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At least 343 records · Page 19

Uncertainty Quantification of Fatigue Behavior of Rough AM Surfaces and Microstructures to Enable Hydrogen Gas Turbine Combustion

Modification of fossil-fueled industrial gas turbines to accept no/low carbon fuels (Hydrogen, H2/natural gas blends) is a significant undertaking. Successful deployment of this technology sits at the intersection of three design criteria (1) new functional fuel injectors that can burn these fuels, (2) manufacturability to meet cost and time-to-market targets, and (3) durability in the harsh environment of an operating turbine. Additive manufacturing (AM) provides accelerated product development. However, uncertainty remains around the durability of parts with rough AM surfaces. A fully experimental approach towards quantifying fatigue performance of rough AM microstructures is costly and laborious. Instead, Solar Turbines Incorporated (Solar) proposes the use of a crystal plasticity finite element (CPFE) model to quantify the factors that drive AM surface fatigue behavior. Solar will use the CPFE results, along with targeted experimental data, to train a computationally efficient surrogate model that can be incorporated into existing turbine part lifing methods.

08 HYDROGEN↗

Life cycle energy demand and carbon emissions of scalable single-junction and tandem perovskite PV

Perovskite photovoltaics reached record efficiencies in the laboratory and, if sustainably commercialized, they would accelerate a green energy transition. Here, this article presents the development of life-cycle inventory material and energy databases of most promising four single-junction and three tandem scalable perovskite systems with assumptions regarding scalable production validated by industry experts. We conducted comprehensive “ex ante” Life Cycle Analysis (LCA) and Net Energy Analysis, analyzing their cumulative energy demand, global warming potential profiles, energy payback times and energy return on investment (EROI). LCA contribution analysis elucidates the most impactful material and process choices. It shows that solution-based perovskite manufacturing would have lower environmental impact than vapor-based methods, and that roll-to-roll (RtR) printing offers the lowest impact. Among material choices, MoOx/Al has lower impact than Ag, and fluorine-tin-oxide lower than indium-tin-oxide. Furthermore, we compare perovskites with commercial crystalline-silicon and thin-film PV, accounting for the most recent developments in crystalline-Si wafer production and differences in life expectancies and efficiencies. It is shown that perovskite systems produced with RtR manufacturing could reach in only 12 years of life the same EROI as that of single-crystalline-Si PV lasting 30-years. This work lays a foundation for sustainability investigations of perovskite large-scale deployment.

14 SOLAR ENERGY↗

Concept of Operations: National Technology Test Bed Network for Water Resource Recovery

There is an urgency to advancing wastewater technologies due to aging water infrastructure and emerging regulations. A crosscutting working group proposes a conceptual design for a test bed network to understand and evaluate wastewater technologies to drive acceptance and deployment of new technologies to enhance performance. The working group includes contributors from the U.S. Department of Energy, the U.S. Environmental Protection Agency, the U.S. National Science Foundation, and the Water Research Foundation (formerly known as the Water Environment & Reuse Foundation). Upgrading today's aging wastewater treatment infrastructure to a new generation of water resource recovery facilities (WRRFs) requires the development and deployment of innovative technologies. The path to technology adoption depends on expensive, time consuming, and often repetitive cycles of testing and validation. Existing water resource recovery technology testing facilities (e.g., test beds) are underutilized and cannot, by themselves, broaden technology uptake. It has been proposed that technology adoption could be accelerated by a network linking these test facilities with innovators, manufacturers, utilities, regulators, policymakers, and educators. This document proposes a structure for a National Test bed Network (TBN) for water resource recovery. The concepts for its operation are explored herein. This document identifies drivers to launch a TBN and critical needs for successful implementation of the network. An important driver to technology implementation at WRRFs is the relationship between local utilities and state regulators. The TBN could provide access to validated performance data and facilitate deployment. To link the stakeholders and accelerate deployment, the TBN will require standards for methods, data quality, data management, and data security. These standards will enable validation of performance and will expand the “toolbox” that utilities and regulators could consider. Design, set up, and launch of this toolbox is beyond the scope of operations of utilities and regulators and will likely require external support to achieve full operation. Herein, a pathway is proposed to achieve this full operation. This document defines the function of a WRRF TBN. It also proposes a structure for the TBN to achieve its stated goals and mission. Finally, this document summarizes findings from several sources, including a series of workshops about the TBN concept, operators of test beds in ancillary industries, and discussions with regulators and permitting agencies. A description of this work was published in the peer-reviewed literature (Mihelcic 2017).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA Tech Briefs, December 2008

Topics covered include: Crew Activity Analyzer; Distributing Data to Hand-Held Devices in a Wireless Network; Reducing Surface Clutter in Cloud Profiling Radar Data; MODIS Atmospheric Data Handler; Multibeam Altimeter Navigation Update Using Faceted Shape Model; Spaceborne Hybrid-FPGA System for Processing FTIR Data; FPGA Coprocessor for Accelerated Classification of Images; SiC JFET Transistor Circuit Model for Extreme Temperature Range; TDR Using Autocorrelation and Varying-Duration Pulses; Update on Development of SiC Multi-Chip Power Modules; Radio Ranging System for Guidance of Approaching Spacecraft; Electromagnetically Clean Solar Arrays; Improved Short-Circuit Protection for Power Cells in Series; Electromagnetically Clean Solar Arrays; Logic Gates Made of N-Channel JFETs and Epitaxial Resistors; Improved Short-Circuit Protection for Power Cells in Series; Communication Limits Due to Photon-Detector Jitter; System for Removing Pollutants from Incinerator Exhaust; Sealing and External Sterilization of a Sample Container; Converting EOS Data from HDF-EOS to netCDF; HDF-EOS 2 and HDF-EOS 5 Compatibility Library; HDF-EOS Web Server; HDF-EOS 5 Validator; XML DTD and Schemas for HDF-EOS; Converting from XML to HDF-EOS; Simulating Attitudes and Trajectories of Multiple Spacecraft; Specialized Color Function for Display of Signed Data; Delivering Alert Messages to Members of a Work Force; Delivering Images for Mars Rover Science Planning; Oxide Fiber Cathode Materials for Rechargeable Lithium Cells; Electrocatalytic Reduction of Carbon Dioxide to Methane; Heterogeneous Superconducting Low-Noise Sensing Coils; Progress toward Making Epoxy/Carbon-Nanotube Composites; Predicting Properties of Unidirectional-Nanofiber Composites; Deployable Crew Quarters; Nonventing, Regenerable, Lightweight Heat Absorber; Miniature High-Force, Long-Stroke SMA Linear Actuators; "Bootstrap" Configuration for Multistage Pulse-Tube Coolers; Reducing Liquid Loss during Ullage Venting in Microgravity; Ka-Band Transponder for Deep-Space Radio Science; Replication of Space-Shuttle Computers in FPGAs and ASICs; Demisable Reaction-Wheel Assembly; Spatial and Temporal Low-Dimensional Models for Fluid Flow; Advanced Land Imager Assessment System; Range Imaging without Moving Parts.

Source record↗

Basic Research Needs for Catalysis Science to Transform Energy Technologies: Report from the U.S. Department of Energy, Office of Basic Energy Sciences Workshop May 8–10, 2017, in Gaithersburg, Maryland

Energy technologies affect virtually every aspect of life in modern societies—including transportation, utilities, agriculture, medicine, and the availability of a myriad of consumer products—and depend on human ability to accelerate and to guide chemical transformations. Controlling these transformations, which occur in the microscopic world of atoms and molecules, forms the basis of countless technologies such as production of fuels, fertilizers, plastics, pharmaceuticals and much more. At the very core of these chemical transformations are catalysts—specialized and often highly complex types of matter that allow chemical reactions to occur rapidly and produce specific products. Catalysts also have the remarkable ability to perform their tasks millions of times without themselves being consumed. The discovery of inexpensive and widely-deployable energy and chemical technologies, and their underpinning catalysis science, is critical to ensure the economic viability of U.S. energy and chemical industries. Over the past decade, remarkable new tools have been discovered that allow the observation of catalytic transformations in exquisite detail, and assembly of novel and elaborate catalytic architectures with atomic precision. Furthermore, increasingly sophisticated theoretical and computational tools allow understanding of the essential details of the catalytic processes, and this overall progress has led to the discovery of catalysts with superior performance and the associated economic benefit. In the next decade and beyond, science promises to revolutionize how catalysts and catalytic processes are designed, to enable the introduction of new energy resources, to provide routes to sustainable synthesis of chemicals and other valuable materials, and to create novel approaches to chemical energy storage. This report is the result of the Basic Energy Sciences Workshop on Basic Research Needs for Catalysis Science to Transform Energy Technologies that was held in May 2017, and was attended by more than 100 leading national and international scientific experts. The attendees were organized into four panels: 1. Diversified Energy Feedstocks and Carriers, 2. Novel Approaches to Energy Transformations, 3. Advanced Chemical Conversion Approaches, and 4. Crosscutting Capabilities and Challenges: Synthesis, Theory, and Characterization. The workshop identified five priority research directions (PRDs) that are aimed at harnessing complexity in catalysis to create next-generation energy technologies and realizing efficient catalytic processes to increase the diversity of resources for production of chemicals and energy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Removal of High Specific Activity Fission Products from Uranyl Sulfate Waste Solutions

The Savannah River National Laboratory (SRNL) is currently providing support to SHINE Medical Technologies (SHINE) which plans to deploy a low energy, accelerator-based neutron source to fission low enriched U in a uranyl sulfate target solution for 99 Mo production. The 99 Mo is initially separated from the fission products and target solution by an extraction column. Subsequent washing of the column will generate waste solutions containing residual U and fission product activity. A small number of high specific activity fission products (e.g., 90 Sr, 137 Cs, and 144 Ce) in these streams will likely control the classification of the low level waste (LLW). If a sufficient amount of the high specific activity isotopes are separated from the SHINE waste streams and concentrated into a waste form, it would be possible to treat a majority of the wash solutions from the column operations as a lower class of LLW (Class A versus Class B or C or Class B versus Class C). The high specific activity fission product elements could then be dispositioned as a much smaller volume of waste rather than requiring the disposal of the entire waste stream at the higher waste classification. The Savannah River Site (SRS) has experience with using monosodium titanate (MST) and crystalline silicotitanate (CST) to remove Cs and Sr from high salt content waste solutions generated during the reprocessing of nuclear fuels and targets. Both of these materials have worked very well for their intended purposes at the SRS where the fission product elements are removed from highly alkaline waste. On the other hand, SHINE waste streams from the extraction column contain H 2 SO 4 which makes the solution acidic. Additionally, the SRS waste streams do not contain other fission product elements such as transition metals or lanthanides because they precipitate upon neutralization of the SRS waste and are not present in the supernate which is dispositioned as LLW following treatment. As such, there are inherent differences between SHINE and SRS waste treatment strategies. Savannah River National Laboratory was tasked with performing scoping studies to see if MST and CST would remove Sr, Cs, and Ce from an acidic mixed metal simulant solution. Batch contact experiments were performed using MST and two CST type materials. The MST material is a 15 wt % powder in 0.15 M NaOH slurry. The MST showed low adsorption for elements of interest from acidic solution. Furthermore, the powder size makes MST non-ideal for column operations. A CST IE-911 ion exchange material had high Cs adsorption, moderate Sr, and marginal Ce adsorption. Based on adsorption of all species, the ion exchange capacity was found to be 0.032 meq/mL. A bench-top column experiment to measure elemental breakthrough curves was performed using CST IE-911 where chromatographic separations of the mixed simulant were expected to occur. While most elements behaved as expected, the lanthanide series, containing Ce, broke though the column earlier than expected. The second CST material, CST R9120, displayed high adsorption for all elements in the acidic mixed simulant solutions in a batch contact study, and had a calculated loading capacity of 0.091 meq/mL. Future studies to develop a waste treatment flowsheet should focus on CST R9120 to treat SHINE waste solutions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Fuel Fabrication Capability Assessment in Support of Advanced Reactor Deployments

More than 30 U.S. companies are designing a variety of advanced reactor concepts, and several companies are planning to demonstrate their reactor designs in the mid-2020s to late 2030s time frame. In 2020, the U.S. Department of Energy (DOE) announced a series of awards under the Advanced Reactor Demonstration Program (ARDP) to accelerate the successful deployment of 10 of these reactors under three pathways. TerraPower and X-energy were awarded grants under the Advanced Reactor Demonstration Program to deploy their respective Natrium reactor and Xe-100 reactor designs in the next 7–10 years. These demonstrations are in addition to several parallel programs, including the U.S. Department of Defense’s (DoD’s) interest in the development of microreactors, and interest of the National Aeronautics and Space Administration in space nuclear power and propulsion. The National Reactor Innovation Center’s (NRIC’s) mission is to accelerate the demonstration and deployment of advanced reactors; NRIC is partnering with several reactor developers and harnessing the world-class capabilities of the U.S. National Laboratory system to deliver on its mission. Several of these reactor designs will require advanced fuel forms that are not commercially available today, including metal fuel, molten salt fuel, TRi-structural ISOtropic (TRISO) particle fuel, and uranium nitride fuel. Recognizing that there may be potential gaps in the laboratory-scale process development and pilot-scale first-of-a-kind (FOAK) production of these fuel forms leading to delivery of the FOAK cores, NRIC commissioned this study to look at the challenges that need to be overcome for successful deliveries, including the evaluation of existing facilities and the potential need for a new fuel fabrication facility.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Science-based Acceleration of the Full Value Stream for Metal Additive Manufacturing (AM): Expedited Powder Development and Additive Manufacturing Deployment in the Area of Aluminum Powder Alloys

The overall Science-based Acceleration of the Full Value Stream for Metal Additive Manufacturing (AM): Expedited Powder Development (“X-P4AM”) project objective is to drastically reduce the time-to-market barriers for new additive alloys of interest in automotive and aerospace applications, through computational alloy design with rapid screening and down- selection via synthesis of candidate alloys with rapid solidification. The project will also refine the technology in high pressure gas atomization to improve the production of commercial quantities of selected powders with high powder yields and enhanced powder quality. A new aluminum (Al) alloy based on high entropy composition, enhanced powder production, and optimized AM build parameterization provided a critical step in widespread adoption of AM technology for automotive applications, in this case. The individual backgrounds and capabilities of the Parties are ideally suited to the successful execution of this work. The included work enhanced the Contractors’ AM capabilities, a core competency of the Contractors, and develop a close working relationship with the Participant in the area of aluminum powder alloys and their end use.

36 MATERIALS SCIENCE↗

Evaluating algorithmic bias on biomarker classification of breast cancer pathology reports

Objectives: This work evaluated algorithmic bias in biomarkers classification using electronic pathology reports from female breast cancer cases. Bias was assessed across 5 subgroups: cancer registry, race, Hispanic ethnicity, age at diagnosis, and socioeconomic status. Materials and Methods: We utilized 594 875 electronic pathology reports from 178 121 tumors diagnosed in Kentucky, Louisiana, New Jersey, New Mexico, Seattle, and Utah to train 2 deep-learning algorithms to classify breast cancer patients using their biomarkers test results. We used balanced error rate (BER), demographic parity (DP), equalized odds (EOD), and equal opportunity (EOP) to assess bias. Results: We found differences in predictive accuracy between registries, with the highest accuracy in the registry that contributed the most data (Seattle Registry, BER ratios for all registries >1.25). BER showed no significant algorithmic bias in extracting biomarkers (estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2) for race, Hispanic ethnicity, age at diagnosis, or socioeconomic subgroups (BER ratio <1.25). DP, EOD, and EOP all showed insignificant results. Discussion: We observed significant differences in BER by registry, but no significant bias using the DP, EOD, and EOP metrics for socio-demographic or racial categories. This highlights the importance of employing a diverse set of metrics for a comprehensive evaluation of model fairness. Conclusion: A thorough evaluation of algorithmic biases that may affect equality in clinical care is a critical step before deploying algorithms in the real world. We found little evidence of algorithmic bias in our biomarker classification tool. Artificial intelligence tools to expedite information extraction from clinical records could accelerate clinical trial matching and improve care.

60 APPLIED LIFE SCIENCES↗

A Full-scale Demonstration of Pressurized Water Reactor Core Design Optimization using Multi-Cycle Optimization Methodology

The U.S. nuclear sector encounters a difficulty in upholding essential safety standards while also securing economic viability for continued operation. Safety stands as a pivotal factor across all facets of operations within light-water reactor nuclear power plants. Achieving economic feasibility alongside safety can be facilitated through the utilization of a risk-informed framework, exemplified by the ongoing development within the Risk-Informed Systems Analysis Pathway under the auspices of the U.S. Department of Energy's LWRS Program. This initiative advocates for a diverse array of research and development endeavors aimed at optimizing both safety and economic efficacy within nuclear power plants, particularly pertinent as many plants contemplate second license renewals. The Risk-Informed Systems Analysis Pathway has two main goals: deploy methodologies and technologies that better represent safety margins and cost and safety factors and develop advanced applications that enable cost-effective plant operation. This report assesses the potential for resolving multi-cycle plant reload challenges through real-world scenarios utilizing the Plant ReLoad Optimization (PRLO) framework. This framework offers reactor core design developers analytic tools of reactor safety and fuel performance with the assistance of artificial intelligence (AI) to enhance core design solutions. Multi-objective genetic algorithm alongside acceleration techniques is explored as an enabling technology for improving fuel efficiency while upholding safety thresholds. The demonstration of multi-cycle core design optimization is performed. This report investigates the practical application of the PRLO platform in addressing real-world core design challenges, supporting AI efforts, and contrasting outcomes with those derived from heuristic or conventional algorithms.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

New signature method for identifying organic material in atmosphere and water samples

The levels of plastic contamination in the earth’s oceans have steadily increased over the past century, creating a threat to marine life and increasing climate change. Several methods have been developed over the past decade to try to determine the amount and accumulation rate of plastic impurities in the ecosystem. These methods have proven promising but suffer from long measurement times, bulky non-mobile systems, and sample degradation. We propose a smaller, faster system that employs an electron beam to examine seawater samples for polyethylene contamination levels. This process generates a full electron and photon energy spectrum analyses based on the subatomic particles generated from electron interactions. Our simulations have already been developed based on the known molecular composition of seawater and polyethylene, showing the possibility of discerning molecular plastics from microorganisms. With a system the size of a suitcase, this system would be easily deployable to remote locations around the world or installed as a monitoring system for manufacturing facilities. This concept could lead to a new methodology for the science of signatures and be applied to other biological hazard investigations, such as general virus detection.

43 PARTICLE ACCELERATORS↗

Demonstration of the Plant Fuel Reload Process Optimization for an Operating PWR

The United States (U.S.) nuclear industry is facing a strong challenge to maintain regulatory-required levels of safety while ensuring economic competitiveness to stay in business. Safety remains a key parameter for all aspects related to the operation of light water reactor (LWR) nuclear power plants (NPPs) and can be achieved more economically by using a risk-informed ecosystem such as that being developed by the Risk-Informed Systems Analysis (RISA) Pathway under the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program. The LWRS Program is promoting a wide range of research and development (R&D) activities with the goal to maximize both the safety and economically efficient performance of NPPs through improved scientific understanding, especially given that many plants are considering second license renewal. The RISA Pathway has two main goals: (1) the deployment of methodologies and technologies that enable better representation of safety margins and the factors that contribute to cost and safety; and (2) the development of advanced applications that enable cost-effective plant operation. This report summarizes the research outcomes in FY-2021, which the project progressed from the planning and methodology development phase to the early demonstration phase. The highlights of these activities are: (1) the development of a multi-objective optimization process using Genetic Algorithms (GAs); (2) the development and test of an approach for optimization process acceleration using artificial intelligence (AI) that significantly reduces the computational burden; (3) the demonstration of the fuel reload optimization framework for a generic pressurized water reactor (PWR); and (4) the demonstration of limiting design basis accident (DBA) scenarios for evaluation of the transition from deterministic to risk-informed approach for fuel reload optimization.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Residual-based error correction for neural operator accelerated infinite-dimensional Bayesian inverse problems

We explore using neural operators, or neural network representations of nonlinear maps between function spaces, to accelerate infinite-dimensional Bayesian inverse problems (BIPs) with models governed by nonlinear parametric partial differential equations (PDEs). Neural operators have gained significant attention in recent years for their ability to approximate the parameter-to-solution maps defined by PDEs using as training data solutions of PDEs at a limited number of parameter samples. The computational cost of BIPs can be drastically reduced if the large number of PDE solves required for posterior characterization are replaced with evaluations of trained neural operators. However, reducing error in the resulting BIP solutions via reducing the approximation error of the neural operators in training can be challenging and unreliable. We provide an a priori error bound result that implies certain BIPs can be ill-conditioned to the approximation error of neural operators, thus leading to inaccessible accuracy requirements in training. To reliably deploy neural operators in BIPs, we consider a strategy for enhancing the performance of neural operators: correcting the prediction of a trained neural operator by solving a linear variational problem based on the PDE residual. We show that a trained neural operator with error correction can achieve a quadratic reduction of its approximation error, all while retaining substantial computational speedups of posterior sampling when models are governed by highly nonlinear PDEs. The strategy is applied to two numerical examples of BIPs based on a nonlinear reaction–diffusion problem and deformation of hyperelastic materials. We demonstrate that posterior representations of the two BIPs produced using trained neural operators are greatly and consistently enhanced by error correction.

97 MATHEMATICS AND COMPUTING↗

US DOE Office of Technology Innovation and Development – Integration of the EM R&D Program in 2012 and Beyond

Applied research and technology development has the potential to accelerate environmental cleanup and reduce the cost for cleanup and closure of U.S. Department of Energy (DOE) legacy waste sites throughout the United States. Providing the scientific understanding, knowledge, and technologies to enable successful completion of the DOE Office of Environmental Management (EM) mission, the Technology Innovation and Development program is transforming science and innovation into practical solutions for environmental cleanup. Through integration, collaboration, and communication with DOE partner organization, DOE site managers and contractors, these technologies will reduce human health and environmental risk, cost, and time associated with cleanup and closure. The Office of Technology Innovation and Development (OTID) focused efforts in fiscal year 2011 (FY 2011) to a proactive, visionary program balance with integrated, cross-disciplinary applied research and technology development activities. This transition provides the necessary scientific and technical advancements to address near-term needs. In addition, it fills the critical role in providing scientific approaches and advanced technologies that look beyond today’s known needs and requirements to provide innovative technologies to make the necessary long-term changes required to facilitate cleanup and bring sites to closure. The outcomes and impacts of this strategy are summarized in the Impact Plan, which describes potential reduction in life-cycle costs through the development and deployment of advanced technologies supporting EM needs associated with waste processing, groundwater and soil remediation, deactivation and decommissioning, and spent nuclear fuel and materials disposition. Additionally, the OTID International Program Strategic Plan 2010-2015 (DOE 2010a) outlines cooperation and collaboration with the international community that has similar nuclear legacy management experience and expertise to foster transfer of best science practices being used in the field.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

US DOE Office of Technology Innovation and Development - Integration of the EM R and D Program in 2012 and Beyond - 12537

Applied research and technology development has the potential to accelerate environmental cleanup and reduce the cost for cleanup and closure of U.S. Department of Energy (DOE) legacy waste sites throughout the United States. Providing the scientific understanding, knowledge, and technologies to enable successful completion of the DOE Office of Environmental Management (EM) mission, the Technology Innovation and Development program is transforming science and innovation into practical solutions for environmental cleanup. Through integration, collaboration, and communication with DOE partner organization, DOE site managers and contractors, these technologies will reduce human health and environmental risk, cost, and time associated with cleanup and closure. The Office of Technology Innovation and Development (OTID) focused efforts in fiscal year 2011 (FY 2011) to a proactive, visionary program balance with integrated, cross-disciplinary applied research and technology development activities. This transition provides the necessary scientific and technical advancements to address near-term needs. In addition, it fills the critical role in providing scientific approaches and advanced technologies that look beyond today's known needs and requirements to provide innovative technologies to make the necessary long-term changes required to facilitate cleanup and bring sites to closure. The outcomes and impacts of this strategy are summarized in the Impact Plan, which describes potential reduction in life-cycle costs through the development and deployment of advanced technologies supporting EM needs associated with waste processing, groundwater and soil remediation, deactivation and decommissioning, and spent nuclear fuel and materials disposition. Additionally, the OTID International Program Strategic Plan 2010-2015 outlines cooperation and collaboration with the international community that has similar nuclear legacy management experience and expertise to foster transfer of best science practices being used in the field. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Reactor design and integration with product detection to accelerate screening of electrocatalysts for carbon dioxide reduction

Identifying new catalyst materials for complex reactions such as the electrochemical reduction of CO 2 poses substantial instrumentation challenges due to the need to integrate reactor control with electrochemical and analytical instrumentation. Performing accelerated screening to enable exploration of a broad span of catalyst materials poses additional challenges due to the long time scales associated with accumulation of reaction products and the detection of the reaction products with traditional separation-based analytical methods. The catalyst screening techniques that have been reported for combinatorial studies of (photo)electrocatalysts do not meet the needs of CO 2 reduction catalyst research, prompting our development of a new electrochemical cell design and its integration to gas and liquid chromatography instruments. To enable rapid chromatography measurements while maintaining sensitivity to minor products, the electrochemical cell features low electrolyte and head space volumes compared to the catalyst surface area. Additionally, the cell is operated as a batch reactor with electrolyte recirculation to rapidly concentrate reaction products, which serves the present needs for rapidly detecting minor products and has additional implications for enabling product separations in industrial CO 2 electrolysis systems. To maintain near-saturation of CO 2 in aqueous electrolytes, we employ electrolyte nebulization through a CO 2 -rich headspace, achieving similar gas-liquid equilibration as vigorous CO 2 bubbling but without gas flow. The instrument is demonstrated with a series of electrochemical experiments on an Au-Pd combinatorial library, revealing non-monotonic variations in product distribution with respect to catalyst composition. The highly integrated analytical electrochemistry system is engineered to enable automation for rapid catalyst screening as well as deployment for a broad range of electrochemical reactions where product distribution is critical to the assessment of catalyst performance.

47 OTHER INSTRUMENTATION↗

Thermomechanical fatigue resistance of low temperature solder for multiwire interconnects in photovoltaic modules

Novel interconnect technologies leveraging low melting temperature solders, such as multiwire interconnects, are being deployed in photovoltaic (PV) modules for improved reliability through interconnect redundancy and lower thermal loads during interconnection and lamination. However, the equivalency of standardized accelerated testing to field conditions has not yet been established for these emerging technologies. In this study, the thermomechanical fatigue resistance of low temperature solder alloys is investigated and compared to that of conventional SnPb to assess the acceleration behavior of these alloys. While InSn is shown to have sufficient thermomechanical fatigue resistance on the order of that of SnPb, these results indicate Sn–Bi alloys may have poor thermomechanical fatigue resistance at field conditions. The results also show that Sn–Bi alloys have thermal cycling acceleration factors of less than one. This indicates that the standardized accelerated thermal cycling test, such as that in IEC 61215, will produce misleading results for Sn–Bi alloys and that unique testing is required for this PV module architecture. Though accelerated thermal cycling may be a meaningful qualification test for SnPb solder joints, these results suggest that mechanical loading may be a more appropriate test for Sn–Bi multiwire interconnects. This is due to the distinct processing and geometry of multiwire interconnects which may allow for mechanical, rather than strictly metallurgical interconnections.

14 SOLAR ENERGY↗

Tuning Film Stresses for Open-Air Processing of Stable Metal Halide Perovskites

Challenges to upscaling metal halide perovskites (MHPs) include mechanical film stresses that accelerate degradation, dominate at the module scale, and can lead to delamination or fracture. In this work, we demonstrate open-air blade coating of single-step coated perovskite as a scalable method to control residual film stress after processing and introduce beneficial compression in the thin film with the use of polymer additives such as gellan gum and corn starch. The optoelectronic properties of MHP films with compression are improved with higher photoluminescence yields. MHP film stability is significantly improved under compression, under humidity, heat, and thermal cycling. By measuring the evolution of film stresses, we demonstrate for the first time that stress relaxation occurs in MHP films with tensile stress that correlates with film degradation. Finally, this discovery of a new mechanism underpinning MHP degradation shows that film stress can be used as a parameter to screen MHP devices and modules for quality control before deployment as a design for reliability criterion.

14 SOLAR ENERGY↗