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This presentation is for ASME Section III at University of Tennessee Student Event on October 18, 2023. Includes ASME Section III - Rules for construction of nuclear facility components, including an all-inclusive term that includes material, design, fabrication, installation, examination, testing, overpressure protection, inspection, stamping, and certification, and discusses Division 1-5.
Precise control over electronic coupling at nanoscale interfaces is critical for designing materials with tunable charge-transfer behavior and catalytic function. Heterostructures with locally coherent interfaces provide a platform for interrogating interfacial charge redistribution in coupled material systems. Here, we report Cu 2 S/MoS 2 heterostructures exhibiting nanoscale crystallographic alignment, which are synthesized through a rapid thermal transformation pathway. We employed electrochemical reduction reactions to probe interfacial charge transfer, revealing shifts in product distribution attributable to modified interfacial energetics, even in the absence of optimized catalytic performance. The observed formate Faradaic efficiency suggests that interfacial electronic modulation in the heterostructure shifts product selectivity towards formate, highlighting how interface-driven electronic modulation can direct reaction pathways and influence product selectivity. Optimizing catalyst loading, architecture, and reactor configuration will be critical for future improvement. Structural and compositional integrity were confirmed through powder x-ray diffraction, x-ray photoelectron spectroscopy, and high-resolution transmission electron microscopy. Electron transfer between Cu 2 S and MoS 2 domains was further evaluated by electrochemical impedance spectroscopy, while selected-area electron diffraction revealed local crystallographic alignment consistent with a local epitaxial relationship at the Cu 2 S/MoS 2 heterointerface. To illustrate the broader applicability of this approach, a ZnS/MoS 2 heterostructure was also synthesized using the same microwave strategy, confirming the generalizability of interfacial engineering principles across metal sulfide-MoS 2 systems. Collectively, these findings demonstrate that controlled local epitaxial alignment serves as an effective design principle for tuning interfacial energetics and catalytic reactivity in complex heterostructure materials.
Blast furnace slag (BPS) is a critical component of grout formulations for the remediation of low activity nuclear waste. This interim report describes the initial results of a study designed to investigate the fundamental mechanisms of BPS dissolution. The goal of the work is to delineate the physicochemical aspects of the slag that impart beneficial properties to grout formulations to enable the consistent production of a slag-replacement material (“designer slag”) that performs better than what is commercially available. This report documents the dissolution experiments that were conducted using nine different initial solution compositions. Solution measurements for each solution, including pH and solution composition, are given for 1, 7, 14, 28, and 56 day intervals samples. Scanning electron microscopy images are presented for the 56 day samples from each of the solutions. Inferences about reaction mechanisms and 56-day mineralogy are made based on the information collected to date. Some conclusions are made based on the work performed for this interim report, and a path forward including the strategy for making stronger conclusions based on X-ray diffraction (XRD) analyses is presented.
To make the power density of electric aircraft closer to conventional aircraft, an electric power system (EPS) with high power delivery and low system mass is necessary. As an essential component of aircraft EPS, cables are necessary to transmit power from one node to another. Virginia Tech will design high-power density, cost-effective ±5 kV cables for twin-aisle all-electric aircraft. Innovations include conductors with increased current-carrying capacity and a multilayer, multifunctional insulation system made of exceptionally high thermal conductivity materials. Designed for DC voltage, the new insulator will allow fewer partial discharge events and provide improved electromagnetic interference protection.
Understanding and controlling microscopic heat transfer mechanisms in solids is critical to material design in numerous technological applications. Yet, the current understanding of thermal transport in semiconductors and insulators is limited by the difficulty in directly measuring individual phonon lifetimes and mean free paths, and studying their dependence on the microscopic state of the material. Here in this paper, we report our measurements of microscopic phonon scattering rates in AgBiSe 2 , which exhibits a controllable, reversible change directly linked to microstructure evolution near a reversible structural phase transition, that directly impacts the thermal conductivity. We demonstrate a steplike doubling of phonon scattering rates resultant from the cation disordering at the structural transition. To rationalize the neutron scattering data, we leverage a stepwise approach to account for alterations to the thermal conductivity that are imparted by distinct scattering mechanisms. These results highlight the potential of tunable microstructures housed in a stable crystal matrix to provide a practical route to tailor phonon scattering to optimize thermal transport properties.
The compact Fusion Pilot Plant (FPP) is defined in the recent National Academies of Sciences, Engineering, and Medicine report as the next step of fusion energy demonstration with a $50$ MWe peak net electricity production, $Q_e$ greater than $1$, and at least $3$ hours of continuous operation. This fusion pilot plant will be a test bed enabling materials, designs, and fuel management assessment, and it will represent an engineering challenge because of its high-fusion power and compact design targets. Previous reactor data is limited to experiments operating in different design space ranges. Therefore, design iterations and assessments should rely on high-fidelity first-principle theoretical and computational models. The high-fidelity integrated modeling of the plasma is a fundamental part of fusion energy research. However, the whole device modeling is often neglected, utilizing low-fidelity, system-level analysis. Recently, the need for high-fidelity multi-physics modeling was recognized, resulting in a selection of integrated tools. Further, autonomous design optimization requires a streamlined framework that perturbs the design point, reruns the analysis, and examines the outputs. However, high-fidelity analysis requires complex geometry specification that is difficult to perturb. This work presents the parametric CAD generation tool TRACER and a new neutronic workflow. TRACER allows the perturbation of the geometry representation, creating geometry files ready for further analysis. The streamlined neutronic workflow allows efficient and accurate calculations. The two new tools coupled together were used to perform a 3D high-fidelity multi-objective, multi-input optimization of an "ARC Class" compact tokamak design. The workflow was driven by an optimization driver for full automation.
A critical bottleneck for further efficiency breakthroughs in organic solar cells (OSCs) is to minimize the non-radiative energy loss (eΔV nr ) while maximizing the charge generation. With the development of highly emissive low-bandgap non-fullerene acceptors, the design of high-performance donors becomes critical to enable the blend with the electroluminescence quantum efficiency to approach or surpass the pristine acceptor. Herein, by shortening the end-capped alkyl chains of the small-molecular donors from hexyl (MPhS-C6) to ethyl (MPhS-C2), the material obtained aggregation that was insensitive to thermal annealing (TA) along with condensed packing simultaneously. The former leads to small phase separation and suppressed upshifts of the highest occupied molecular orbital energy level during TA, and the latter facilitates its efficient charge-transport at aggregation-less packing. Hence, the ΔV nr decreases from 0.242 to 0.182 V, from MPhS-C6 to MPhS-C2 based OSCs. An excellent PCE of 17.11% is obtained by 1,8-diiodoctane addition due to almost unchanged high J sc (26.6 mA cm –2 ) and V oc (0.888 V) with improved fill factor, which is the record efficiency with the smallest energy loss (0.497 eV) and ΔV nr (0.192 V) in all-small-molecule OSCs. Finally, these results emphasize the potential material design direction of obtaining concurrent TA-insensitive aggregation and condensed packing to maximize the device performances with a super low ΔV nr .
Here, in this work, a long-established but sparsely documented method of obtaining semi-analytic derivatives of thermodynamic properties with respect to equilibrium conditions is briefly reviewed and rigorously derived. This procedure is then leveraged to construct general forms of derivatives of the residual driving force, a metric for measuring phase stability used in CALPHAD model optimization, with respect to overall system and individual phase compositions. Applied examples – calculating heat capacity in the Al-Fe system, thermodynamic factors in the Nb-V-W system, and residual driving force derivatives in the Ni-Ti system – demonstrate the versatility, accuracy, and extensibility of this method. Using the developed method, residual driving force gradients can be applied directly in CALPHAD model optimizers, as well as in materials design frameworks, to identify regions of phase stability with an efficient, gradient-based approach.
The multicomponent Ti alloys, specifically the -phase, have experienced a strong growth over the last decades, due to their outstanding properties of ultra-high strength and low Young’s modulus. These properties play a significant role in many aerospace and biomedical applications. Selection and optimization of multicomponent alloys is challenging due to the vast chemical and compositional space. Here we investigate the use of machine learning techniques informed by density functional calculations to guide the selection of Nb- and Zr-based Ti binary alloys. From the cubic structures obtained from high throughput calculations and literature, we identify several structures with Young’s moduli below 40 GPa. The multivariant decision tree methods provide efficient surrogate models to identify structure variables have high influences on the energetic stability and Young’s modulus. Furthermore, we implement a workflow of incorporating DFT provided results and machine learning method to explore the chemical and composition space of other binary and multicomponent alloys, to eventually accelerate the material design via taking advantages of identified key variables.
The present report describes the establishing of an advanced experimental approach – high-resolution digital image correlation or µDIC – for testing miniature irradiated specimens in the ORNL’s Low Activation Materials Development and Analysis (LAMDA) facility. As expected, the µDIC approach will allow for studying strain localization inside grains, for instance, during dislocation channel-grain boundary interaction processes. This information is of high importance for understanding degradation processes in irradiated austenitic steels – in-core materials of Light Water Reactors. The Level 4 report provides a brief introduction, lists materials designated for µDIC testing and delivered in LAMDA this FY, discusses methodical concerns and preliminary observations.
Magnetic tunnel junctions (MTJs) have been widely utilized in sensitive sensors, magnetic memory, and logic gates due to their tunneling magnetoresistance. Moreover, these MTJ devices have promising potential for renewable energy generation and storage. Compared with Si-based devices, MTJs are more tolerant to electromagnetic radiation. In this review, we summarize the functionalities of MgO-based MTJ devices under different electromagnetic irradiation environments, with a focus on gamma-ray radiation. We explore the effects of these radiation exposures on the MgO tunnel barriers, magnetic layers, and interfaces to understand the origin of their tolerance. This review enhances our knowledge of the radiation tolerance of MgO-based MTJs, improves the design of these MgO-based MTJ devices with better tolerances, and provides information to minimize the risks of irradiation under various irradiation environments. This review starts with an introduction to MTJs and irradiation backgrounds, followed by the fundamental properties of MTJ materials, such as the MgO barrier and magnetic layers. Then, we review and discuss the MTJ materials and devices’ radiation tolerances under different irradiation environments, including high-energy cosmic radiation, gamma-ray radiation, and lower-energy electromagnetic radiation (X-ray, UV–vis, infrared, microwave, and radiofrequency electromagnetic radiation). In conclusion, we summarize the radiation effects based on the published literature, which might benefit material design and protection.
The generation of high-order neutron scattering cross sections consistent with high-fidelity simulations remains an area of active research. Popular options include generating cross sections from continuous energy Monte Carlo calculations or generating cross sections from a deterministic neutron transport calculation with high-fidelity tabulated cross sections. Both options present challenges. Monte Carlo simulations can naturally process continuous energy cross section data and allow for the general description of anisotropic neutron scattering given a scattering law. However, Monte Carlo simulations are inherently related to particle weighting and it has been suggested that this may be unacceptable for generating high-order neutron scattering cross sections. Deterministic neutron transport calculations can easily calculate high-order moments of the flux to appropriately calculate higher-order neutron scattering cross sections but are generally limited by discretization of space, energy, and angle. In this work, the trade-offs between generation of high-order neutron scattering cross sections via Monte Carlo and deterministic neutron transport methods are investigated. The methods implemented in the Monte Carlo computer program Serpent and the deterministic fast reactor neutron cross section generator MC2-3 are compared. Cross sections resulting from these methods are used in Rattlesnake, a deterministic neutron transport code developed by Idaho National Laboratory (INL), and results are compared to a reference continuous energy Monte Carlo calculation. Whereas previous work investigating the effects of anisotropic neutron scattering has focused on light water reactor (LWR) simulations, this work focuses on high-order neutron scattering cross sections as they relate to fast reactor simulations. To investigate the consequences of the Serpent and MC2-3 methodologies, a test problem is developed. The test problem is a one-dimensional geometry with fast reactor materials designed to demonstrate deep penetration and exacerbate the effects of high-order neutron scattering. Based on the results of the deep penetration test problem, it is concluded that P3 neutron scattering cross sections are sufficient to describe anisotropic scattering in fast reactor materials. Any neutron scattering of order higher than P3 offers negligible change in the eigenvalue of the test problem. Additionally, it is determined that the methodology as implemented in Serpent is applicable for generating high-order neutron scattering cross sections through at least P3 in fast reactor materials.
The capture of CO2 and its simultaneously conversion to useful chemical fuels driven by solar energy represents one of the best solutions to resolve our growing energy and environmental concerns. The most critical challenge to this endeavor is the rational design of a photocatalytic architecture that can effectively couple a given photosensitizer (PS) with an appropriate catalyst, thereby enabling efficient photosensitization of a multi-electron reduction catalysis. This research program aims to address this challenge using an interdisciplinary approach that combines innovative material design and synthesis, fundamental mechanistic studies, and photocatalytic performance evaluation. The strategies include 1) constructing and investigating a novel class of 2D COF hybrid photocatalysts with an effective photoactive organic building block as PS and a precisely incorporated CO2 reduction molecular catalyst (MC); and 2) mechanistic origins of CO2 photoreduction using a set of complementary time-resolved and in situ spectroscopic techniques. The novelty of the proposed hybrid system lies in the unprecedented combination of the unique advantage of porous crystalline COF PS with the precise catalytic function of MC for photocatalytic CO2 reduction. In the periods of the support (09/01/2019-12/31/2022), we have made research progress in four projects: 1) Exploring 2D COFs with incorporated Mn complex for light driven CO2 reduction; 2) The dependence of excited state and charge transfer dynamics on monomer structure of 2D COFs; and 3) Control over Charge Separation by Imine Structural Isomerization in Covalent Organic Frameworks with Implications on CO2 Photoreduction; and 4) The impact of monomer structure on the photoluminescence properties of COFs. We found that both monomer structure and linker chemistry can effectively impact the excited state dynamics, charge transfer properties, and photoluminescence quantum yields, the important properties that dictate their applications in photocatalysis. In addition, we found that the direction of imine linker determines charge transfer direction and thus controls the types of catalytic reactions (e.g. water oxidation or CO2 reduction reactions). The result from these fundamental studies provides important information for correlating the structure of the COF photocatalysts with their photophysical properties and catalytic functions, paving the way for their novel application in photocatalysis. We expect that our findings will contribute to addressing current shortcomings of semiconductor- and molecular-based photocatalytic systems that suffer from inefficient light harvesting and charge separation and poor adsorption and activation of reactants. In turn, this research will contribute towards the development of novel photocatalytic systems for CO2 reduction to generate renewable chemical fuels and simultaneously address the problem of mitigating climate change due to CO2 accumulation. In addition, the experimental approaches employed in this research can be easily transferred to other energy technologies and are expected to broadly impact fields involving photocatalysis, optoelectronic devices, and solar energy conversion. The proposed research has also been integrated with educational activities and serve as a basis to raise awareness around the critical issues of global energy production and consumption, and to develop the next generation of solar energy scientists.
Industrial process heat (IPH) is one of the largest energy demands in U.S., representing about 10% of all domestic energy consumption. Fuel costs to generate this industrial process heat are generally a top three cost for industry, a major component in American manufacturing competitiveness. Roughly 60% of US IPH demand (about 6,500 TBtu annually) falls in the medium-temperature range of 100–250 °C. While concentrated solar thermal (CST) technologies can provide a cost-effective source of heat in this temperature range, solar intermittency limits their adoption in industries that operate 24/7. Element 16 Technologies, Inc. developed a low-cost sulfur thermal energy storage (TES) technology to bridge this gap by capturing excess solar heat during the day and dispatching it reliably during non-solar hours. The core innovation is the use of sulfur, an abundant, industrial waste byproduct that costs ten times less than molten salt used in commercial TES systems. The overall goal of the project was to advance the design and development of molten sulfur TES to a manufacturing-relevant prototype stage for solar industrial process heat applications, while establishing and validating a realistic pathway to commercial success. Key tasks included corrosion and mechanical durability testing to identify cost-effective materials, design investigations using physics-based simulation tools, techno-economic evaluations of system lifetime costs, and pilot-scale testing for performance verification. Corrosion testing of steel alloys under cyclic molten sulfur conditions showed that austenitic stainless steels in the 300 series performed particularly well, with no structural degradation of welds or joints. Thermal cyclic testing of pilot sulfur TES units up to 1.5 MWh quantified charge/discharge rates, heat losses, round-trip efficiency and validated the system's capability to operate effectively under intermittent charging conditions. A techno-economic model, informed by sulfur TES performance model validated using pilot test data, showed that hybrid solar+sulfur TES+NG boiler systems are economically competitive with incumbent natural gas boilers for multiple locations in the southwest US. In summary, this project established molten sulfur TES as a technically viable pathway to improve economic competitiveness of American manufacturing by lowering the cost of solar industrial process heat.
Machine learning (ML) has become a part of the fabric of high-throughput screening and computational discovery of materials. Despite its increasingly central role, challenges remain in fully realizing the promise of ML. This is especially true for the practical acceleration of the engineering of robust materials and the development of design strategies that surpass trial and error or high-throughput screening alone. Depending on the quantity being predicted and the experimental data available, ML can either outperform physics-based models, be used to accelerate such models, or be integrated with them to improve their performance. We cover recent advances in algorithms and in their application that are starting to make inroads toward ( a) the discovery of new materials through large-scale enumerative screening, ( b) the design of materials through identification of rules and principles that govern materials properties, and ( c) the engineering of practical materials by satisfying multiple objectives. We conclude with opportunities for further advancement to realize ML as a widespread tool for practical computational materials design.
The performance of ISS spacecraft materials and systems on prolonged exposure to the low- Earth orbit (LEO) space flight are reported in this paper. In-flight data, flight crew observations, and the results of ground-based test and analysis directly supporting programmatic and operational decision-making are described. The space flight environments definitions (both natural and induced) used for ISS design, material selection, and verification testing are shown, in most cases, to be more severe than the actual flight environment accounting, in part, for the outstanding performance of ISS as a long mission duration spacecraft. No significant ISS material or system failures have been attributed to spacecraft-environments interactions. Nonetheless, ISS materials and systems performance data is contributing to our understanding of spacecraft material interactions with the spaceflight environment so as to reduce cost and risk for future spaceflight projects and programs. Orbital inclination (51.6 deg) and altitude (nominally near 360 km) determine the set of natural environment factors affecting the functional life of materials and systems on ISS. ISS operates in an electrically conducting environment (the F2 region of Earth s ionosphere) with well-defined fluxes of atomic oxygen, other charged and neutral ionospheric plasma species, solar UV, VUV, and x-ray radiation as well as galactic cosmic rays, trapped radiation, and solar cosmic rays. The LEO micrometeoroid and orbital debris environment is an especially important determinant of spacecraft design and operations. The magnitude of several environmental factors varies dramatically with latitude and longitude as ISS orbits the Earth. The high latitude orbital environment also exposes ISS to higher fluences of trapped energetic electrons, auroral electrons, solar cosmic rays, and galactic cosmic rays than would be the case in lower inclination orbits, largely as a result of the overall shape and magnitude of the geomagnetic field. As a result, ISS exposure to many environmental factors can vary dramatically along a particular orbital ground track, and from one ground track to the next, during any 24-hour period. The induced environment results from ISS interactions with the natural environment as well as environmental factors produced by ISS itself and visiting vehicles fleet. Examples include ram-wake effects, hypergolic thruster plume impingement, materials out-gassing, venting and dumping of fluids, and specific photovoltaic (PV) power system interactions with the ionospheric plasma (7-11). Vehicle size (L) and velocity (V), combined with the magnitude and direction of the geomagnetic field (B) produce operationally significant magnetic induction voltages (VxB.L) in ISS conducting structure during flight through high latitudes (> +45deg) during each orbit. Finally, an induced ionizing radiation environment is produced by cosmic ray interaction with the relatively thick ISS structure and shielding materials. The intent of this review article is, therefore, to provide a summary of selected aspects and elements of the ISS vehicle with regard to LEO space environment effects, associated with the much larger and more complicated vehicle that ISS has become since 1998, but also with an eye towards performance life extension to the year 2016 and beyond.
Optical constants characterize the interaction of materials with light and are important properties in material design. Here we present a Python-based Corvus workflow for simulations of full spectrum optical constants from the visible and ultraviolet to hard x-ray wavelengths based on the real-space Green’s function code FEFF10 and structural data from the Materials Project (MP). The Corvus workflow manager and its associated tools provide an interface to FEFF10 and the MP database. The workflow parallelizes the FEFF computations of optical constants over all absorption edges for each material in the MP database specified by a unique MP-ID. The workflow tools determine the distribution of computational resources needed for that case. Similarly, the optical constants for selected sets of materials can be computed in a single-shot. Additionally, to illustrate the approach, we present results for several elemental solids in the periodic table, as well as a sample compound, and compare our predictions with experimental results. In addition, we provide a database of calculated results for all elements for which there is a stable elemental solid at standard conditions available in the Materials Project database. As in x-ray absorption spectra, these results are interpreted in terms of an atomic-like background and fine-structure contributions.
Crystalline materials can be strengthened by introducing dissimilar phases that impede dislocation glide. At the same time, the changes in microstructure and chemistry usually make the materials less ductile. One way to circumvent the strength–ductility dilemma is to take advantage of heterogeneous nanophases which simultaneously serve as dislocation barriers and sources. Owing to their superior mechanical properties, heterogeneous nanostructured materials (HNMs) have attracted a lot of attention worldwide. Nevertheless, it has been difficult to characterize dislocation dynamics in HNMs using classical continuum models, mainly due to the challenges in describing the elastic and plastic heterogeneity among the phases. Here, in this work, we advance a phase-field dislocation dynamics (PFDD) model to treat multi-phase materials, consisting of phases differing in composition, structural order, and size in the same system. We then apply the advanced PFDD model to exploring two important but divergent materials design problems in HNMs: dislocation/obstacle interactions and dislocation/interface interactions. Results show that the interactions between a dislocation and distribution of obstacles varying in structure and composition cannot be understood by simply interpolating from their individual interactions with a dislocation. It is also found that materials containing interfaces with nanoscale thicknesses and compositional gradients have a much higher dislocation bypass stress than those with sharp interfaces, providing an explanation for the simultaneous high strength and toughness of thick interface-containing nanolaminates as observed in recent experiments.