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At least 73 records · Page 4

Advanced microfabrication technologies for microspacecraft

Advanced microfabrication technologies offer the prospect of reducing the weight and size of spacecraft through the use of lighter and stronger materials in conjunction with new mechanical/structural design concepts and design optimization methods. At the same time, electronic components have been scaled down while increasing functional utility. A two-fold benefit is derived for space applications through the use of less expensive components and the lower launch costs associated with lighter components. GE-CRD is actively pursuing research in these key technologies for a wide range of applications including satellites. These key technologies will be reviewed and an update on GE progress will be given. The need to reduce weight and lower cost, while maintaining product quality and reliability are primary drivers in the design of satellites, in general, and microsatellites in particular. For the structural subsystem, these requirements pose a complex design problem unless new mechanical design concepts and computer-aided design optimization methods are employed. Several new concepts, such as battery packs doubling as panel reinforcements and fuel tanks as integral structural members, need to utilized. In addition, new viscoelastic material damping concepts for spacecraft components provide for lighter weight/lower cost designs, while satisfying the structural dynamics requirements. High density interconnect (HDI) technology permits the use of bare IC's on a ceramic substrate with 90 percent active area utilization. A copper/polyimide multilayer structure is the backbone of the technology, which has demonstrated a size/weight reduction of greater than 10x compared to printed circuit board with performance up to the GHz level. HDI modules have exceptional mechanical robustness as evidenced by survival of 180 kg rapid acceleration tests. Microelectromechanical systems (MEMS) are redefining sensors and actuators by miniaturization through micromachining techniques. Sharing many fabrication steps with HDI, we have developed a new technique for surface micromachining of copper/polyimide structures using computer-aided laser patterning.

Ghezzo, M.↗

A machine learning approach to quantify degradation of nuclear fuels and the effects of fission products

Nuclear fuel performance is critically dependent on understanding the evolution of fuel properties under operational conditions, a complex challenge driven by chemical changes and substantial radiation damage during fission. Traditionally, property evolution has been determined via empirical data collected following irradiation. However, these empirical correlations are limited in their applicability beyond the specific conditions in which they were obtained. This study explores a novel approach to address this challenge by applying materials informatics to develop a machine learning random forest (ML-RF) model that captures the effects of fission products on fuel compounds. The model predicts formation enthalpy (ΔH f ) by leveraging extensive quantum materials property data and correlating it with material descriptors such as composition, atomic and site features, and crystal lattice properties. This ML-RF model enables rapid interpolation across the compositional and structural spaces covered by the training data, thus supporting high-throughput screening and energetic ranking of candidate phases. The model demonstrates the ability to predict ΔH f with a mean absolute error (MAE) of approximately 0.1 to 0.2 eV/atom across a wide range of compounds, including key nuclear fuel systems (U-O, U-N, U-C, U-Si, and U-Mo). For example, it was used to assess shifts in stoichiometry for UO 2 (O/M) and UN (N/M) fuels, revealing their distinct tendencies in chemical potential variation and enabling preliminary convex hull analyses. Furthermore, the model provides insights into how individual fission products affect fuel properties. Results indicate that larger fission products (e.g., Nd, Pu, Ce) have a more pronounced impact on UO 2 , while lighter ones (e.g., Zr) strongly influence UN. Here, the model developed in this work can be used to support the Accelerated Fuel Qualification approach by facilitating preliminary evaluations prior to extensive materials modeling and experimentation. To this end, the trained model has been made available to the fuel community to support ongoing fuel development efforts.

Accelerated fuel qualification↗

A framework for strategic discovery of credible neural network surrogate models under uncertainty

The widespread integration of deep neural networks in developing data-driven surrogate models for high-fidelity simulations of complex physical systems highlights the critical necessity for robust uncertainty quantification techniques and credibility assessment methodologies, ensuring the reliable deployment of surrogate models in consequential decision-making. Here, this study presents the Occam Plausibility Algorithm for surrogate models (OPAL-surrogate), providing a systematic framework to uncover predictive neural network-based surrogate models within the large space of potential models, including various neural network classes and choices of architecture and hyperparameters. The framework is grounded in hierarchical Bayesian inferences and employs model validation tests to evaluate the credibility and prediction reliability of the surrogate models under uncertainty. Leveraging these principles, OPAL-surrogate introduces a systematic and efficient strategy for balancing the trade-off between model complexity, accuracy, and prediction uncertainty. The effectiveness of OPAL-surrogate is demonstrated through two modeling problems, including the deformation of porous materials for building insulation and turbulent combustion flow for ablation of solid fuels within hybrid rocket motors.

42 ENGINEERING↗

Radiation Effects on Uranyl Tetrachloro Coordination Compounds: Impact of Lattice Water

Nuclear materials, such as uranium-bearing solids, are exposed to high levels of ionizing radiation throughout the nuclear fuel cycle; thus, it is important to develop a molecular-level understanding of how these materials behave and degrade in the presence of gamma (γ) irradiation. In the current study, three U(VI) tetrachloride complexes, M 2 [UO 2 Cl 4 ]·xH 2 O (where M = K + , Rb + , or Cs + and x = 0 or 2), and their respective chloride salts were exposed to 1–50 kGy of γ radiation using a 60 Co source. Irradiated materials were evaluated by using electron paramagnetic resonance (EPR) and Raman spectroscopy and were further explored by using density functional theory (DFT) methods. EPR spectra of the irradiated materials suggest the formation of a Cl-based radical for both the alkali salts and the uranyl tetrachloride compounds, and DFT calculations provide evidence that the Cl 2 –• radical is formed within these materials. The presence of water in the K + and Rb + compounds leads to additional spectroscopic signatures that could be traced back to water radiolysis and the formation of peroxide and superoxide species. DFT results support the formation of HO 2 • in the lattice and potentially the formation of a [UO 2 Cl 3 (O 2 )] 3– species, highlighting the impact of water within the hydrated material to alter U(VI) speciation by radiolysis.

36 MATERIALS SCIENCE↗

Solid Surface Combustion Experiment Yields Significant Observations

The spread of a flame over solid fuel is not only a fundamental textbook combustion phenomenon, but also the central element of destructive fires that cause tragic loss of life and property each year. Throughout history, practical measures to prevent and fight fires have been developed, but these have often been based on lessons learned in a costly fire. Since the 1960 s, scientists and engineers have employed powerful tools of scientific research to understand the details of flame spread and how a material can be rendered nonflammable. High-speed computers have enabled complex flame simulations, whereasand lasers have provided measurements of the chemical composition, temperature, and air velocities inside flames. The microgravity environment has emerged as the third great tool for these studies. Spreading flames are complex combinations of chemical reactions and several physical processes including the transport of oxygen and fuel vapor to the flame and the transfer of heat from the flame to fresh fuel and to the surroundings. Depending on its speed, air motion in the vicinity of the flame can affect the flame in substantially different ways. For example, consider the difference between blowing on a campfire and blowing out a match. On Earth, gravity induces air motion because of buoyancy (the familiar rising hot gases); this process cannot be controlled experimentally. For theoreticians, buoyant air motion complicates the problem modeling of flame spread beyond the capacity of modern computers to simulate. The microgravity environment provides experimental control of air motion near spreading flames, with results that can be compared with detailed theory. The Solid Surface Combustion Experiment (SSCE) was designed to obtain benchmark flame spreading data in quiescent test atmospheres--the limiting case of flames spreading. Professor Robert Altenkirch, Vice President for Research at Mississippi State University, proposed the experiment concept, and the NASA Lewis Research Center designed, built, and tested the SSCE hardware. It was the first microgravity science experiment built by Lewis for the space shuttle and the first combustion science experiment flown in space.

Sacksteder, Kurt R.↗

Low Cost Upper Stage-Class Propulsion (LCUSP)

NASA is making space exploration more affordable and viable by developing and utilizing innovative manufacturing technologies. Technology development efforts at NASA in propulsion are committed to continuous innovation of design and manufacturing technologies for rocket engines in order to reduce the cost of NASA's journey to Mars. The Low Cost Upper Stage-Class Propulsion (LCUSP) effort will develop and utilize emerging Additive Manufacturing (AM) to significantly reduce the development time and cost for complex rocket propulsion hardware. Benefit of Additive Manufacturing (3-D Printing) Current rocket propulsion manufacturing techniques are costly and have lengthy development times. In order to fabricate rocket engines, numerous complex parts made of different materials are assembled in a way that allow the propellant to collect heat at the right places to drive the turbopump and simultaneously keep the thrust chamber from melting. The heat conditioned fuel and oxidizer come together and burn inside the combustion chamber to provide thrust. The efforts to make multiple parts precisely fit together and not leak after experiencing cryogenic temperatures on one-side and combustion temperatures on the other is quite challenging. Additive manufacturing has the potential to significantly reduce the time and cost of making rocket parts like the copper liner and Nickel-alloy jackets found in rocket combustion chambers where super-cold cryogenic propellants are heated and mixed to the extreme temperatures needed to propel rockets in space. The Selective Laser Melting (SLM) machine fuses 8,255 layers of copper powder to make a section of the chamber in 10 days. Machining an equivalent part and assembling it with welding and brazing techniques could take months to accomplish with potential failures or leaks that could require fixes. The design process is also enhanced since it does not require the 3D model to be converted to 2-D drawings. The design and fabrication process can be sped up and improved with fewer errors to be accomplished in weeks instead of months.

Vickers, John↗

Versatile TRISO fuel particle modeling in Bison

Tri-structural isotropic (TRISO) fuel particles are a key component in several previous and current reactors as well as in a variety of novel nuclear reactor designs. Interest in TRISO fuel is on the rise, necessitating considerable computer modeling of TRISO fuel behavior in order to support related design and licensing activities. The Bison nuclear fuel performance code, which offers a full set of capabilities for modeling TRISO fuels, makes it easier to explore the various important aspects of TRISO fuel behavior. One key advantage of Bison is its ability to create meshes in 1D, 2D, and 3D. Users can customize these meshes for specific geometries, mesh densities, and use cases. This enables a wide variety of analyses, including thermal, structural, mass diffusion, homogenization, and statistical failure analyses. Furthermore, the meshing capability simplifies analysts’ workflows. The inherent mesh generation capability eliminates the need for separate mesh-generating software and mesh file management. Also, the fact that the meshes are customizable makes it straightforward to automate an investigation over a range of geometric parameters or mesh densities. Here, the present paper highlights the ease with which Bison may be used to create meshes for both simple and relatively complex TRISO fuel particles, and it explores the types of analyses enabled by these meshes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

FFTF HT9 Cladding Microstructure Characterization

The sodium-cooled fast reactor (SFR) is a promising candidate for next generation nuclear reactors, operating at extreme conditions which include high temperatures (>500?C core outlet temperature) and significant neutron damage. High-Cr martensitic HT9 steel is an excellent candidate for SFR cladding and duct material due to its compatibility with liquid sodium, good thermal conductivity, resistance to void swelling, and strong creep rupture strength [1-4].However, the harsh in-core environment of SFRs can cause complex microstructural changes and mechanical property degradation in HT-9. Ensuring the safe use of HT9 cladding for metallic fuel requires both a thorough understanding of its mechanical response to microstructure evolution as well as reliable microstructure-sensitive modeling predictions. Microstructure-sensitive modeling of high temperature creep behavior in HT9 cladding for SFR applications currently lack experimental data to model the phenomena accurately. To fill this need, methods to perform microstructural characterization have been developed and performed on HT9.

36 MATERIALS SCIENCE↗

Description of FY25 Theory and Simulation Performance Target: Development of an integrated modeling framework for fusion reactor design and assessment

The urgency to deliver fusion power is growing now more than ever, with increasing pressure for both public programs and private companies to meet milestones timelines and overcome significant remaining technical challenges to ensure growth of a nascent fusion industry in time to meet rapidly growing clean energy demands. With incredible advancements in computation and years of investment in fusion model development and validation, integrated modeling is poised to fill a key role in accelerating the timeline to a fusion pilot plant (FPP). Future fusion pilot plants will operate in regimes far beyond current experience, and device design will rely on physics-based prediction and extrapolation. Many concepts will also rely on simulation to assess safety (shielding, tritium management, materials activation and lifetimes), economics and scalability before the decision to build. Importantly, integrated simulation can be used to reveal and solve the complexities of system integration that may otherwise not be apparent in physical components or models developed in isolation. New experimental test facilities that produce relevant conditions to validate and resolve key technical challenges for various subsystems (materials, blankets, fuel cycle, etc.) have been repeatedly called for by the fusion community but are not yet realized. Integrated modeling has an important role in identifying realistic load conditions (thermal, electromagnetic, plasma, neutron and photon loads, etc.) and defining the components and experiments for these test facilities in order to ensure meaningful validation that sufficiently reduces modeling uncertainties and technical risk for the full integrated reactor. The Fusion REactor Design and Assessment (FREDA) SciDAC project is building a component-based integrated modeling framework & data structure to enable self-consistent, multi-fidelity, iterative optimization workflows for the fusion reactor design process. FREDA aims to shorten the time to viable designs by providing a set of flexible workflows to support the various stages of the design process using an integrated model hierarchy, ranging from the simple analytic descriptions to the highest fidelity, theory-based plasma and engineering modeling developed by the fusion and fission communities. These tools are expected to be needed for timely support of FPP design in the milestone program and in the FIRE collaboratives. The plasma simulation backbone of FREDA is IPS-FASTRAN with newly developed coupled Core-Edge Pedestal-SOL (CESOL) workflows, which is being extended to the far-SOL region up to the plasma facing components. FREDA incorporates the FERMI engineering modeling suite and will enable self-consistent evaluation of the thermal shields, limiters, blanket, magnets, and other surrounding structures with predictions of temperatures, erosion, dpa, activation, tritium generation and transport, creep, corrosion, material degradation, etc. Parametric generation of 3D CAD enables rapid iteration of component geometry in response to plasma and loading specifications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Trioxane-Air Counterflow Diffusion Flames in Normal and Microgravity

Trioxane, a weakly bound polymer of formaldehyde (C3H6O3, m.p. 61 C, b.p. 115 C), is a uniquely suited compound for studying material flammability. Like many of the more commonly used materials for such tests (e.g., delrin, polyethylene, acrylic sheet, wood, and paper), it displays relevant phenomena (internal heat conduction, melting, vaporization, thermal decomposition, and gas phase reaction of the decomposition products). Unlike the other materials, however, it is non-sooting and has simple and well-known chemical kinetic pathways for its combustion. Hence it should prove to be much more useful for numerical modeling of surface combustion than the complex fuels typically used. We have performed the first exploratory tests of trioxane combustion in the counterflow configuration to determine its potential as a surrogate solid fuel which allows detailed modeling. The experiments were performed in the spring and summer of 1998 at the National Institute of Standards and Technology in Gaithersburg, MD, and at NASA-GRC in Cleveland. Using counterflow flames at 1-g, we measured the fuel consumption rate and the extinction conditions with added N2 in the air; at mg conditions, we observed the ignition characteristics and flame shape from video images. We have performed numerical calculations of the flame structure, but these are not described here due to space limitations. This paper summarizes some burning characteristics of trioxane relevant to its use for studying flame spread and fire suppression.

Linteris, Gregory T.↗

Shuttle Fire Tests Are Radiant

Flame spreading is a phenomenon familiar to everyone who has witnessed an accidental fire. Yet, because of the complexity of the physical and chemical processes that are involved, the theoretical understanding of fires and flame spreading is a relatively new science. Flames spread along solid materials in a process where heat from the flames vaporizes the fuel just ahead of the moving flame. The vaporized fuel mixes with oxygen from the air and reacts chemically with it, producing the flame. On Earth, the spread rate of the flame is directly affected by the rate at which the fuel and oxygen are mixed with the help of buoyant convection.

Olson, Sandra L.↗

MOOSE ProbML: Parallelizable Probabilistic Machine Learning and Uncertainty Quantification Capabilities

The Multiphysics Object Oriented Simulation Environment (MOOSE) is a widely used open- source finite element software for performing multiphysics multiscale simulations in a massively parallel fashion. Recently, the computational team at Idaho National Laboratory (INL) has implemented Probabilistic Machine Learning (ProbML) capabilities in MOOSE—in a parallelized fashion—and enable active learning with large-scale computational models for tasks such as surrogate model development, scale bridging, forward/inverse uncertainty quantification (UQ), Bayesian optimization, etc. This presentation summarizes these developments in MOOSE along with demonstrations on several real applications relevant to nuclear energy. At the fundamental level, samplers like Monte Carlo/Latin Hypercube, variance reduction, parallelized Markov Chain Monte Carlo (MCMC) support uncertainty propagation in both forward and inverse settings. These samplers can be integrated with the Gaussian processes (GP) suite in MOOSE, which offer several variants like scalar GPs, multi-output GPs, and deep GPs, to enable active learning. These GPs can be tuned using gradient-based optimization methods like Adam and its variants or gradient-free methods like the elliptical slice sampler (a variant of MCMC adept under Gaussian settings) for more complex covariance kernels or likelihoods whose gradient computations can be cumbersome. A variety of batch acquisition functions permit parallelized evaluation of the computational model and support different learning objectives with high efficiency like Bayesian inference, global surrogate development, optimization, etc. Furthermore, libtorch integration supports training, evaluation, and re-training of neural networks and other complex machine learning models in active learning settings. The impacts of these developments are shown on several real applications: (1) nuclear fuel inverse UQ and model inadequacy assessment using the Kennedy O’Hagan framework; (2) uncertainty aware surrogate modeling for additive manufacturing to predict field quantities; (3) nuclear reactor rare events analysis; and (4) complex fluid flow prediction using a global surrogate with quantified prediction uncertainty. Finally, the outlook of MOOSE ProbML is discussed for both outer-loop and inner-loop computations in the broad view to accelerate fuels and materials qualification, address gaps in knowledge and data, and assess new reactor/fuel systems.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

The Role of Structural Dynamics and Testing in the Shuttle Flowliner Crack Investigation

During a normal inspection of the main propulsion system at Kennedy Space Center, small cracks were noticed near a slotted region of a gimbal joint flowliner located just upstream from one of the Space Shuttle Main Engines (SSME). These small cracks sparked an investigation of the entire Space Shuttle fleet main propulsion feedlines. The investigation was initiated to determine the cause of the small cracks and a repair method that would be needed to return the Shuttle fleet back to operation safely. The cracks were found to be initiated by structural resonance caused by flow fluctuations from the SSME low pressure fuel turbopump interacting with the flowliner. The pump induced backward traveling wakes that excited the liner and duct acoustics which also caused the liner to vibrate in complex mode shapes. The investigation involved an extensive effort by a team of engineers from the NASA civil servant and contractor workforce with the goal to characterize the root cause of the cracking behavior of the fuel side gimbal joint flowliners. In addition to working to identify the root cause, a parallel path was taken to characterize the material properties and fatigue capabilities of the liner material such that the life of the liners could be ascertained. As the characterization of the material and the most probable cause matured, the combination of the two with pump speed restrictions provided a means to return the Shuttle to flight in a safe manner. This paper traces the flowliner investigation results with respect to the structural dynamics analysis, component level testing and hot-fire flow testing on a static testbed. The paper will address the unique aspects of a very complex problem involving backflow from a high performance pump that has never been characterized nor understood to such detail. In addition, the paper will briefly address the flow phenomena that excited the liners, the unique structural dynamic modal characteristics and the variability of SSME operation which has ultimately ensured the safe and reliable operation of the shuttle main engines for each flight.

Frady, Gregory P.↗

Heat Transfer and Thermal Stability Research for Advanced Hydrocarbon Fuel Technologies

In recent years there has been increased interest in the development of a new generation of high performance boost rocket engines. These efforts, which will represent a substantial advancement in boost engine technology over that developed for the Space Shuttle Main Engines in the early 1970s, are being pursued both at NASA and the United States Air Force. NASA, under its Space Launch Initiative s Next Generation Launch Technology Program, is investigating the feasibility of developing a highly reliable, long-life, liquid oxygen/kerosene (RP-1) rocket engine for launch vehicles. One of the top technical risks to any engine program employing hydrocarbon fuels is the potential for fuel thermal stability and material compatibility problems to occur under the high-pressure, high-temperature conditions required for regenerative fuel cooling of the engine combustion chamber and nozzle. Decreased heat transfer due to carbon deposits forming on wetted fuel components, corrosion of materials common in engine construction (copper based alloys), and corrosion induced pressure drop increases have all been observed in laboratory tests simulating rocket engine cooling channels. To mitigate these risks, the knowledge of how these fuels behave in high temperature environments must be obtained. Currently, due to the complexity of the physical and chemical process occurring, the only way to accomplish this is empirically. Heated tube testing is a well-established method of experimentally determining the thermal stability and heat transfer characteristics of hydrocarbon fuels. The popularity of this method stems from the low cost incurred in testing when compared to hot fire engine tests, the ability to have greater control over experimental conditions, and the accessibility of the test section, facilitating easy instrumentation. These benefits make heated tube testing the best alternative to hot fire engine testing for thermal stability and heat transfer research. This investigation used the Heated Tube Facility at the NASA Glenn Research Center to perform a thermal stability and heat transfer characterization of RP-1 in an environment simulating that of a high chamber pressure, regenerative cooled rocket engine. The first step in the research was to investigate the carbon deposition process of previous heated tube experiments by performing scanning electron microscopic analysis in conjunction with energy dispersive spectroscopy on the tube sections. This analysis gave insight into the carbon deposition process and the effect that test conditions played in the formation of deleterious coke. Furthermore, several different formations were observed and noted. One other crucial finding of this investigation was that in sulfur containing hydrocarbon fuels, the interaction of the sulfur components with copper based wall materials presented a significant corrosion problem. This problem in many cases was more life limiting than those posed by the carbon deposition process. The results of this microscopic analysis was detailed and presented at the December 2003 JANNAF Air-Breathing Propulsion Meeting as a Materials Compatibility and Thermal Stability Analysis of common Hydrocarbon Fuels (reference 1).

DeWitt, Kenneth↗

Understanding the effect of crystal anisotropy on grain growth, texturing and transport via the orthorhombic ?-U system [Slides]

The alpha phase of uranium exhibits the orthorhombic crystal structure, resulting in significant physical property anisotropy. These complex properties make the material challenging to work with in engineering settings but provide a rich arena to investigate the fundamental, multi-scale effects of anisotropy on physical behaviors such as grain growth and microstructure evolution under irradiation. We apply molecular dynamics and phase field modeling to study mass transport and grain growth in alpha-uranium. We characterize the mobilities of crystalline defects and the interfacial energy, and We find that the grain boundary energy is highly variable depending on the interface structure and that the relative rates of defect transport change with temperature. We also find that anisotropic thermal expansion has a significant impact on grain growth kinetics and texture development. Our results are used to explain experimental observations and to provide a basis for further hypotheses into the complex physical behavior of alpha-uranium.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Joining and Integration of Silicon Carbide-Based Materials for High Temperature Applications

Advanced joining and integration technologies of silicon carbide-based ceramics and ceramic matrix composites are enabling for their implementation into wide scale aerospace and ground-based applications. The robust joining and integration technologies allow for large and complex shapes to be fabricated and integrated with the larger system. Potential aerospace applications include lean-direct fuel injectors, thermal actuators, turbine vanes, blades, shrouds, combustor liners and other hot section components. Ground based applications include components for energy and environmental systems. Performance requirements and processing challenges are identified for the successful implementation different joining technologies. An overview will be provided of several joining approaches which have been developed for high temperature applications. In addition, various characterization approaches were pursued to provide an understanding of the processing-microstructure-property relationships. Microstructural analysis of the joint interfaces was conducted using optical, scanning electron, and transmission electron microscopy to identify phases and evaluate the bond quality. Mechanical testing results will be presented along with the need for new standardized test methods. The critical need for tailoring interlayer compositions for optimum joint properties will also be highlighted.

Ceramic Matrix Composites↗

Computational Approaches for Clean Energy Materials

Currently, 80% of the global final energy consumption occurs in form of fuels and only 20% as electricity. On the other hand, renewable energy additions come almost exclusively in the form of electricity (dominantly photovoltaics and wind). Thus, a successful energy transition will require enormous growth in renewables, sufficient to convert excess electricity into fuels, as well as the development of non-electricity based solar fuel technologies. As much as photovoltaic capacities have grown over the past 20 years, it is far from clear that current technologies and materials are up to the task to grow from here by yet another factor 100 until 2050. Therefore, sustained research efforts on emerging inorganic semiconductors for solar electricity and fuels are essential for facing the double challenge of climate change and energy security. Computational materials science can make important contributions, guiding and supporting research activities through both materials search and discovery and through detailed studies that help to develop a mechanistic understanding of materials performance and bottlenecks. This presentation will highlight three recent computational projects with relevance for photovoltaics and solar fuels (1) Defect graph neural networks (dGNN) for materials discovery in solar thermochemical hydrogen (STCH) [1]. The dGNN approach facilitates broad and fast materials screening for defect properties. (2) Modeling highly off-stoichiometric systems by evaluating the free energy of defect interaction [2]. This approach allows quantitative prediction of H2 production in complex STCH oxides. (3) First-principles atomic structure prediction for interfaces [3]. This work showed how an atomically thin CdCl2 interlayer phase enables in principle ideal electron transport across the incommensurate SnO2/CdTe interface. [1] M.D. Witman, A. Goyal, T. Ogitsu, A.H. McDaniel, S. Lany, Nat. Comput. Sci. (2023). https://doi.org/10.1038/s43588-023-00495-2. [2] A. Goyal, M.D. Sanders, R.P. O'Hayre, S. Lany, PRX Energy 3, 013008 (2024). https://doi.org/10.1103/PRXEnergy.3.013008. [3] A. Sharan, M. Nardone, D. Krasikov, N. Singh, S. Lany, Appl. Phys. Rev. 9, 041411 (2022). https://doi.org/10.1063/5.0104008.

density functional theory↗

A Novel Manufacturing Process of Lightweight Automotive Seats: Integration of Additive Manufacturing and Reinforced Polymer Composite

Lightweight automotive seats offer multiple benefits to original equipment manufacturers in terms of cost savings from various aspects, including less material usage, more integrated processes, and compliance with Corporate Average Fuel Economy Standards. Original equipment manufacturers have been focusing on innovative ways to produce light weight automotive seats. The commercially available automotive seats are currently made of multiple metal components combined through welding and fasteners. The use of additive manufacturing and composite structures is particularly useful for light weighting the automotive components. Additive manufacturing (AM) offers multiple advantages over traditional manufacturing processes such as freedom of design thereby enabling complex structural geometries, mass customization and waste minimization, and control over the fiber alignment through deposition in a predetermined pattern. Combining metal inserts with polymer composites through a novel manufacturing process allows design of lightweight and high-performance materials for automotive components.

99 GENERAL AND MISCELLANEOUS↗