SEARCH · Engineering Papers

Results for “Employment”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 919 records · Page 51

All sources NASA NTRS DOE OSTI

DOE OSTI2022

Advanced Ceramic Membranes/Modules for Ultra Efficient Hydrogen (H2) Production/Carbon Dioxide (CO2) Capture for Coal-Based Polygeneration Plants: Fabrication, Testing, and CFD Modeling

Inorganic membrane-based systems are a promising technology for precombustion CO2 capture with simultaneous H2 production. State-of-the-art packages for high temperature and pressure service consist of multiple tube membrane bundles prepared in a "candle filter" configuration, in which the membrane tubes are open at one end and sealed at the other. This configuration is used for practical reasons, specifically the need to minimize problems due to thermal expansion mismatch between the ceramic tube bundle and the steel housing. However, the primary technical problem with the candle filter format for commercial-scale installations is the inability to purge the tube side (typically the permeate side), a feature that is crucial for high H2 recovery. In this study, the focus is to design and fabricate the first dual-end open full ceramic multiple tube membrane bundle that enables tube side (permeate) purge for gas separation applications. An additional key feature of this design is the simplified module layout, as the membrane bundles can be installed end-to-end with tube side (permeate) flow directly from one bundle to the next. This layout simplifies the membrane to housing seals and yields significant improvement in membrane packing density. Detailed focus areas in our studies include: (i) Materials development and preparation of the tube-to-tube sheet potting for the dual-ended bundle; (ii) the sealing and optimal module configuration design to minimize membrane stress upon module mounting; (iii) the demonstration, via the fabrication of CMS and Pd-alloy membranes supported on full-size, dual-ended ceramic support bundles, of the first example of a purgeable ceramic membrane and module; and (iv) development of a CFD model of the membrane module for calculation of feed flow distribution, and for use in scale-up, and capital cost estimating. The CFD model was validated using experimental data with the multi-tubular membrane system, employing He/N2 as a model gas mixture (surrogate for H2/CO2), and has been shown to be quite accurate. Employing the model, we are able to study the effects of operating pressure and temperature, feed and sweep gas flow rates, and the choice of membrane tube configuration on system performance.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2022

Inferring Water Content from Neutron Die-away Curves for Planetary Science Applications

Signatures of liquid water on planetary bodies may provide evidence for past, present, or future life elsewhere in the solar system. Multiple current and upcoming planetary science missions are prioritizing the search for water, using innovative technologies and creative algorithms. For this project, we explore the capabilities of an instrument similar to the Dragonfly spacecraft to map water content on the surface of Titan, the largest moon of Saturn. We simulate Dragonfly’s neutron observations for a variety of soil compositions and develop multiple techniques to extract water content from the resultant neutron data. Additionally, we supplement neutron observations with gamma spectroscopy in an attempt to further refine water content estimates. This work is part of a larger study to employ Gaussian process regression to estimate a map of water content along the surface of Titan. Using the estimated map, an algorithm based on prediction difference mapping is employed to optimally move multiple Dragonfly detectors around the surface of Titan, fully autonomously.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Fundamental Studies of Bifunctional Catalysts for Tandem Reactions

During the past few years of our funding from DOE Basic Energy Sciences, we have focused on the catalytic conversion of biomass-derived 5-hydroxymethyl furfural (HMF) as a platform molecule for sustainable synthesis of value-added chemicals. The combination of the diene and aldehyde functionalities in HMF enables catalytic production of acetalized HMF derivatives with diol or epoxy reactants to allow reversible synthesis of norcantharimide derivatives upon Diels-Alder reaction with maleimides. Whereas the electron-withdrawing nature of aldehyde group inhibits the reactivity of diene group in HMF to undergo Diels-Alder reactions with dienophiles, by converting the aldehyde group in HMF to an electron-donating hydroxyl group, HMF can append maleimide-based chemicals through Diels-Alder coupling. Acetalization of HMF not only produces an electron-rich diene for Diels-Alder reaction, but it also alters the reversibility of acetal formation and thereby allows for the controlled release of chemicals by hydrolysis. Therefore, we synthesized various norcantharimide derivatives from biomass-derived HMF by acetalization over an acid catalyst, Amberlyst-15, followed by Diels-Alder reaction with maleimide. The norcantharimides release the starting materials by retro Diels-Alder reaction that is triggered by acetal hydrolysis under acidic (≤pH 3) conditions. In subsequent work, we explored the synthesis and properties of functional polyurethanes and polyesters with tunable properties from biomass-derived (HMF)-Acetone-HMF (HAH) monomers. HAH can be selectively hydrogenated over Cu and Ru catalysts to produce partially-hydrogenated HAH (PHAH) and fully-hydrogenated HAH (FHAH). HAH contains functional groups, including hydroxyl, furan, enone, and ketone functionalities, that can be exploited to further tune the polymer properties. The π-electron conjugation between the enone and furan groups in HAH monomer stabilizes the furan group to prevent the uncontrolled degradation of furans during reactions, such as etherification. Therefore, HAH is a renewable monomer that can be used to synthesize polymers, having high molecular weight, symmetric functionalities, an inexpensive production price, and being derived from renewable resources without competition with food resources. We demonstrated the synthesis of functional polyurethanes and a renewable polyester from HAH-derived monomers, and 4,4’-methylenebis(phenyl isocyanate) (MDI). We showed that it is essential to be able to selective hydrogenate C=C double bonds in HAH to be able to achieve effective Diels Alder reactions of the furan ring. Therefore, we studied the hydrogenation at temperatures from 313 – 393 K of HAH over Pd, Ru, and Cu based catalysts. HAH was selectively hydrogenated to produce partially-hydrogenated monomers (PHAH) over Cu and Ru catalysts and to fully-hydrogenated HAH monomers (FHAH) over the Ru catalyst. Pd based catalysts yielded a mixture of partially and fully hydrogenated monomers. Reaction kinetics models were employed to quantify the kinetic behavior for hydrogenation over Ru, Cu, and Pd catalysts. A 5-step pathway exhibited over Pd and Ru catalysts consists of both series and parallel reaction steps, where HAH is both converted to fully hydrogenated products sequentially via series reactions of partially hydrogenated intermediates, as well as converted directly in parallel reactions to form the fully hydrogenated products. In contrast, a 3-step pathway over the Cu catalyst consists only of the consecutive reaction steps, where the final product was formed via series reactions of intermediate products. Additionally, reaction over the Cu catalyst did not hydrogenate the furan rings of the HAH molecule and yielded a different final product than those hydrogenation over Pd and Ru catalysts. Using the results from our detailed reaction kinetics studies, we developed universal conditions for the maximum production of the various hydrogenated products for both batch and plug flow systems. In subsequent work, we employed reaction schemes to optimize the yields of products from selective hydrogenations of HAH in isopropanol solvent and in the presence of liquid water. Reaction schemes consisting of 7, 9, and 11 steps were examined to describe the rates of formation of the observed products and reaction intermediates for hydrogenation of HAH over Ru and Pd catalysts, and a 3-step scheme was studied over Cu catalysts. Rate constants and activation energies were calculated using these reaction schemes, and we then apply these reaction schemes to explore the effects of water addition on the hydrogenation pathways. The effects of water addition to isopropanol (IPA) solvents on the hydrogenation of HAH were markedly different over Pd, Ru, and Cu catalysts. Over the Pd catalyst, the addition of water to IPA increased hydrogenation rates and promoted hydrogenation of furan rings. The addition of water to IPA yielded significant carbon losses over the Ru catalyst, and slowed hydrogenation steps over Cu, while significantly inhibiting hydrogenation of the ketone group. This behavior opened routes toward increased production rates of PHAH=O (a partially hydrogenated form of HAH containing a C=O bond), a product in which the diene groups of the furan rings were not hydrogenated. Addition of water also allowed increased feed concentrations of HAH that were previously not possible in pure IPA solvents.

09 BIOMASS FUELS↗

DOE OSTI2023

Studies of Conventional and ERL-Based Re-Circulator Electron Cooling for an Electron Ion Collider (Final Report)

The envisioned Electron Ion Collider will be comprised of a chain of accelerators, each employing electron cooling. Depending on the purpose, each accelerator will employ some form of electron cooling: conventional DC type, Energy Recovering Linac-based recirculator, or coherent electron cooling. Each electron cooling type has its own peculiarities that need to be studied, understood, and their performance optimized to maximize luminosity; these are the subjects of this project. In particular, we developed the first microscopic electron cooling modeling and simulation framework that was also benchmarked against experiment. We proved for the first time the feasibility of first principle, accurate and efficient electron cooling simulations with a minimal number of assumptions and approximations that match empirical studies.

43 PARTICLE ACCELERATORS↗

DOE OSTI2023

Molecular dynamics simulations of fission gas xenon (Xe) diffusion at UO 2 grain-boundaries (Rev.1)

The diffusivity of fission gas xenon (Xe) at UO 2 grain-boundaries is one of the most important parameters in mechanistic modeling of fission gas diffusion in UO 2 based nuclear fuels. In this report, we use molecular dynamics simulations to investigate the Xe diffusivity in UO 2 grain-boundaries, employing the many-body potential developed by Cooper, Rushton and Grimes for UO 2 . Three different types of grain-boundaries are investigated, twist Σ5, tilt Σ5, and a random grain-boundary. Diffusion activation energies in the range of 0.39 – 1.46 eV are obtained for the Xe diffusivity. Comparison to results for the uranium vacancy diffusivity from MD simulations employing the same methodology suggests a weak to moderate attractive Xe-uranium vacancy binding energy depending on the grain-boundary type.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Ultrasonic Characterization of Ethylene Vinyl Acetate (EVA) Crosslinking for Quality Assurance and Lamination Process Control (US-Xlink)

Module makers strive to cut lamination processing times to enhance production throughput and reduce costs. If overdone, this might lead to poor EVA quality due to incomplete EVA crosslinking and a large concentration of potentially harmful reactants. Those deficiencies are frequently missed during production quality testing as initially their impact on power output is small. Additionally, the crosslinking agent is frequently inhomogeneously dispersed across the EVA foils such that local destructive characterization procedures such as differential scanning calorimetry (DSC), Soxhlet extraction, swelling methods, or mechanical tests provide only a limited amount of information. However, these defects and inhomogeneities can become considerably more important during field operation, dramatically reducing long-term power yield, and increasing LCOE. Examples of typical long-term module degradation modes relating to poor lamination process conditions include cell breakage, corrosion of the metallization, delamination, and local quality deficiencies. To provide reliable material characterization in a manufacturing setting, we devised a non-destructive technology that uses ultrasound to evaluate the quality of interface adhesion and the degree of crosslinking. As a calibration reference, DSC measurements were employed. Although the potential of ultrasonic approaches for this purpose has already been noted, those previous methods were generally limited to local qualitative measurements. Furthermore, variations in EVA thickness and temperature had a substantial impact on them. The solution we propose solves these limitations by employing ultrasonic absorption rather than relying solely on sound velocity data.

14 SOLAR ENERGY↗

DOE OSTI2023

A Case Study of Tunable White LED Lighting with Networked Lighting Controls (Emory University Cognitive Empowerment Program)

Emory University and Georgia Institute of Technology (Georgia Tech) partnered to create the Charlie and Harriet Schaffer Cognitive Empowerment Program (CEP) facility in northeast Atlanta. Together with the funders they are building a program to help individuals experiencing mild cognitive impairment (MCI) to maintain their physical and cognitive health, and independence as long as possible. In addition to applying effective strategies and therapies, the two research groups are investigating the responses of the MCI members to treatments that involve acoustical conditions, exercise and movement, and lighting changes that may support retention or relearning of skills. Care partners and family members receive support and instruction to improve home and work life, promoting joy, purpose, and wellness in the family groups. The lighting system uses tunable-white LEDs, employing luminaires with both warm and cool-color emitters that can be dimmed separately to produce any white correlated color temperature (CCT) between 2700 K and 6500 K. All luminaires were dimmable to achieve subdued or lively surroundings for different treatments, time-of-day, and mood. A central networked digital control system was employed to allow tuning of multiple spaces together (for example, bright, cool morning light could be programmed for extra stimulation, or lighting in all spaces at the end of the day could be reduced in both light output and CCT to promote relaxation and not interfere with the melatonin cycle of occupants). Almost all spaces were equipped with individual room control of dimming and color temperature with touch screens to allow users to tune the lighting as desired, but each room’s controls could also be specially programmed through the server in case the research staff were investigating lighting settings on learning, for example. The server incorporates a timeclock, and it is able to send signals to switch off all lighting after occupancy hours, or enable occupancy sensors to control the lighting. The bulk of the construction work was completed in January 2020. It was clear from an initial walk-through that although the lighting system produced the expected high light level with low-glare qualities of light, that there were issues and inconsistencies to be resolved. These were noted in an initial punchlist visit and expected to be resolved when the tech representatives from the agency visited with the electrical contractor in the following few weeks. What followed was 2.5 years of identifying unexpected lighting performance in terms of light output, color, scheduling, and occupancy. This report documents the issues encountered in the effort to get the lighting and controls systems to operate as intended. It concludes with guidance for design professionals and manufacturers to help avoid problematic complexity in future projects.

42 ENGINEERING↗

DOE OSTI2023

Nuclear Power's Future Role in a Decarbonized U.S. Electricity System

This study explores the potential future role of nuclear energy in a decarbonized U.S. electricity system through a multi-model comparison approach. We employ four state-of-the-art CEMs with native and harmonized input assumptions, layered with different policy and technology trajectories. Comparing outputs across models, technology assumptions, and policy scenarios informs model understanding, interpretation, and development decisions. Under current policies, models differ in their projections for nuclear retirements, but nuclear power plants consistently run with high capacity factors and new builds only occur in scenarios with very low nuclear costs. String power sector carbon policies drive models to align in keeping existing nuclear capacity and employing nuclear plant flexibility, but they may not be enough to bring new nuclear capacity online in the absence of significant cost declines. Therefore, significant economic deployment of new nuclear capacity requires both a stringent electric sector CO2 policy and very low cost assumptions for new nuclear. While these scenarios should not be interpreted as predictions, they are informative for understanding differing model assessments of the relative competitiveness of nuclear energy under a range of policy and technology conditions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

FY22 Economic Impact Summary

In 2022, Idaho National Laboratory was one of the state’s top employers (sixth overall). INL directly employed a total of 5,460 positions, a 4% growth from the previous year. The large growth of Idaho’s economy between 2021 and 2022 means INL’s economic impact on the state has also deepened. Dollars that INL has brought into the state tend to stay and circulate longer, facilitating increased impacts and growth rates for the state. INL, along with the other 16 national labs housed under the Department of Energy (DOE), perform research focused on: nuclear energy, integrated energy systems (such Summary Results as microgrid, battery and environmental research), and national security. This study evaluates the economic activity of INL within the economy of Idaho. This study estimates the total economic impact generated by INL apart from any other DOE or Department of Defense operations within the state. Total operational impacts of INL in 2022 amounted to $\$ $3.38 billion in output, $\$ $2.42 billion in gross state product (GSP), and 16,445 jobs throughout Idaho.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2023

Cyberguardians and STEM Warriors (Final Technical Report (FTR))

In the past decade, solar power, with and without energy storage has become the fastest growing source of energy generation in the world. In the U.S., solar employment more than doubled from 105,145 jobs in 2011 to 255,037 jobs in 2021, four times faster than the U.S. job growth rate overall. These factors, combined with technology advancements, creates a skills gap that puts tremendous stress on society to deliver the workers to fill the open job requisitions. The Cyberguardians and STEM Warriors project (Cyberguardians) was designed to address the trained-worker shortage in the energy industry in three ways: 1) by developing educational curriculum that addresses DER technology changes; 2) by delivering curriculum to prospective workers, including military veterans and their families, via universities, community colleges, and vocational training outlets; and 3) introducing individuals who have completed training to employers that can hire them. Cyberguardians exceeded its curriculum goals by producing 27 academic units of university-accredited material (12 total courses) covering energy fundamentals, smart inverters, Distributed Energy Resource (DER) data communication, cybersecurity, standardization, certification, data analytics, and IEEE 1547 standard topics. The North American Board of Certified Energy Practitioners (NABCEP) also accredited the material for use in their credential program. Seven instructors were recruited and trained, and six academic institutions (University of California San Diego, State University of New York, North Carolina State University, Harper Community College, Green Village Academy, and the SunSpec Alliance) were enlisted, meeting program goals. All course material was published under the Creative Commons license and made available royalty free, thus providing a long-lasting public benefit. The program’s outreach program vastly exceeded program goals and incorporated the efforts of 13 outreach partners (11 of which are veteran focused), an advisory board representing 15 companies, webinars and 10’s of thousands of email messages sent to prospective students and hiring managers. Despite these efforts, the global pandemic depressed anticipated program participation by about a third. Still, a total of 396 students enrolled and 289 completed the courses and were accredited. The job applicant task achieved similar results (111 realized vs a 174 goal) but reported job placement was weaker at (9 realized vs. a 51 goal). The Cyberguardians program fills a critical void for cost-effective, royalty-free curriculum and training pertaining to DER technologies and cybersecurity that prospective energy workers must possess to be effective in the 21 st century. On this basis alone, the investment of taxpayer funds will pay dividends for years to come.

14 SOLAR ENERGY↗

DOE OSTI2023

Bright Solar Futures

The Bright Solar Futures (BSF) program addresses national climate and energy concerns by fulfilling the need for more solar technicians. About to enter its 5th year, the program demonstrates how the need for alternative energy can be addressed through a sustainable education and employment strategy. Career and Technical Education (CTE) Solar programs in the U.S. that train young adults for employment in the solar industry are in demand. Bright Solar Futures is designed to fill this local and national need as a replicable high school solar curriculum for CTE students.

14 SOLAR ENERGY↗

DOE OSTI2022

ARPA-E PNDIODES "PN Junctions by Ion Implantation" Project (Final Report)

Electricity accounts for nearly 40% of the energy generated in the United States, of which 65% is lost to electrical system inefficiency before reaching end-use sectors. Power electronics will play a growing role in this distribution and end-use, with up to 80% of electricity estimated to pass through power electronics from generation to consumption by 2030. This gives technical improvements in power electronics enormous potential to drive efficiency gains throughout the U.S. economy. Current Si-based power architectures including MOSFETs and IGBTs are limited by high losses, low switching frequency, and poor high-temperature performance. Given the material properties of GaN, devices can exhibit a given turn-on resistance and breakdown voltage with a minute fraction of the area of a Si device—all with higher switching speeds. While n-type doping of III-nitrides has reached a high level of maturity and integration into commercialized products, p-type doping presents distinct challenges that requires continued research. The success of the next generation of GaN-based power devices depends in large part on the ability to form selective-area p-type regions, which can be accomplished by ion implantation of the prevailing acceptor dopant, Mg. This approach is relatively inexpensive and is a fab-ready processing step for creation of current-generation power electronic devices including BJTs, IGBTs, and diode rectifiers. However, ion implantation induces lattice damage and creates point defects within the material, which negatively impacts dopant activation annealing. These forms of damage may be removed by high-temperature annealing, however short annealing time and higher pressures are required to prevent decomposition of the material. We approach this challenge through an innovative combination of approaches toward obtaining high-conductivity p-type GaN. By the novel employment of a gyrotron, a microwave source that can be shaped into a highly localized beam to dissipate very high power in a semiconductor target, a wafer of GaN can be annealed in short (<2 s) ‘pulses’ at temperatures of 1450 °C (2640 °F) to achieve p-type activation without appreciable surface degradation. The p-type activation of Mg-implanted GaN can be further aided by co-implantation with N, believed to enhance the removal of point defects that compensate the acceptors dopant. Elevation to such high temperatures for even a short time induces degradation of GaN-to overcome, we have implemented additional measures to retain high-quality crystalline GaN while removing implant damage and activating Mg dopant. A bilayer cap of AlN is deposited by a combination of chemical and physical vapor deposition to protect the GaN surface. To prevent decomposition of GaN loss of N during annealing, a custom vessel—to contain pressurized N while allowing injection of microwave energy—is employed. By detailed study of the interaction of various measures that are implemented to protect the sample surface (GaN), activate the implanted dopants, and mitigate damage of the lattice heating damage during annealing, we are able to achieve p-type GaN and observe recovery of the crystal and removal of substantial density of defects created during the implantation process.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Closing the loop between in-situ stress complexity and EGS fracture complexity

The goal of the project is to employ a combination of high-fidelity simulations and true-triaxial block fracturing tests at high temperature to explore the intricate relationship between in-situ stress and hydraulic fracture patterns and better characterize the in-situ stress at Utah FORGE. Laboratory experiments are used to validate numerical models and better understand the impact of various parameters (e.g., temperature, well orientation, stress, etc) on the hydraulic fracture nucleation process in EGS. The project will have a significant impact as it will (1) improve the characterization of the in-situ stress field at FORGE; (2) demonstrate how high-fidelity modeling tools can be employed to analyze data for EGS; (3) provide a unique set of high-temperature hydraulic fracturing experimental results for EGS to help identifying the most important components for in-situ stress estimation and to validate the current in-situ stress estimation theory and establish a strong foundation for proposing a new one; (4) provide a validated set of numerical tools in an open source simulation framework (GEOS) that can be used to model EGS.

15 GEOTHERMAL ENERGY↗

DOE OSTI2023

Integrated Process Testing of MSR Salt Spill Accidents

Part of the licensing process for new nuclear reactors requires vendors to assess the potential consequences of identified accident scenarios using accident progression modeling. The accident scenario that will likely be evaluated by all molten salt reactor (MSR) developers is a spill of radionuclide-bearing fuel salt onto the reactor containment floor (i.e., a salt spill accident). The development of accident progression models requires experimental data to inform which processes to incorporate, to enable the calculation of parameters to model these processes, and to validate the model predictions. The data should quantify the sensitivities of key processes (e.g., molten salt spreading, heat transfer, containment structure corrosion, radionuclide vaporization, and aerosol generation) towards the initial conditions of the spill, the ambient environment, and the features of the containment. In addition, results from integrated process tests that quantify coupled processes are required to validate systems-level models. This report documents results from integrated process tests conducted on simulated molten salt spill accidents. The generated experimental data simultaneously quantify the heat transfer behavior of the spilled salt, compositional changes to the bulk salt, and the release of surrogate fission products from the spilled salt as aerosol particles. All tests that were conducted used FLiNaK doped with surrogate fission products, and the variables that were evaluated included the initial salt temperature and the concentration of surrogate fission products present in the salt. The major accomplishments of this work include identifying surrogate fuel salt compositions that provide insight into the dispersal behavior of radionuclides of potential significance to the source term, employing previously developed methods and measurement techniques to simultaneously measure key processes, generating data on the coupled processes of molten salt heat transfer and surrogate fission product release as aerosol particles, demonstrating new test methods for real-time monitoring of the flow rate of the spill and aerosol size quantification in an argon atmosphere, and developing a mass transfer model for cesium and iodine release from molten FLiNaK to provide insight into aerosol formation by vapor condensation. The same methodology applied herein can be employed to study different salt compositions of interest to MSR developers, different environmental conditions, and other variables that are relevant to postulated accident scenarios. The insights gained from these integrated process tests conducted at a laboratory scale will be incorporated into future integral effects tests conducted at an engineering scale.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2023

Bench-Scale Testing of a High Efficiency, Ultra-Compact Process for Pre-Combustion CO 2 Capture (Final Report)

The overarching objective of this bench-scale study is to field-validate the technical feasibility of a membrane- and adsorption-enhanced water gas shift (WGS) reaction process that employs a carbon molecular sieve (CMS) membrane reactor (MR) followed by an adsorption reactor (AR) for pre-combustion CO 2 capture while demonstrating progress towards achievement of the overall performance goals of CO 2 capture with 95% CO 2 purity at a cost of electricity (COE) of 30% less than the baseline capture approaches. The main goal of this bench-scale project is to advance the proposed MR-AR transformative CO 2 capture technology to a sufficient maturity level so that our present industrial partners (M&PT and Worley) can potentially adapt the technology for further small pilot-scale testing. The project began at TRL 4, as the system prototype had already been validated in the laboratory on simulated syngas (as part of project DE-FE0026423). The project ended at TRL 5, via scaling-up of the prototype system and testing it on actual syngas at a host site (CAER at the University of Kentucky (UKy)). The project was carried-out in two different phases: In Phase I (during BP1 of the project), the team designed, constructed, and assembled the bench-scale experimental MR-AR system, prepared the membranes, adsorbents, and catalysts, tested the bench-scale unit with simulated syngas to validate functionality, and prepared a preliminary TEA of the technology. In Phase II (during BP2 of the project), the team installed the unit at the test site at the UKy site and completed all utility connections and hookups, field-tested the novel MR-AR process in the bench-scale system using real syngas, collected and analyzed experimental data, and completed a detailed TEA of the technology. A key aim of the project was to identify and address the technical and process risks and to generate information to advance the technology to the next stage of development. All project milestones and success criteria were met. Specifically, the team: (i) designed, constructed and assembled a bench scale system that handled 1 – 5 scfm syngas and tested its functionality with simulated syngas; (ii) prepared high performance CMS membrane tubes (ID: 3.5 mm, OD: 5.7 mm, 30” long) that meet the target H 2 permeance ( > 1 m 3 /(m 2 .hr.bar) or (> 370.3 GPU)) and a target H 2 /CO selectivity >80 at the relevant temperature (up to 300oC) and pressure conditions (up to 25 bar) with a <10% decline in performance over each 250 hr. testing period (iii) procured commercial sour-shift catalyst in sufficient quantity and prepared up to 10 kg of pelletized adsorbent for use at relevant conditions (250oC 2.5wt.% and target sorbent attrition rate < 0.2; (iv) installed the bench-scale unit at the test site (UKy) and tested the MR-AR technology using real syngas for over 250 hr. for both static and flow experiments; (v) updated the TEA analysis based on bench-scale data and met CO 2 capture goals of 95% CO 2 purity at a cost of electricity 30% less than baseline capture approaches. The CMS membranes, HTC adsorbents and catalysts employed all exhibited very robust and stable performance during the long-term run (over a >250 hr live syngas run). Furthermore, the proposed MR-AR IGCC system achieved a LCOE with a N 2 sale price of $\$$ 30/ton, with N 2 compression (no N 2 compression) of 101.2 $\$$/MWh (95.3 $\$$/MWh), which represents a 29.8% (33.9%) LCOE reduction in the baseline IGCC with carbon capture of 144.2 $\$$/MWh. The proposed MR-AR IGCC delivers a CO 2 capture cost of 44.8 $\$$/tonne (39.9 $\$$/tonne) vs 98.1 $\$$/tonne of the baseline capture case and a net power production of 586 MWe (623 MWe) vs 556 MWe of the baseline capture case.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2023

Inventory of Public Key Cryptography in US Electric Vehicle Charging

Electric vehicles (EVs) and charging infrastructure are networked systems, which employ high-level communications in support of charging and grid service decisions. Public key cryptography (PKC) underlies much of the security and privacy protections of the information exchange. We are entering a new epoch where quantum computing threats must be seriously considered. A sufficiently large quantum computer, so named Cryptographically Relevant Quantum Computer (QRQC), will be able to perform the mathematical operations to efficiently attack the underpinnings of traditional PKC, thus jeopardizing the digital foundations for trust, communications security, and data security. Estimates suggest a QRQC can break public key encryption and digital signatures in the manner of tens to hundreds of hours, compared to traditional computing that would demand more than 10 18 years in a brute force-style attack. A consensus belief of quantum theorists, quantum experimenters, and cryptographers suggest that the quantum threat will be likely realized in the next twenty years. To address the threat, post-quantum cryptography, which is cryptosystems that are designed to be secure against both traditional and quantum computing threats, must be adopted. Migration from traditional PKC to quantum-resilient cryptography is a global undertaking and likely represents the largest transition in computing history. The nascent state of EV public key infrastructure, combined with limited adoption of the vehicle secure charging features, presents an opportunity to establish a preference for quantum-resistant cryptography as a step on the migration path. Delays will stunt the efforts as rapidly accelerating EVs sales and huge infrastructure investments will create large growing bases of long-lived vehicles and infrastructure. Migration preparations can commence while NIST continues the process to standardize post-quantum cryptography (PQC), which are quantum-resilient algorithms designed to be secure against traditional and quantum computing threats. The first step in preparing EV charging is to identify the presence of traditional public key cryptography algorithms and applications. With this objective in mind, this report is intended to advise the vehicle manufacturers, charging station manufacturers, charging station operators, charge network providers and other EV charging stakeholders with information on traditional PKC application and the potential risks when PKC becomes insecure. This report, the first in a series of reports discussing the topics existing at the confluence of post-quantum cryptography adoption and EV charging, identifies traditional public key applications employed and identifies potential consequences of leaving EV charging infrastructure vulnerable to quantum computing. The focus remains squarely on the of EV charging and infrastructure with respect to PKC and is believed by the authors to complement the NIST SP 1800-38 Migration to Post-Quantum Cryptography. While the report is centered on infrastructure, there are implications to vehicles.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2023

PRIMED for the Future: Purposing Raw Intake for Machine Learning-Enabled Detection (Final Report)

The COVID-19 pandemic demonstrated how a novel, elusive, and diffuse biological threat can engender uncertainty and misinformation, and it underscored the need for flexible analytical modalities agnostic to the identity of biological material. Yet even before the pandemic, recognition of the limitations of the current, list-based approach, which focuses on known pathogens and biotoxins, and of the importance of agent-agnostic biodetection was growing within the biosecurity community. In a 2018 report on “Biodefense in the Age of Synthetic Biology,” for example, the National Academy of Sciences stated that “an overreliance on the Select Agent List is a systematic weakness affecting many aspects of the United States’ current biodefense mitigation capability”. More recently, a group of biodefense researchers proposed the identification and adoption of “bioagent-agnostic signatures (BASs)” as a way of detecting and characterizing not only existing agents but also novel ones, an approach they believe will “enable a more flexible and resilient biodefense posture”. Indeed, the future of biodetection requires us to begin developing novel analytics that can identify anomalies and/or characteristics that indicate a potential threat, whether known or unknown, without looking for a specific signature that has been identified previously. To assess potential threats more rapidly, it is critical to develop agnostic artificial intelligence (AI)/machine learning (ML) systems that can be employed for real-time assessment of the nature and source of a perturbation. Such systems should be multi scale and multi-dimensional, integrating sensor data from a range of biological, chemical, and physical application spaces. Emerging deep learning (DL) models demonstrate exceptional promise for identification of discriminatory features within multi-dimensional datasets. DL models have the capacity to recognize and encode highly complex patterns in a wide range of input data modalities, including images, text, and biological/chemical/physical spectra. As such, they can execute a wide range of assessments and determinations that have traditionally required a human operator. The promise of advances in DL is apparent in the realm of human health and medicine. DL models have been validated for evaluating a variety of clinical threats to human health in a range of contexts, including infection and cancer, and they demonstrated improved performance in predicting stroke relative to human neurologists in some categories of data. Continuously evolving advances in AI/ML are expected to support more efficient evaluation of raw sequence, spectroscopy, and spectrometry data. For instance, recent advances and deployment of large language models (LLM) such as Generative Pre training Transformer (GPT) and Bidirectional Encoder Representations from Transformers (BERT) have already motivated application of these models for biological function prediction. As frameworks such as LLMs become larger and more complex in their representations, their capacity to serve as pre-trained models that can be fine-tuned for biological/biodetection purposes will similarly be amplified. While existing and emerging AI/ML have found broad applicability and use cases in the clinical sciences, development for environmental evaluation and biodetection has been limited. Functionalizing such capabilities for this purpose requires an understanding of the existing technical landscape and how the respective tools and algorithms are currently being employed. This landscape awareness then allows an assessment of the current practical capabilities of existing models and the anticipated requirements and development efforts that will be needed to adapt available algorithms for biodetection applications relevant to DHS. Leveraging expertise in biodetection, ML, and operational biodetection, the effort described in this report is comprised of a systematic landscape assessment (Subtask 2.1), comparative evaluation (Subtask 2.2), and formulation of a value proposition (Subtask 2.3) for the prospect of ML-enabled, agnostic biodetection from raw, or minimally-processed, datasets.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

2022 AI Testbed Expeditions Report

By exploiting the coherent properties of a light source, coherent diffraction imaging (CDI) is able to obtain the sample image at a nanoscale resolution using the measured diffraction pattern. Bragg Coherent Diffraction Imaging (BCDI) has become valuable for recovering the displacement and strain field of crystals, providing a valuable tool in material science and solid-state physics. X-ray ptychography is another emerging CDI technique that can produce a high-resolution image of the extended sample and has become popular in many research areas (e.g., materials science, biology, electronics, and optics characterization). CDI including BCDI and ptychography has become an established technique in Synchrotron Facilities including the Advanced Photon Source (APS) and will greatly benefit from the 100x coherent flux increase of the upcoming APS Upgrade (APSU). The current image formation process in CDI employs iterative phase retrieval algorithms, which is a time-consuming and computationally expensive process. Especially after APSU, the traditional iterative methods will not be able to match the experimental data acquisition speed. We employ deep learning (DL) approach to replace the iterative approaches, therefore allowing hundreds of times faster recovery of the object. We developed AutoPhaseNN, a DL-based approach which learns to solve the inverse problem without labeled data. Taking 3D BCDI as a representative technique, AutoPhaseNN has been demonstrated to be one hundred times faster than traditional iterative phase retrieval methods while providing comparable image quality. The current network is trained with 64 x 64 x 64 data size, to achieve higher resolution imaging, we will need to scale the network to input and train/infer 3D arrays of size 256 x 256 x 256 (today) and of size 2560x2560x2560 (APSU). However, the scalability of the network is restricted due to the memory-intensive training process. To perform the training for a 256 x 256 x 256 data size, the required memory exceeds the capacity of the current machine. In this project, we explore using Sambanova system to train the network for the direct data inversion for CDI.

36 MATERIALS SCIENCE↗