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DOE OSTI2020

Embedding physics domain knowledge into a Bayesian network enables layer-by-layer process innovation for photovoltaics

Process optimization of photovoltaic devices is a time-intensive, trial-and-error endeavor, which lacks full transparency of the underlying physics and relies on user-imposed constraints that may or may not lead to a global optimum. Herein, we demonstrate that embedding physics domain knowledge into a Bayesian network enables an optimization approach for gallium arsenide (GaAs) solar cells that identifies the root cause(s) of underperformance with layer-by-layer resolution and reveals alternative optimal process windows beyond traditional black-box optimization. Our Bayesian network approach links a key GaAs process variable (growth temperature) to material descriptors (bulk and interface properties, e.g., bulk lifetime, doping, and surface recombination) and device performance parameters (e.g., cell efficiency). For this purpose, we combine a Bayesian inference framework with a neural network surrogate device-physics model that is 100× faster than numerical solvers. With the trained surrogate model and only a small number of experimental samples, our approach reduces significantly the time-consuming intervention and characterization required by the experimentalist. As a demonstration of our method, in only five metal organic chemical vapor depositions, we identify a superior growth temperature profile for the window, bulk, and back surface field layer of a GaAs solar cell, without any secondary measurements, and demonstrate a 6.5% relative AM1.5G efficiency improvement above traditional grid search methods.

14 SOLAR ENERGY↗

NASA NTRS1996

High Energy Density Matter for Rocket Propulsion

The objective of the High Energy Density Matter (HEDM) program is to identify, develop, and exploit high energy atomic and molecular systems as energetic sources for rocket propulsion applications. It is a high risk, high payoff program that incorporates both basic and applied research, experimental and theoretical efforts, and science and engineering efforts. The HEDM program is co-sponsored by the Air Force Office of Scientific Research (AFOSR) and the Phillips Laboratory (PURKS). It includes both in-house and contracted University/Industry efforts. Technology developed by the HEDM program offers the opportunity for significant breakthroughs in propulsion system capabilities over the current state-of-the-art. One area of great interest is the use of cryogenic solids to increase the density of the propellant and to act as a stable matrix for storage of energetic materials. No cryogenic solid propellant has ever been used in a rocket, and there remain engineering challenges to such a propellant. However, these solids would enable a wide class of highly energetic materials by providing an environment that is at very low temperatures and is a physical barrier to recombination or energy loss reactions. Previous to our experiments only hydrogen atoms had been isolated in solid hydrogen. To date we have succeeded in trapping B, Al, Li, N, and Mg atoms in solid H2. Small molecules, such as B2 and LiB, are also of interest. Current efforts involve the search for new energetic small molecules, increasing free radical concentrations up to 5 mole percent, and scale-up for propulsion testing.

Carrick, Patrick G.↗

DOE OSTI2024

Accelerating the design of lattice structures using machine learning

Lattices remain an attractive class of structures due to their design versatility; however, rapidly designing lattice structures with tailored or optimal mechanical properties remains a significant challenge. With each added design variable, the design space quickly becomes intractable. To address this challenge, research efforts have sought to combine computational approaches with machine learning (ML)-based approaches to reduce the computational cost of the design process and accelerate mechanical design. While these efforts have made substantial progress, significant challenges remain in (1) building and interpreting the ML-based surrogate models and (2) iteratively and efficiently curating training datasets for optimization tasks. Here, we address the first challenge by combining ML-based surrogate modeling and Shapley additive explanation (SHAP) analysis to interpret the impact of each design variable. We find that our ML-based surrogate models achieve excellent prediction capabilities (R 2 > 0.95) and SHAP values aid in uncovering design variables influencing performance. We address the second challenge by utilizing active learning-based methods, such as Bayesian optimization, to explore the design space and report a 5 × reduction in simulations relative to grid-based search. Collectively, these results underscore the value of building intelligent design systems that leverage ML-based methods for uncovering key design variables and accelerating design.

36 MATERIALS SCIENCE↗

NASA NTRS1992

Machine Learning Techniques in Optimal Design

Many important applications can be formalized as constrained optimization tasks. For example, we are studying the engineering domain of two-dimensional (2-D) structural design. In this task, the goal is to design a structure of minimum weight that bears a set of loads. A solution to a design problem in which there is a single load (L) and two stationary support points (S1 and S2) consists of four members, E1, E2, E3, and E4 that connect the load to the support points is discussed. In principle, optimal solutions to problems of this kind can be found by numerical optimization techniques. However, in practice [Vanderplaats, 1984] these methods are slow and they can produce different local solutions whose quality (ratio to the global optimum) varies with the choice of starting points. Hence, their applicability to real-world problems is severely restricted. To overcome these limitations, we propose to augment numerical optimization by first performing a symbolic compilation stage to produce: (a) objective functions that are faster to evaluate and that depend less on the choice of the starting point and (b) selection rules that associate problem instances to a set of recommended solutions. These goals are accomplished by successive specializations of the problem class and of the associated objective functions. In the end, this process reduces the problem to a collection of independent functions that are fast to evaluate, that can be differentiated symbolically, and that represent smaller regions of the overall search space. However, the specialization process can produce a large number of sub-problems. This is overcome by deriving inductively selection rules which associate problems to small sets of specialized independent sub-problems. Each set of candidate solutions is chosen to minimize a cost function which expresses the tradeoff between the quality of the solution that can be obtained from the sub-problem and the time it takes to produce it. The overall solution to the problem, is then obtained by solving in parallel each of the sub-problems in the set and computing the one with the minimum cost. In addition to speeding up the optimization process, our use of learning methods also relieves the expert from the burden of identifying rules that exactly pinpoint optimal candidate sub-problems. In real engineering tasks it is usually too costly to the engineers to derive such rules. Therefore, this paper also contributes to a further step towards the solution of the knowledge acquisition bottleneck [Feigenbaum, 1977] which has somewhat impaired the construction of rulebased expert systems.

Cerbone, Giuseppe↗

DOE OSTI2021

nEXO Team Active Georgetown University: Systems Integration and Test

The nEXO experiment is the “next” tonne-scale enriched xenon observatory which will be fielded deep underground to search for neutrinoless double-beta decay. The observation of neutrinoless double-beta decay is important to the low-energy physics community, and confirmation of the phenomenon will allow physicists to extend current physics models and propose new theories for the evolution of matter in our universe.

42 ENGINEERING↗

DOE OSTI2024

Finding ways to reduce nuclear waste: searching for the unknown one step at a time

In my home country, Venezuela, research has been stagnant. Due to the political turmoil and the crisis, many educated people have left the country in search for a better life. This has caused a deficit in any technological and scientific advances, making Venezuela one of the first South American countries to have its rate of publications decline by 29% in 2013. Currently, Venezuela lacks the infrastructure and the means to keep up with the research progress as compared to other countries in South America, such as Brazil. Since coming to the United States (US), and currently working for a national laboratory, the active research environment endorses a wide range of careers and engineering programs that allow researchers to thrive at any given field. Researchers have access to funds and tools to succeed in developing materials for the future. There are 17 national laboratories in the US, and all of these have a different research focus/objective. As examples, Los Alamos National Laboratory and Sandia National Laboratory focus is on national homeland security, weapon science, radiation effects, among others. Argonne National Laboratory focuses on nuclear energy, energy storage, high performance computing, etc. At Idaho National Laboratory (INL) the research focuses on innovating nuclear energy and clean energy resources, critical infrastructure materials, along with fuel cycle solutions to manage, dispose and find ways to recycle current and future radiological waste. Compared to other national laboratories, INL focuses slightly more on applied processes and how nuclear energy can be innovated to next reactor design and technologies. The research being conducted at INL made me apply for a Seaborg distinguished postdoctoral position. For the position itself, the researcher must submit a proposal related to actinide chemistry on a research field area. In this position, 50% of my time will be focused on my own proposal. The proposal that I am working on is focused on the innovation of nuclear energy and fuel cycle recycling, which is why I was mainly interested on working at this national laboratory. To give a bit more context of what my proposal is about, a little bit of background is necessary: After the nuclear fuel (UO2) is used in a reactor, the fuel matrix is then characterized by various fission products (FP). Among these FP (including rare earth elements, alkali/alkaline earths, and actinides), many can potentially be recovered through nuclear reprocessing technologies. In pyroprocessing, the used nuclear fuel undergoes electrochemical dissolution into a molten chloride salt mixture in an electrorefiner. Initially, uranium is reduced onto an inert cathode by applied potentials. However, numerous remaining FPs accumulate in the melt and pose challenges for recovery by an inert electrode, particularly the rare earth elements (e.g., Nd, Gd, Pr, Sm) due to their multivalent oxidation states and tendencies toward side reactions, leading to their dissolution in the electrolyte. These recovery challenges result in inefficiencies and necessitate the continual discarding of the molten chloride salt, thereby generating additional waste. Furthermore, the presence of rare earth elements and other fission products in the molten salt electrolyte alters its physical and chemical properties, affecting both uranium recovery efficiency and the longevity of the molten chloride salt. To improve the recovery efficiency of the FP, specifically rare earth elements, I am investigating the fundamental interactions between rare earth elements in the molten chloride salt and their metallic form. The kinetic pathways and the chemical reactions of these elements will give insights on how the recovery efficiency can be improved. The interactions and speciation of these elements are being studied by spectro-electrochemistry at high temperature environments in quartz and other ceramic materials (e.g., alumina crucibles). Some of the challenges I am facing specifically relates the reactivity of some of these elements with different glass and crucible materials. Although my research focuses on fundamental science, it will benefit the applied process by generating new scientific knowledge and closing the gap for an efficient recycling of the waste: one step at a time.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS2019

Mars Exploration Rover Opportunity End of Mission Report

The Mars Exploration Rover (MER) Opportunity landed on Meridiani Planum on 25 January 2004 for a prime mission designed to last three months (90 sols). After more than fourteen years operating on the surface of Mars, the last communication from Opportunity occurred on sol 5111 (10 June, 2018) when a major dust storm reduced power on the solar panels to the point where further communications were not possible. Following the cessation of the dust storm several weeks later, the MER project radiated over 1000 commands to Mars in an attempt to elicit a response from the rover. Attempts were made utilizing the Deep Space Network X-Band and UHF relay via both Mars Odyssey and the Mars Reconnaissance Orbiter. Search and recovery efforts concluded on 12 February, 2019. It is the MER project’s assessment that the environmental window in which it would be most probable to recover Opportunity had passed by that time and that the rover would succumb to the extreme environmental conditions experienced during a winter on Mars. This report summarizes the major science accomplishments throughout the fourteen years of this mission, with a detailed focused on recent science accomplishments during the last extended mission (EM-11). This report also describes the mission engineering accomplishments and specific actions taken during the attempt to recover the vehicle after communications were lost during the major dust storm.

Callas, John L.↗

NASA NTRS1986

Investigation of chord ratio, stagger, decalage angle, and flap angle for dual wing configurations

Aerodynamical closely coupled dual wing configurations of unequal chords are investigated for medium speed general aviation applications. Vortex panel and momentum boundary layer analysis are utilized for the two-dimensional predictions. A multi-surface vortex lattice method is used for the three-dimensional predictions. In the process of searching for the highest lift to drag ratio upper airfoil to lower airfoil chord ratios, both greater than and less than one, are investigated in terms of stagger, decalage angle, and gap. With the optimum chord ratio, at the optimum stagger and gap, proper spanwise decalage distribution is shown to yield the lowest two dimensional drag results. Various wing taper ratios and wing twists are investigated to increase wing efficiency. Comparisons are made between optimized dual and optimized single wing configurations both with the same fuselage, stabilator surfaces, engines, payload, and fuel. The dual wing configuration is shown to have significantly less drag and hence longer range than the conventional single wing configuration.

Selberg, B. P.↗

DOE OSTI2023

Rapid design of top-performing metal-organic frameworks with qualitative representations of building blocks

Abstract Data-driven materials design often encounters challenges where systems possess qualitative (categorical) information. Specifically, representing Metal-organic frameworks (MOFs) through different building blocks poses a challenge for designers to incorporate qualitative information into design optimization, and leads to a combinatorial challenge, with large number of MOFs that could be explored. In this work, we integrated Latent Variable Gaussian Process (LVGP) and Multi-Objective Batch-Bayesian Optimization (MOBBO) to identify top-performing MOFs adaptively, autonomously, and efficiently. We showcased that our method (i) requires no specific physical descriptors and only uses building blocks that construct the MOFs for global optimization through qualitative representations, (ii) is application and property independent, and (iii) provides an interpretable model of building blocks with physical justification. By searching only ~1% of the design space, LVGP-MOBBO identified all MOFs on the Pareto front and 97% of the 50 top-performing designs for the CO 2 working capacity and CO 2 /N 2 selectivity properties.

36 MATERIALS SCIENCE↗

DOE OSTI2021

The Event Detection System in the NEXT-White Detector

This article describes the event detection system of the NEXT-White detector, a 5 kg high pressure xenon TPC with electroluminescent amplification, located in the Laboratorio Subterráneo de Canfranc (LSC), Spain. The detector is based on a plane of photomultipliers (PMTs) for energy measurements and a silicon photomultiplier (SiPM) tracking plane for offline topological event filtering. The event detection system, based on the SRS-ATCA data acquisition system developed in the framework of the CERN RD51 collaboration, has been designed to detect multiple events based on online PMT signal energy measurements and a coincidence-detection algorithm. Implemented on FPGA, the system has been successfully running and evolving during NEXT-White operation. The event detection system brings some relevant and new functionalities in the field. A distributed double event processor has been implemented to detect simultaneously two different types of events thus allowing simultaneous calibration and physics runs. This special feature provides constant monitoring of the detector conditions, being especially relevant to the lifetime and geometrical map computations which are needed to correct high-energy physics events. Other features, like primary scintillation event rejection, or a double buffer associated with the type of event being searched, help reduce the unnecessary data throughput thus minimizing dead time and improving trigger efficiency.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1992

An expert system for diagnosing environmentally induced spacecraft anomalies

A new rule-based, machine independent analytical tool was designed for diagnosing spacecraft anomalies using an expert system. Expert systems provide an effective method for saving knowledge, allow computers to sift through large amounts of data pinpointing significant parts, and most importantly, use heuristics in addition to algorithms, which allow approximate reasoning and inference and the ability to attack problems not rigidly defined. The knowledge base consists of over two-hundred (200) rules and provides links to historical and environmental databases. The environmental causes considered are bulk charging, single event upsets (SEU), surface charging, and total radiation dose. The system's driver translates forward chaining rules into a backward chaining sequence, prompting the user for information pertinent to the causes considered. The use of heuristics frees the user from searching through large amounts of irrelevant information and allows the user to input partial information (varying degrees of confidence in an answer) or 'unknown' to any question. The modularity of the expert system allows for easy updates and modifications. It not only provides scientists with needed risk analysis and confidence not found in algorithmic programs, but is also an effective learning tool, and the window implementation makes it very easy to use. The system currently runs on a Micro VAX II at Goddard Space Flight Center (GSFC). The inference engine used is NASA's C Language Integrated Production System (CLIPS).

Rolincik, Mark↗

NASA NTRS2024

Transitioning Sixty Years of NASA Spacesuit Knowledge Capture Lessons Learned to Searchable Knowledge Transfer Databases

Sixty years of spacesuit knowledge capture and lessons learned by spacesuit subject matter experts are documented on videos and presentations and archived with the NASA Engineering and Safety Center (NESC) Academy. The NESC Academy is a web-based platform that hosts online courses by technical experts. A process is underway to transition these decades of lessons learned from the U.S. Spacesuit Knowledge Capture Program Library into more quicky searchable databases and to proactively provide this information to those working on spacesuit projects. Hundreds of lessons learned from Project Mercury, Gemini, Apollo, Apollo- Soyuz Test Project, Skylab, Space Shuttle, International Space Station, and Artemis have been captured in a format that can be quickly searched, enabling users to find information directly applicable to their needs. Transitioning this information to a NASA wiki page will further enhance search and retrieval of data immediately useful to users. This paper provides information about how the lessons learned were determined and how to access them.

spacesuit↗

NASA NTRSDate not supplied

Transitioning Sixty Years of NASA Spacesuit Knowledge Capture Lessons Learned to Searchable Knowledge Transfer Databases

spacesuit↗

DOE OSTI2020

A Nonlocal-Gradient Descent Method for Inverse Design in Nanophotonics

Local-gradient-based optimization approaches lack nonlocal exploration abilityrequired for escaping from local minima when searching non-convex landscapes.A directional Gaussian smoothing (DGS) approach was recently proposed in [29]and used to define a truly nonlocal gradient, referred to as the DGS gradient, inorder to enable nonlocal exploration in high-dimensional black-box optimization.Promising results show that replacing the traditional local gradient with the nonlocalDGS gradient can significantly improve the performance of gradient-based methodsin optimizing highly multi-modal loss functions. However, the current DGS methodis designed for unbounded and uncontrained optimization problems, making itinapplicable to real-world engineering optimization problems where the tuningparameters are often bounded and the loss function is usually constrained byphysical processes. In this work, we propose to extend to the DGS approachto the constrained inverse design framework in order to find better optima ofmulti-modal loss functions. A series of adaptive strategies for smoothing radiusand learning rate updating are developed to improve the computational efficiencyand robustness. Our methodology is demonstrated by an example of designing ananoscale wavelength demultiplexer, and shows superior performance compared tothe state-of-the-art approaches. By incorporating volume constraints, the optimizeddesign achieves an equivalently high performance but significantly reduces theamount of material usage.

Bi, Sirui↗

NASA NTRS2018

EVA Swab Tool to Support Planetary Protection and Astrobiology Evaluations

When we send humans to search for life on other planets, we'll need to know what we brought with us versus what may already be there. To ensure our crewed systems meet planetary protection requirements-and to protect our science from human contamination-we'll need to assess whether microorganisms may be leaking or venting from our spacecraft. Microbial sample collection outside of a pressurized spacecraft is complicated by temperature extremes, low pressures that preclude the use of laboratory standard (wetted) swabs, and operation either in bulky spacesuits or with robotic assistance. Engineers at the National Aeronautics and Space Administration (NASA) recently developed a swab kit for use in collecting microbial samples from the external surfaces of crewed spacecraft, including spacesuits. The Extravehicular Activity (EVA) Swab Kit consists of a single swab tool handle and an eight-canister sample caddy. The design team minimized development cost by re-purposing a heritage Space Shuttle tile repair handle that was designed to quickly snap into different tool attachments by engaging a mating device in each attachment. This allowed the tool handle to snap onto a fresh swab attachment much like popular shaving razor handles can snap onto a disposable blade cartridge. To disengage the handle from a swab, the user performs two independent functions, which can be done with a single hand. This dual operation mitigates the risk that a swab will be inadvertently released and lost in microgravity. Each swab attachment is fitted with commercially available foam swab tips, vendor-certified to be sterile for Deoxyribonucleic Acid (DNA). A microbial filter installed in the bottom of each sample container allows the container to outgas and repressurize without introducing microbial contaminants to internal void spaces. Extensive ground testing, post-test handling, and sample analysis confirmed the design is able to maintain sterile conditions as the canister moves between various pressure environments. To further minimize cost, the design team acquired extensive ground test experience in a relevant flight environment by piggy-backing onto suited crew training runs. These training runs allowed the project to validate tool interfaces with pressurized EVA gloves and collect user feedback on the tool design and function, as well as characterize baseline microbial data for different types of spacesuits. In general, test subjects found the EVA Swab Kit relatively straightforward to operate, but identified a number of design improvements that will be incorporated into the final design. Although originally intended to help characterize human forward contaminants, this tool has other potential applications, such as for collecting and preserving space-exposed materials to support astrobiology experiments.

Rucker, Michelle A.↗

DOE OSTI2022

Engineering magnetic topological insulators in Eu 5 M 2 X 6 Zintl compounds

Magnetic topological insulators provide a prominent material platform for quantum anomalous Hall physics and axion electrodynamics. However, the lack of material realizations with cleanly gapped surfaces hinders technological utilization of these exotic quantum phenomena. Here, using the Zintl concept and the properties of nonsymmorphic space groups, we computationally engineer magnetic topological insulators. Specifically, we explore Eu 5 M 2 X 6 (M=metal, X=pnictide) Zintl compounds and find that Eu 5 Ga 2 Sb 6 , Eu 5 Tl 2 Sb 6 , and Eu 5 In 2 Bi 6 form stable structures with nontrivial Z 2 indices. We also show that epitaxial and uniaxial strain can be used to control the Z 2 index and the bulk energy gap. Lastly, we discuss experimental progress towards the synthesis of the proposed candidates and provide insights that can be used in the search for robust magnetic topological insulators in Zintl compounds.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

NASA NTRS2005

Monitoring the Intrinsic Absorption Complex Toward RX J1230.8+115

There is a very prominent intrinsic absorption complex in the spectrum of the quasar RX J1230.8+115. It was diagnosed as intrinsic due to partial covering of the quasar by the absorber, which can only happen for material very near to the quasar. Measuring a variability timescale for the absorption would allow us to place a more stringent constraint on the distance of the absorber from the central engine. Furthermore, understanding the variability and covering factors in different transitions can help to identify if it is due to changes in the ionizing source or transverse motion of the absorber. The OVI doublet is covered in the FUSE wavelength range. Unfortunately, our initial target, RX J1230.8+0115 could not be observed due to the failure of the first reaction wheel. We determined that another target, H 1821+643, could be observed and would satisfy similar science goals, understanding intrinsic narrow absorption line systems. Our specific goal for that target was to search for Ne VI11 absorption from the associated absorber. This observation was attempted, but the counts in the Sic channel, where the absorption was expected to lie, were too low to satisfy our science goal. This was, at least in part, due to a misalignment of the SiC mirrors. Because of this problem, more time was awarded. However, even the extra time was too little. It appears that the quasar may be too faint to properly align all the mirrors. So with disappointment, I report that we were not able to accomplish our science goals for this program. The funds were used to support my work with a graduate student, Jie Ding, to evaluate possible replacement targets once we learned that Rx J1230.8+115 would not be observable. We considered the intrinsic NAL candidates that we could find through a partial coverage analysis of doublets in the STIS E140M and E230M quasar spectra taken from the HST archive. We then checked the flux in the FUSE wavelength range, and in most cases of interest it was found to be too low to satisfy our S/N requirement in the exposure time we had been awarded. We decided that H1821+643 was the best choice for this project, even though the associated absorber we would be studying might in fact originate in the cluster with the quasar and not in intrinsic gas. Part of the appeal of the target, was in fact the opportunity to consider this issue. Please do not hesitate to contact me if more detail is needed for this report. I found it difficult to write a satisfying report under the circumstance and am uncertain if I've provided the proper level of information.

Charlton, Jane↗

DOE OSTI2022

Survey of the Worldwide Supply Chain of Commodities Needed for a Quantum Technology Program

Quantum Information Science (QIS) is an emerging technology being pursued by fundamental science research groups worldwide, as well as commercial companies and government programs. There are a variety of QIS disciplines, including quantum computing, quantum sensing and quantum encryption. Some of the commodities needed for a robust quantum laboratory are particular to quantum phenomenon, but in general the equipment needed is similar to that needed for a typical high - technology lab (e.g. oscilloscopes, lasers, vacuum chambers, etc.). This study focuses on identifying commodities manufactured worldwide that would be needed for a robust quantum lab. The authors' own knowledge of needed equipment and primary vendors was used as a starting point, follow ed by extensive internet searching and utilization of buyer's guides to create a large spreadsheet of most of the components needed, the company offering the components, and country of manufacture. With this extensive spreadsheet, stakeholders can identify commodities that would be needed for a quantum lab oratory and potentially identify market choke points.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗