Ulva is also shown to behave as an excellent adhesive agent between two prepressed beams. Finally, we perform an in-depth analysis of the environmental impact of wood-Ulva biocomposites.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Material Characterization of Grade 91 Steel Welds using, Micro-resolution Ultrasonic Imaging System

Grade 91 (9Cr-1Mo-V) steel is a common structural material for fossil-fuel fired and nuclear power plants because of its creep strength and oxidation resistance at high temperatures. In this research, we studied the feasibility of correlating the high-resolution images obtained from the immersion ultrasonic imaging technique to microstructure regions in Grade 91 steel plate weldments. The high-resolution ultrasonic images presented in this paper were generated using a 20-MHz focused transducer as the transmitter, and a laser vibrometer as the receiver in the through transmission configuration to produce longitudinal and shear waves. This nondestructive evaluation (NDE) method was used to identify the Fusion Zone (FZ), Heat-Affected Zone (HAZ), and Base Metal (BM) regions of Grade 91 cold metal transfer (CMT) and flux core arc welds (FCAW). The ultrasonic imaging results were analyzed using beam propagation amplitudes and homogeneity, which in turn were used to relate the different microstructure regions of the FCAW and CMT welded samples. With this study, we were able to identify highly susceptible microstructures in the weld that could potentially promote creep type failures.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2022

Recent Advances and Prospects in Design of Hydrogen Permeation Barrier Materials for Energy Applications—A Review

The hydrogen infrastructure involves hydrogen production, storage and delivery for utilization with clean energy applications. Hydrogen ingress into structural materials can be detrimental due to corrosion and embrittlement. To enable safe operation in applications that need protection from hydrogen isotopes, this review article summarizes most recent advances in materials design and performance characterization of barrier coatings to prevent hydrogen isotopes’ absorption ingress and permeation. Barriers are crucial to prevent hydride formation and unwanted hydrogen effects to increase safety, materials’ lifetime and reduce cost for applications within nuclear and renewable energy. The coating may be applied on a material that requires protection from hydrogen pick-up, transport and hydride formation in hydrogen storage containers, in pipelines, spent nuclear fuel storage or in nuclear reactors. While existing, commercial coatings that have been much in use may be satisfactory for various applications, it is desirable to evaluate whether alternative coating concepts can provide a greater resistance to hydrogen isotope permeation along with other improved properties, such as mechanical strength and thermal resistance. The information presented here is focusing on recent findings within the past 5–7 years of promising hydrogen barriers including oxides, nitrides, carbon, carbide, MAX-phases and metals and their mechanical strength, hydrogen pick-up, radiation resistance and coating manufacturing techniques. A brief introduction to hydrogen permeation is provided. Knowledge gaps were identified to provide guidance for material’s research prospects.

08 HYDROGEN↗

DOE OSTI2024

Small scale tensile testing technique for measuring grain boundary strength of neutron-irradiated materials in focused ion beam systems

Irradiation induced defects on grain boundaries (GBs) can lead to GB strength degradation and cause intergranular cracking in structural materials, affecting the safe operation and service life of nuclear reactors. Establishing the quantitative relationship between the strength and character/microchemistry for individual GB in an effort of integrating experimental measurements and multiscale simulations.

36 MATERIALS SCIENCE↗

DOE OSTI2020

He ion irradiation response of a gradient T91 steel

Metallic materials with a gradient microstructure usually exhibit excellent mechanical properties. How- ever, the radiation response of gradient structural materials is less well understood. In this work, room- temperature He ion irradiation up to ~4.5 dpa with ~10 at% He injection was performed on a gradient T91 steel processed by surface severe plastic deformation. In comparison to the coarse-grained ferritic T91, the gradient T91 with the nanocrystalline layers shows improved radiation tolerance in terms of less bubble swelling and radiation hardening. Additionally, bubble distribution along grain boundaries depends on misorientation angle suggesting a strong capacity of non-equilibrium grain boundaries in storing He atoms. The present study provides insight into the design of radiation tolerant gradient steels for nuclear industry applications.

36 MATERIALS SCIENCE↗

DOE OSTI2025

New class of tritium breeders for fusion applications: Metal-reinforced composite breeders

Commercial fusion reactors operating on a D-T fuel cycle will require a steady supply of tritium to maintain the burning plasma required for continuous power generation. Since tritium has a short half-life, there is negligible natural abundance which necessitates fusion reactors to produce their own source of tritium. Tritium is most easily produced by surrounding a fusion reactor core with lithium (Li), which reacts under the intense neutron flux leaving the reactor core to form tritium and helium. Due to the hazards and technical challenges associated with surrounding a fusion reactor core with many tons of molten Li, other Li-bearing tritium breeder materials have been pursued. Unfortunately, most of the liquid breeders historically examined are exceedingly corrosive to reactor structural materials while many solid breeders in the form of ceramics are forced to make tradeoffs between Li content and mechanical integrity. In this work, to break the historic limit between Li-density and mechanical integrity of traditional solid breeders, a new class of solid tritium breeders is developed: metal-reinforced composite (MERC) breeders. Specifically, the high Li-density of lithium oxide (Li 2 O) is exploited through the addition of a metal reinforcing phase, producing a composite breeder material exhibiting high splitting tensile strength and quasi-ductility with a Li-density greater than other leading solid breeder candidates, including lithium orthosilicate (Li 4 SiO 4 ) and lithium metatitanate (Li 2 TiO 3 ). Mechanical testing, microstructural characterization, and neutronic simulation results are presented and discussed in light of fusion reactor design considerations.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Understanding the Photochemical Properties of Polythiophene Polyelectrolyte Soft Aggregates with Sodium Dodecyl Sulfate for Antimicrobial Activity

The threat of antibiotic-resistant bacteria is an ever-increasing problem in public health. In this report, we examine the photochemical properties with a proof-of-principle biocidal assay for a novel series of regio-regular imidazolium derivative poly-(3-hexylthiophene)/sodium dodecyl sulfate (P3HT-Im/SDS) materials from ultrafast sub-ps dynamics to μs generation of reactive oxygen species (ROS) and 30 min biocidal reactivity with Escherichia coli (E. coli). This broad series encompassing pure P3HT-Im to cationic, neutral, and anionic P3HT-Im/SDS materials are all interrogated by a variety of techniques to characterize the physical material structure, electronic structure, and antimicrobial activity. Our results show that SDS complexation with P3HT-Im results in aggregate materials with reduced ROS generation and light-induced anti-microbial activity. However, our characterization reveals that the presence of non-aggregated or lightly SDS-covered polymer segments is still capable of ROS generation. Full encapsulation of the P3HT-Im polymer completely deactivates the light killing pathway. High SDS concentrations, near and above critical micelle concentration, further deactivate all anti-microbial activity (light and dark) even though the P3HT-Im regains its electronic properties to generate ROS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Nanoscale Mass Spectrometry Multimodal Imaging via Tip-Enhanced Photothermal Desorption

Materials ranging from adhesives, pharmaceuticals, lubricants, and personal care products are traditionally studied using macroscopic characterization techniques. However, their functionality is in reality defined by details of chemical organization on often noncrystalline matter with characteristic length scales on the order of microns to nanometers. Additionally, these materials are traditionally difficult to analyze using standard vacuum-based approaches that provide nanoscale chemical characterization due to their volatile and beam-sensitive nature. Therefore, approaches that operate under ambient conditions need to be developed that allow probing of nanoscale chemical phenomena and correlated functionality. Here, we demonstrate a tool for probing and visualizing local chemical environments and correlating them to material structure and functionality using advanced multimodal chemical imaging on a combined atomic force microscopy (AFM) and mass spectrometry (MS) system using tip-enhanced photothermal desorption with atmospheric pressure chemical ionization (APCI). We demonstrate enhanced performance metrics of the technique for correlated imaging and point sampling and illustrate the applicability for the analysis of trace chemicals on a human hair, additives in adhesives on paper, and pharmaceuticals samples notoriously difficult to analyze in a vacuum environment. Overall, this approach of correlating local chemical environments to structure and functionality is key to advancing research in many fields ranging from biology, to medicine, to material science.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Exploring the origins of the indentation size effect at submicron scales

Significance Downscaling material structure into ever-decreasing levels for modern technological advancements demands small-scale mechanical characterizations of materials, such as nanoindentation. Thus, a comprehensive understanding of indentation size effect (ISE) has a far-reaching impact, but such understanding remains incomplete at the submicron scale despite a decades-long quest since the 1980s. Here, we explored the origins of this effect experimentally by linking dislocation behavior evolution with nanoindentation mechanical data at various depths. Importantly, the dislocation behavior is found to be strongly depth dependent and gives rise to subgrain formation progressively. Aided by subgrain boundaries, the ISE mechanism transitions from dislocation source starvation to dislocation interaction as indentation depth increases. The critical mechanism transition elucidates the distinctive ISE behavior at the submicron scale.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Discovering mechanisms for materials microstructure optimization via reinforcement learning of a generative model

Abstract The design of materials structure for optimizing functional properties and potentially, the discovery of novel behaviors is a keystone problem in materials science. In many cases microstructural models underpinning materials functionality are available and well understood. However, optimization of average properties via microstructural engineering often leads to combinatorically intractable problems. Here, we explore the use of the reinforcement learning (RL) for microstructure optimization targeting the discovery of the physical mechanisms behind enhanced functionalities. We illustrate that RL can provide insights into the mechanisms driving properties of interest in a 2D discrete Landau ferroelectrics simulator. Intriguingly, we find that non-trivial phenomena emerge if the rewards are assigned to favor physically impossible tasks, which we illustrate through rewarding RL agents to rotate polarization vectors to energetically unfavorable positions. We further find that strategies to induce polarization curl can be non-intuitive, based on analysis of learned agent policies. This study suggests that RL is a promising machine learning method for material design optimization tasks, and for better understanding the dynamics of microstructural simulations.

36 MATERIALS SCIENCE↗

DOE OSTI2025

MPEX AI Digital Twins

All magnetically confined plasma fusion power plant concepts (Tokamak, Spherical Tokamak, Stellarator, Mirror, ...) must exhaust the heat and plasma from the core confinement region to the material walls. The primary channel for this exhaust is through a plasma divertor which directs plasma along open magnetic field lines to a material target. The Material Plasma Exposure eXperiment (MPEX) illustrated in Figure 1, is a high-power, steady-state linear plasma device designed to produce the plasma material interaction (PMI) conditions of the divertor of future magnetic confinement fusion power plants: energy flux 20MW/m 2 , ion fluence 1031/m 2 , pulse duration 106 sec. These goals of plasma exposure in MPEX are well beyond those achieved in magnetic fusion experimental devices. Successfully achieving these high power steady state conditions for long pulses requires operational control of the heating and particle sources and the plasma flux to the walls and target. The MPEX AI Hot Spot Controller, proposed in this project, will help achieve the operational milestones of MPEX. The MPEX device will begin commissioning at the end of FY26. A smaller proto-MPEX was operated for 14,666 plasma discharges and will resume operation in September of 2025 as proto-MPEX-lite, with reduced capability, to test a new window for the Helicon plasma source. The proto-MPEX data has undergone surrogate modeling with machine learning methods (R. Archibald, 2022 IEEE International Conference on Big Data). This proto-MPEX data will be used to begin development of the AI digital twins described in this white paper. The scientific mission of MPEX is to qualify materials of different composition for use in the high energy and plasma flux conditions of a fusion power plant. The materials exposed in MPEX will in some cases be exposed to high neutron fluxes at other ORNL facilities to measure the changes to their PMI properties. The targets exposed in MPEX will be transported under vacuum to a Surface Analysis Station (SAS). The SAS will be equipped with the following diagnostics: Focused Ion Beam (FIB) for trench milling, 100-400 angstrom resolution scanning electron microscope (SEM), surface mapping x-ray spectrometer, high resolution camera, and a future upgrade to a laser induced breakdown spectroscopy quadruple mass spectrometer (LIBS-QMS). The MPEX experiments will generate diverse pre- and post-exposure measurement data of detailed material properties down to the crystal grain level in 3D for post-exposure assessment of PMI damage (e.g. cracking, melting, erosion and redeposition of the material). Physics models for the PMI, and how the material composition and manufacturing impact its performance under high energy plasma exposure, need to be validated with MPEX data to guide the selection of new candidate materials. Our vision for the MPEX AI Digital Twins project is to supply experimental and physics model simulation data to train Artificial Intelligence (AI) models for data processing, analysis, operational control, PMI and materials simulation to maximize the scientific output of the MPEX device. Ultimately, an AI digital twin of MPEX material assessment metrics for tested and synthetic material types with simulated PMI will be trained by the AI Modeling Teams on the experimental and physics simulation data submitted to the American Science Cloud by this project. A purely empirical search for the best material is inefficient given the finite number of samples that can be tested on MPEX. In order to expand the material properties database for training the MPEX Material Assessment AI Digital Twin, and to gain physics understanding of the PMI processes, physics models of the material properties and PMI processes are required. The physics simulations provide detailed simulation data, like impact angles for plasma ions, sputtering yields, transport of the ionized sputtered target material in the plasma, and redeposition locations. This simulation data expands the measurement data for deeper physics understanding. The experimental data is essential to validate the PMI and material structure simulation models. The validated models can then be used to generate new simulation data of MPEX material assessments for synthetic material compositions that have not been exposed in MPEX. These predictive simulations, plus the whole experimental dataset, will be used to train the MPEX Material Assessment AI Digital Twin allowing a rapid generative AI search for new materials with reduced PMI damage by interpolating the domain of the training set. These new optimum materials can be simulated with the physics codes and/or tested in MPEX. The ability of AI neural networks to interpolate multi-dimensional parameter spaces and generate virtual data is exploited for a more efficient search for optimum materials. The advent of the Transformational AI Models Consortium (TAIMC) is an opportunity to engage with state of the art private and public AI developers to achieve the goals of the AI digital twins and AI accelerated physics models proposed in this project. Our partners at ORNL from the Advance Scientific Computing Research (ASCR) organization will collaborate in accelerating the integrated plasma material interaction simulation framework. This simulation framework will provide a platform for generating simulation data across a range of physical fidelities, including hybrid methods that produce multi-fidelity results. This data will be leveraged for AI model development, both for generation of surrogates and the automation of simulation campaigns. A part of the research below will include collaborative efforts with the TAIMC to (i) adapt data storage approaches to ensure AI-readiness, (ii) provide a protypical exemplar to inform and exercise constructed workflows, and (iii) generate and share data, using the TAIMC unified AI data standard, for foundational models that will be trained from multiple sources across the DOE complex. We will also collaborate with the TAIMC, as well as the planned AI modeling teams, to develop approaches for reducing the cost of data generation. These include tailored multi-fidelity approaches as well as fine-tuning strategies to augment general, large-scale foundational models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Accelerating Nuclear Fuels and Materials Qualification by Multi-Level Irradiation Experiment Campaign

The advanced reactor technologies feature fuels, coolants, and materials that promise safer operating conditions under normal and accident scenarios. However, the nuclear fuels and materials qualifications require several decades (for example, new reactor fuel qualification from conceptualization requires about 20 years). Therefore, accelerating nuclear fuels and materials qualification is essential, and it can be achieved by combining high through-put materials irradiation and testing, advanced post-irradiation examinations, and Multiphysics modeling. This paper addressed the associated challenges in accelerating nuclear fuels and material qualification for new and advanced reactor designs, which differ based on fuel, coolant, operating conditions, and structural materials. These challenges vary for radiation level, operating conditions (e.g., temperature and pressure), and coolant type (e.g., corrosion environment). In addition, the challenges and limitations in modeling tools, experimental facilities, and licensing guidelines are also discussed, and a general solution path forward is recommended.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2023

Presentation: Accelerating Nuclear Fuels and Materials Qualification by Multi-Level Irradiation Experiment Campaign

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2021

The In Situ Ion Irradiation Toolbox: Time-Resolved Structure and Property Measurements

Abstract The dynamic interactions of ions with matter drive a host of complex evolution mechanisms, requiring monitoring on short spatial and temporal scales to gain a full picture of a material response. Understanding the evolution of materials under ion irradiation and displacement damage is vital for many fields, including semiconductor processing, nuclear reactors, and space systems. Despite materials in service having a dynamic response to radiation damage, typical characterization is performed post-irradiation, washing out all information from transient processes. Characterizing active processes in situ during irradiation allows the mechanisms at play during the dynamic ion-material interaction process to be deciphered. In this review, we examine the in situ characterization techniques utilized for examining material structure, composition, and property evolution under ion irradiation. Covering analyses of microstructure, surface composition, and material properties, this work offers a perspective on the recent advances in methods for in situ monitoring of materials under ion irradiation, including a future outlook examining the role of complementary and combined characterization techniques in understanding dynamic materials evolution.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Understanding FLiNaK Salt Intrusion Behavior on Nuclear-Grade Graphite via Neutron Tomography

Graphite is an essential material as a neutron moderator in molten salt reactors (MSRs). To understand the impact of salt on the graphite structure to develop structural materials for MSRs, molten salt intrusion behavior on nuclear-grade graphite was studied. The graphite samples, IG-110 and PCEA, were tested for infiltration with LiF-NaF-KF (FLiNaK) at 750°C, 5 bar for 12 h, and, after the intrusion experiment, the graphite was analyzed by neutron imaging. The graphite and Li from FLiNaK showed great contrast in the neutron attenuation coefficient. Thus, the salt behavior in the graphite structure has been visualized for the first time without damaging the sample. The 3D image of the graphite was reconstructed after a neutron computed tomography scan, and the average salt coverage distribution of the XY surface in different depths was obtained from the reconstructed 3D images.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗