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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.

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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Metal nitride materials for solar-thermal ammonia production [Slides]

Solar Thermal Ammonia Production has the potential to synthesize ammonia in a green, renewable process that can greatly reduce the carbon footprint left by the conventional Haber-Bosch reaction. Co 3 Mo 3 N has been identified as a potential candidate for ammonia production. It is synthesized via oxide precursor synthesis followed by nitridation under 10% H 2 /N 2 . The synthesis method can be extended to other candidate nitrides. The Co 3 Mo 3 N → Co 6 Mo 6 N reduction is demonstrated on TGA with rapid kinetics. The formation of NH 3 is qualitatively observed, but not quantitatively determined. The material retains crystal structure, but no secondary phases are observed in XRD. Partial re-nitridation back to CMN331 of ~35% of max nitridation is observed. Reaction parameters in TGA differ from experimental conditions in the literature. Experiments at Georgia Tech better mimic re-nitridation conditions with more sensitive, quantitative analytical techniques (GC-MS). The ASU NH 3 synthesis/re-nitridation reactor is under development and will permit experiments (reduction/re-nitridation) under precisely controlled T, pH 2 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

LDRD-2022-00108: Biomining Rare Earth Elements

Rare earth elements (REEs) are crucial to many high-tech devices and maintaining a competitive modern economy, thus they are of critical and strategic importance. Currently, mining approaches include rock grinding, strong acid or base extraction, separation, and concentration. The objective of this project was to develop cost-effective, environmentally friendly technologies for bioextracting REEs from mined materials.

58 GEOSCIENCES↗
DOE OSTI2022

Ultracold Storage Ring

The modern ring upgrades aim at reaching beam low emittance while paying little attention to the beam energy spread. The purpose of this note is to conjecture on a possibility of designing a storage ring with ultimately small energy spread. This might be of interest with respect to the following two applications: increasing brightness and coherence of radiation at higher harmonics of undulator radiation and a potential of building a soft X-ray FEL on a storage ring. Throughout the tech note we are taking a 3 GeV storage ring of the NSLS-II size as an example.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Autonomous System Subversion Tactics: Prototypes and Recommended Countermeasures

One of the fielding requirements for Advanced and Small Modular Reactors (AR/SMR) is the ability to support remote and autonomous operations. Autonomous Control Systems (ACS) are found on platforms such as Autonomous Space Vehicles, Cruise Missiles, and advanced driver-assistance systems. Each of these ACS implementations depends upon a set of decision support subsystems responsible for supporting Autonomous Mission Managers (names vary based upon field and author preferences). These Autonomous Mission Managers receive inputs from system sensors (e.g., LIDAR collection from an automobile travelling down a street; transients from a nuclear reactor), and perform a set of classifications (e.g., Red Traffic Light; Small Pedestrian at 10m; Load Rejection; Single Coolant Pump Trip), and then use these classifications in combination with recommendation algorithms to achieve platform goals (e.g., Stop the Vehicle at the Traffic Light, Avoid the Small Pedestrian; Trip the Reactor to prevent a Safety Event). The design, implementation, and fielding of an ACS capability will alter the cyber-attack surface such that existing risk management plans will need to be updated to include how to protect and defend against data-science and decision-support-system attack classes. These attack classes would include protection of the design and training environments where algorithm selection and testing and training data would be obvious attack vectors. These attack classes would also require an informed set of detection and response procedures to identify anomalous behaviors and document best practices for anomaly assessment and vulnerability mitigation and remediation. Last year we published a Cyber Threat Assessment Methodology for Autonomous and Remote Operations for AR/SMRs along with a companion publication on Cyber Attack and Defense Use Cases. The focus of the methodology was on describing and enumerating ACS processes, components, and functions such that security engineers could: evaluate subversion options against the target; identify threat actor attributes and capabilities derived from each subversion option; and identify security controls and response countermeasures. The Use Cases document offered detailed methodology examples including an assessment of a Military Base SMR, an Autonomous System Decision Loop, and implementation of AR/SMR Machine Learning algorithms. Our proposal at the end of last year was to focus on implementation of subversion prototypes related to the last Use Case area: AR/SMR Machine Learning (ML) Algorithms. We included six attack scenarios in our Use Cases paper: a Poisoning Attack against ML functions implemented using an FPGA; a Trojaning Attack against ML classifiers exploiting the excitability of Nuclear Engineers; a Backdooring Attack against ML Training environments to ensure persistence of an attack vector; a False Positive Evasion Attack against multi-factor Access Control Systems using clever inputs; an Inference Attack against ML models by an Insider with access to the Operational environment; and an Adversarial Reprogramming Attack against a Material Access Control Video Surveillance System. At the beginning of this year these six attack scenarios were provided to our research teams at Georgia Tech and Idaho State University and each team successfully implemented a subversion attack against a ML implementation to include transient misclassifications. While this is a notable outcome from this type of research, this paper offers the reader insight into not only how to structure and execute these types of attacks, but into the thought process behind how the researcher investigated the problem space, performed initial algorithm implementation, and the trial-and-error behind arriving at the successful subversion prototypes. We include in this paper a set of associated Scenarios on how these subversion prototypes could be implemented and an initial set of guidance for AR/SMR architects, Nuclear Regulators, and Cyber Defenders to implement awareness and defense capabilities into their current operational portfolios.

42 ENGINEERING↗
DOE OSTI2022

Development of Novel Materials for Direct Air Capture of CO 2 : MIL-101(Cr)-Amine Sorbents Evaluation Under Realistic Direct Air Capture Conditions (Final Report)

The overarching goal of this project is to evaluate the CO 2 adsorption properties of a small family of metal-organic framework (MOFs) materials functionalized with amines at sub-ambient conditions. Our goal is to develop capabilities to measure CO 2 adsorption at conditions more relevant to the weather of the planet. For this purpose, Georgia Tech is constructing a “sub-ambient adsorption facility” in partnership with ZCP Sorbent Development, LLC, aimed specifically at rapidly and deeply characterizing the performance of DAC candidate materials in this important operational range (adsorption at -20 to 20 °C and RH of 0-100%). Here, we use the sub-ambient lab instrumentation designed or adapted to study the behavior of the pristine metal organic framework (MOF) MIL-101(Cr) and the MOF in the presence of amines ranging from small molecules (e.g. TREN, tris(2-aminoethylamine)) to oligomers (e.g. PEI, poly(ethyleneimine)). Any DAC sorbent must be amenable to deployment in practical contactors for gas-solid contacting (traditional pellet-based fixed beds are impossible at scale). To this end, we developed and tested these DAC materials in the forms of composite polymer/MOF fibers and custom 3D-printed monolith structures containing MOF DAC sorbents. The proposed studies advance these materials from technology readiness level (TRL) 2 to TRL 3.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

Detectable Changes in U1a Data [Slides]

This is an update presentation on U1a data analytics for the Advanced Data Analytics for Proliferation Detection Tech Exchange Meeting.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Integrated Capture and Conversion of CO 2 to Methanol (ICCCM) Process Technology - CRADA 449 (Final Report)

The goal of this project is to develop a prototype system that integrates the capture and catalytic hydrogenation of CO 2 into methanol in the same solvent. Ultimately, this integrated approach could provide a technology with projected reductions to capital and operating costs by at least 20% relative to a benchmark methanol synthesis via gas-phase CO 2 hydrogenation. There were five primary objectives for the project: 1. Optimize the selections of both the catalysts and the CO 2 capture solvents to achieve high conversion (>80%) and high selectivity (>90%) toward methanol in the targeted processing ranges (100-180°C, 1-60 bar). 2. Design a reactor system that provides a fixed catalyst surface area and high-efficiency heat exchange to assure compact modular processing. 3. Build and test a reactor system and demonstrate in a bench scale continuous flow system, and use the operating data to refine the comparison to existing conversion technologies. 4. Refine techno economic (TEA) and Tech-to-Market (TTM) analyses using the experimental data obtained from the bench-scale system. 5. Use the experimental data and TEA/TTM projections to develop a conceptual design for a pre-commercial system that targets a specific market opportunity.

09 BIOMASS FUELS↗
DOE OSTI2023

Field Laboratory for Emerging Stacked Unconventional Plays in Central Appalachia

The goal of the Field Laboratory for Emerging Stacked Unconventional Plays (ESUP) in Central Appalachia project was to investigate and characterize the resource potential for multi-play production of emerging unconventional reservoirs in Central Appalachia. Project activities included drilling, logging and coring of a vertical characterization well drilled to basement to approximately 15,000 feet in depth. The data from drilling and well logs as well recovered core samples were used by the research team to support characterization of the geology and potential pay zones within the Nora Gas Field of southwestern Virginia and the greater Central Appalachian Basin. This project was led by Dr. Nino Ripepi of the Virginia Center for Coal and Energy Research (VCCER) in close collaboration with EnerVest Operating LLC (EnerVest). VCCER is housed in the Department of Mining and Minerals Engineering at Virginia Tech and was created by an Act of the Virginia General Assembly on March 30, 1977, as an interdisciplinary study, research, information, and resource facility for the Commonwealth of Virginia. EnerVest is a top tier, low-cost oil and natural gas company with a long history of traditional operating relationships with institutional investors as well as public and private companies. This report summarizes two major research activities: 1) Log and Core Analysis and 2) Numerical Modeling. Core analysis comprises the characterization efforts of the ESUP Field Laboratory and includes a discussion of the well logs run in the deep characterization wells, an initial analysis of those, the number, size and location of cores recovered, core testing and analysis done to date as well as plans for future analysis. Numerical modeling is comprised of seven major modeling efforts, including (1) Multiphysics shale transport modeling work, (2) the developed in-house compositional simulator studies, (3) reservoir modeling studies using GEM software, (4) fracture modeling work using EFRAC3D software and (5) numerical modeling efforts with ABAQUS software, (6) Numerical modeling efforts using FLAC3D and PFC3D, and (7) Automatic Machine Learning (AutoML) Studies.

02 PETROLEUM↗
DOE OSTI2023

Natural Language Processing for Text Based Event Extraction: Identifying Events of Interest Related to Worldwide State-Sponsored Civil Nuclear Power

Beginning in FY20, SRNL was funded by the National Nuclear Security Administration’s Office of Defense Nuclear Non-Proliferation Research and Development to develop a prototype natural language processing/natural language understating machine learning-based modeling and analysis pipeline to extract and forecast events of interest from massive open data sources. The working hypothesis within the approach is that contextual shifts in key words and phrases act as indicators of events of interest over time. Therefore, by identifying points in time where contextual shifts occur, events of interest can be extracted along with explicit and implicit connections of entities and activities. The development of the preliminary prototype pipeline proved successful, meriting further testing of the pipeline on more broad topical domains and in a worldwide data environment. Therefore, SRNL, in collaboration with the Sanghani Center for Artificial Intelligence and Data Analytics at Virginia Tech, have continued development with a test case of identifying events of interest related to worldwide state-sponsored civil nuclear power in open data sources. In the first year of this follow-on effort, the team has curated domain-specific data corpuses using an automated scheme and applied the modeling and analysis pipeline. This robust, focused, and efficient approach consists of an ensemble of analyses applied to time dependent word embedding models that are trained on the data corpuses. In this report, the team has demonstrated the capability of the existing pipeline (as development has continued in parallel) by exploring several specific case-studies centered around Rosatom’s international activities regarding the planning, construction, operation, and/or shutdown of nuclear reactors. A basic timeline events has been generated by manually cataloging known “milestone” events that have occurred at reactors in Turkey, Finland, Hungary, and Egypt and compared with the output of the modeling pipeline. In this approach, the team has characterized the lead time using the prototype pipeline, as well as the ability to capture relevant information, which proved 100% successful. A deep dive example of the Akkuyu reactor (Turkey) is presented that shows the breadth of information that can be captured using the approach. In this case study, events were extracted pertaining to the planning/construction of Akkuyu including protests from the population, information campaigns in response to the protests, forged regulatory documents and lawsuits, budgetary/shareholder information, geopolitical tensions, and the various construction milestones. This has demonstrated the pipeline’s utility as a research aid or real-time event extraction tool, where summary-level information and detailed text extractions from millions of articles or Tweets across long time periods can be generated with significantly less effort than current techniques.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

TRACER Lightning Mapping Array Field Campaign Report

Our observational contribution to the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s Tracking Aerosol Convection Interactions Experiment (TRACER) was the deployment of additional Lightning Mapping Array sensors to provide enhanced capability to the Houston Lightning Mapping Array (HLMA) during the TRACER intensive operational period. To that end, the Texas Tech University personnel (Professor Bruning and Dr. Brunner, and graduate students Jessica Souza, David Singewald, Stephanie Weiss, and Matthew Miller) deployed two portable LMA antennae at locations G and B shown in the map below. The map also shows the predicted lightning flash detection efficiency in black contours, as well as color-shaded very-high-frequency (VHF) source detection efficiency, which roughly corresponds to the sensitivity to lightning channel detail. Feeds from these sensors were integrated in the HLMA processing in real-time and in post-processing, partially leveraging National Science Foundation support through the TRACER campaign that supported the core HLMA, operated by Timothy Logan.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Multi-Sourced Collaboration for the Production and Refining of Rare Elements and Critical Metals (Final Technical Report)

The project objective was to develop a feasible and cost-effective method for recovering rare earth elements (REEs) and critical materials (CMs) from coal and coal byproducts, resulting in high-purity individually separated REEs and CMs. The targeted REEs included Y, Pr, Nd, Gd, Dy, and Sm, with a purity of over 99.5%, while the CMs included Co, Mn, Ga, Sr, Li, Ni, Zn, and Ge, with a purity of over 90%. The project aimed to design a prototype facility capable of producing 1-3 tonnes/day of high-purity REO mixes. The work was divided into four designated circuits: 1) REE extraction and concentration, 2) REE separation and purification, 3) RE metal production, and 4) CM production. To achieve these goals, the project involved 11 tasks, including technology reviews, research, process flow diagram development, mass balance estimation, and preliminary technical-economic analysis. The project team included researchers from the University of Kentucky, University of Alabama and Virginia Tech as well as process specialists from Argonne National Laboratory. MP Materials provided technical support regarding rare earth markets and processing while Alliance Coal performed resource assessment. The project included a market analysis for Nd/Pr, Tb, Dy, Gd, Y, Co, Mn, Li, Sr, Ga, Ni, Zn, and Ge. These analyses provided insights into the supply and demand trends as well as historic and future projections of market price relative to purity requirements for these elements. Two coal resources were selected for the project: the West Kentucky No. 13 (Baker) Seam and an undisclosed lignite resource in the Illinois coal basin. The estimated quantities of REEs in these resources were calculated based on production samples and drilling data. It was estimated that there is adequate supply for an operation producing one metric ton daily of higher purity mixed rare earth oxides (MREO) for approximately 20 years at a site located in western Kentucky. In Circuit 1, project data was obtained from a pilot heap leach and REE concentration facility. It was concluded that the existing circuit, which generated a MREO concentrate, two types of CM mixed products, and Li- and Sr-containing waters, would be suitable feed for circuits 2-4. Data from the first-of-its-kind coal coarse refuse heap leach pilot pad played a crucial role in estimating reliable elemental concentrations of the pregnant leaching solution (PLS). The average total REE concentration in the PLS was found to be 28.6 ppm. In Circuit 2, several concepts were explored including a novel process referred to as solvent-assisted chromatography (SAC). This concept involved a novel columnar reactor that incorporated multiple mixer/settlers, thereby enabling the operation of counter-flowing aqueous and organic phases. Unfortunately, due to project time constraints, a complete fundamental modeling analysis could not be completed to fully evaluate the technology. Molten salt electrowinning was considered as an alternative for circuit 3 following circuit 2 purification circuit utilizing the novel SAC process. A mass and energy balance of Nd reduction to metal in a fluoride containing molten salt electrolyte was conducted. Comparisons were made with the current state of Asian molten salt electrorefining, and potential improvements in siphoning rare earth metals (REM) from the reactor were presented. A cost estimate was performed for the production of 1 tonne per day, which yielded a total of $2.29 million for the nine electrowinning (EW) cells required. The selected option for circuits 2 and 3 was a plasma distillation process, which initially separates rare earth elements (REEs) from other elements. This is followed by selective electrowinning in various ionic liquids. The selection was made on the basis of thermodynamic modeling and experimental data previously published by a project partner. The combination offers an innovative approach to integrated refining and RE metal production. For Circuit 4, an extensive literature review was conducted for the processing of the CMs. The ultimate decision was to utilize a combined plasma and ionic liquid process as well to produce individual high-purity concentrates of Zn, Ni, Co, Mn, and Mg. A separate flowsheet for Li and Sr was recommended, which would yield carbonates of these elements. Due to the lack of suitable experimental data at this time, a process recommendation could not be provided but several methods have been proposed for consideration. Lastly, a techno-economic analysis (TEA) was conducted to assess the effectiveness of the proposed process for further investigation. The TEA results revealed a capital expense (CapEx) of $737 million and an annual operational expense (OpEx) of $220 million. Due to the selected elements, the hypothetical heap leach pad can produce 1 metric tonne per day of REO equivalent, but a conscious decision was made to only treat targeted REEs, resulting in the production of 0.4 metric tonne of REM. An estimated annual revenue of $90.87 million was projected based on standard market pricing information provided by the funding agency. During the TEA, ten different modules were evaluated for costing purposes. The precipitation circuit was identified as the largest single operational expense, followed by the Mg/Mn process due to the amount of treated metal. In terms of capital expenditures, the heap leach process incurred the highest cost, followed by the Mg/Mn process. The scalability of the plasma process is a crucial consideration since the reactors cannot be scaled beyond the largest demonstrated size due to their reliance on surface area of the slag and vapor phase. The purity estimate for the REEs are generally 98%±2% to produce a metal. The purity level being lower than the project objective was due to the lack of specific experimental data needed to tighten the tolerance of the estimates. Based on literature and previous experience, the CMs are estimated as follows; Ga (95%+, metal), Sr (95%+, carbonate), Li (95%+, carbonate), Ni (98%±2%, metal), Zn (95%+, metal sponge), Ge (95%+, metal), Co (98%±2%, metal), and Mn (98%±2%, metal).

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

High Inlet Temperature Combustor for Direct-Fired Supercritical Oxy-Combustion

It is envisioned that supercritical CO 2 (sCO 2 ) electric power plant efficiencies can exceed 52% with 99% carbon capture using direct-fired oxy-combustion. Such efficiencies would be competitive with Natural Gas Combined Cycles (NGCC) and operate with nearly zero carbon emissions. To achieve high plant efficiencies, turbine inlet conditions must approach 1,200 °C at 250 bar. Such conditions, while desirable from a systems perspective, exceed the current state of the art in turbine design and materials qualification. The team of Southwest Research Institute ® (SwRI ® ), Georgia Institute of Technology (Georgia Tech), Spectral Energies, LLC (Spectral), GE Global Research (GE-GRC), and the University of Central Florida (UCF) sought to demonstrate an intermediate step toward these high efficiency plants with the development of a 1 MWth, subscale direct-fired oxy-fuel combustor. The efforts focused largely on the development of an auto-ignition based combustion system capable of providing the targeted 1200 °C and the pilot-scale plant to operate the combustor. While the project was stopped short of the commissioning and demonstration work, the advances made in this effort will reduce risks associated with chemical kinetics, thermal management, water separation, flue gas cleanup, materials selection, and corrosion in future demonstration efforts for the direct-fired oxy-fuel combustion cycles. The following report documents the design, analysis, and installation efforts completed during the project periods of performance.

03 NATURAL GAS↗
DOE OSTI2023

A Simplified Method to Evaluate Energy Life Cycle Cost Effectiveness for Electron Ion Collider Infrastructure Design

The new DOE Order 436.1A approved on April 25 th provides instructions to incorporate principles of sustainability early in the project planning and design process. Integral to the principles of sustainability is life cycle cost effectiveness Life Cycle Cost (LCC) Analysis is vital to the sustainable energy efficient design and construction of the Electron Ion Collider (EIC). Reducing energy consumption has a direct impact on reducing life cycle operating costs with benefits to the environment. The early stages of the project are the most influential where design decisions and so life-cycle considerations during this stage can result in significant impacts to the energy footprint of the design. For example, when comparing between various options, it is necessary to compare the energy savings in $\frac{US$}{kWh}$ to the capital cost in US$. And although uncertain by nature, it is important to factor in the expected inflation and discount of future spendings to compare with the cost of immediate capital investment. This tech note presents a tool that engineers can readily use to analyze energy operating costs using an incremental life cycle cost method when comparing different design alternative.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Optimizing liquid free ionomer binders for high-temperature polymer electrolyte membrane fuel cells for heavy duty vehicles

This report documents tech transfer from Penn State to Ionomer Solutions LLC for high-temperature polymer electrolyte membrane fuel cells. High-temperature polymer electrolyte membrane (HT-PEM) fuel cells are enticing power plants for heavy-duty vehicle (HDV) transportation because their elevated temperature operation fosters greater heat rejection through larger temperature differentials. In 2021, over 6 million battery electric light duty vehicles (LDVs) were sold. Conversely, only 19,000 LDVs using fuel cell power trains were sold in 2021. Given the meteoric rise of battery-based powertrains for LDVs and its projected growth, stakeholders for fuel cell technology for transportation have shifted their focus towards HDVs rather than LDVs given fuel cells specific and volumetric energy density advantage over batteries when the vehicle is large, heavy, and/or needs to move large distances before refueling.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2022

Passive Ultrasonic Deterrents to Reduce Bat Mortality in Wind Farms (Final Report)

The overall objective of this project was to develop active and passive ultrasonic deterrent concepts to mitigate bat mortality at wind turbines. The research was supported by the US Department of Energy under the contract DE-EE0008731. Novel ultrasonic bat deterrents are investigated in this study. The deterrents are based on the idea of aerodynamic whistles wherein flow-acoustic resonance is used to produce high-amplitude tonal sound at desired ultrasonic frequencies. The deterrents can be grouped into active and passive. The active deterrents/whistles are driven by pressurized air supplied by an external source (e.g., an air compressor). The passive deterrents/whistles are designed to be mounted on wind turbine blades and are “powered” by the energy in the air moving past the rotor blades. Multiple active and passive deterrent ideas are proposed and investigated numerically and experimentally. The computational analysis involves solving the compressible unsteady Reynolds-averaged Navier-Stokes (URANS) equations and coupling the near-field aerodynamic solution with an integral method based on the Ffowcs Williams-Hawkings acoustic analogy to predict ultrasound in the farfield. Experiments are performed in the anechoic chamber at ISU (for the active whistles) and in the Stability wind tunnel at Virginia Tech (for the passive whistles).

17 WIND ENERGY↗
DOE OSTI2023

Unlocking Metamaterials At The Macro Scale (CRADA Final Report)

This project was part of the Cyclotron Road program, which supports scientific entrepreneurs in their efforts to commercialize novel technologies with potential to address energy, manufacturing and climate related issues. The participants' technology is a lightweight cellular material system which could be applied to a range of products and markets and offer benefits of reduced weight, cost, waste, and carbon footprint. The objective of the project was to investigate potential opportunities and de-risk technical and market barriers in pursuit of successful commercialization. This project’s purpose was to find market pathways and technical roadmaps for commercializing the lightweight cellular material technology. The main problems to overcome are the risks in both tech and market. On the technical side, performance, weight, cost and speed of manufacturing, and other scaleup problems needed to be addressed. On the market side, the challenges included finding product/market fit, developing business models and go to market strategies, and developing commercial relationships within various industries. Our approach typically started with market analysis, in order to identify potential applications where our technology could solve problems and address pain points. To do this, we performed customer discovery, interviewing hundreds of industry stakeholders along all parts of the value chain for a given product or industry. From here, we would develop technoeconomic models which combined aspects of numerical modeling for structural and mechanical performance based on criteria from customers or industry guidelines such as stiffness, strength, weight, and other physical properties. Then, this would be combined with detailed cost models to translate the engineering solution into a manufacturable, scalable product. The challenge here was to have equal or better performance at lower cost and higher speed than existing solutions.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A SENSOR CHARACTERIZATION METADATA ARCHITECTURE

Presentation conducted at the 11th Annual International AMS Tech Exchange in Spiez, Switzerland addressing the next generation algorithms require metadata and contextual data not currently recorded and/or digitized. Need to develop more robust and interchangability to perform more complex tasks for a wider range of international users.

47 OTHER INSTRUMENTATION↗