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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 217 records · Page 12

A Wrapper to Use a Machine-Learning-Based Algorithm for Earthquake Monitoring

Seismology is one of the main sciences used to monitor volcanic activity worldwide. Fast, efficient, and accurate seismicity detectors are crucial to assess the activity level of a volcano in near–real time and to issue timely warnings. Traditional real–time seismic processing software uses phase onset pickers followed by a phase association algorithm to declare an event and estimate its location. The pickers typically do not identify whether the detected phase is a P or S arrival, which can have a negative impact on hypocentral location quality and complicates phase association. We implemented the deep–neural–network–based method PhaseNet to identify in real time P and S seismic waves on data from one– and three–component seismometers. We tuned the Earthworm binder_ew associator module to use the phase identification from PhaseNet to detect and locate the events, which we archive in a SeisComP3 database. We assessed the performance of the algorithm by comparing the results with existing catalogs built to monitor seismic and volcanic activity in Mayotte and the Lesser Antilles region. Our algorithm, which we refer to as PhaseWorm, showed promising results in both contexts and clearly outperformed the previous automatic method implemented in Mayotte. As a result, this innovative real–time processing system is now operational for seismicity monitoring in Mayotte and Martinique.

58 GEOSCIENCES↗

Battery‐Grade Lithium Materials: Virgin Production and Recycling, a Techno‐Economic Comparison

Lithium has been identified as an essential mineral to the economic and national security of the United States. It is vital for rechargeable batteries that surround us daily from the personal electronics to large-scale energy storage. With a comprehensive techno-economic analysis, the cost of battery-grade lithium compounds production, i.e., lithium carbonate (LC) is evaluated and lithium hydroxide monohydrate (LHM), from both virgin (spodumene ore and brine) and recycled feedstocks (spent lithium-ion batteries). The goal of this study is to inform about the economics of lithium compounds production with comprehensive insights into differences in manufacturing routes and pave a pathway to explore more innovative, domestic manufacturing processes in future for their cost competitiveness and environmental impact. The study includes details on mining and extraction operations as well as unit level operation in the refining process. Moreover, process level information has been collected for pyrometallurgical and hydrometallurgical battery recycling routes. This analysis shows that brine and direct lithium extraction are the cheapest pathways to produce LC or LHM (between $\$3.39$ and 6.20 kg −1 ). The cost of production in the ore and recycling routes can range between $\$4.17$ and $\$53.41$ kg −1 and is highly depending on capital equipment investment, plant location, and the price of spodumene concentrate SC6.0.

battery recycling↗

Acid Etching‐Driven Self‐Assembly of Mn‐Shell Inducing Rock‐Salt Phase for Enhanced Single‐Crystal Ni‐Rich Cathodes

With the wide adoption of Li‐ion batteries, Ni‐rich cathode is considered as one of the most promising candidates of cathodes due to its high energy density and low cost. However, stability decreased with increasing Ni content in the Ni‐rich cathode. To solve this bottleneck, many strategies, such as coating, doping, surface modification, and special morphologies, have been developed. Herein, we introduce a groundbreaking approach for enhancing Ni‐rich cathode through an innovative acid etching process that promotes Mn shell self‐assembly, inducing a rock‐salt phase on the surface. This method not only simplifies the Ni‐rich cathode modification process, but also significantly improves the structural stability and electrochemical performance of Ni‐rich cathode. Our findings demonstrate that developed single‐crystal Ni‐rich cathode shows 3–34 % better stability compared to both commercial modified Ni‐rich cathode and unmodified counterparts. The unique Mn shell effectively mitigates reversible phase shifts during cycling, contributing to a remarkable enhancement in cycling stability. Additionally, this novel fabrication technique paves the way for cost‐effective production of high‐performance cathode materials, offering substantial benefits for lithium‐ion battery technology. And this study proves the potential of this method in advancing the design and development of durable, high‐capacity cathode materials for next‐generation batteries.

Ni-rich cathode↗

Urban mining from biomass, brine, sewage sludge, phosphogypsum and e-waste for reducing the environmental pollution: Current status of availability, potential, and technologies with a focus on LCA and TEA

We discuss how rapid industrialization, improved standards of living, growing economies and ever-increasing population has led to the unprecedented exploitation of the finite and non-renewable resources of minerals in past years. It was observed that out of 100 BMT of raw materials processed annually only 10% is recycled back. This has resulted in a strenuous burden on natural or primary resources of minerals (such as ores) having limited availability. Moreover, severe environmental concerns have been raised by the huge piles of waste generated at landfill sites. To resolve these issues, ‘Urban Mining’ from waste or secondary resources in a Circular Economy’ concept is the only sustainable solution. The objective of this review is to critically examine the availability, elemental composition, and the market potential of the selected secondary resources such as lignocellulosic/algal biomass, desalination water, sewage sludge, phosphogypsum, and e-waste for minerals sequestration. This review showed that, secondary resources have potential to partially replace the minerals required in different sectors such as macro and microelements in agriculture, rare earth elements (REEs) in electrical and electronics industry, metals in manufacturing sector and precious elements such as gold and platinum in ornamental industry. Further, inputs from the selected life cycle analysis (LCA) & techno economic analysis (TEA) were discussed which showed that although, urban mining has a potential to reduce the greenhouse gaseous (GHG) emissions in a sustainable manner however, process improvements through innovative, novel and cost-effective pathways are essentially required for its large-scale deployment at industrial scale in future.

54 ENVIRONMENTAL SCIENCES↗

Dynamic machine learning-based optimization algorithm to improve boiler efficiency

With decreasing computational costs, improvement in algorithms, and the aggregation of large industrial and commercial datasets, machine learning is becoming a ubiquitous tool for process and business innovations. Machine learning is still lacking applications in the field of dynamic optimization for real-time control. This work presents a novel framework for performing constrained dynamic optimization using a recurrent neural network model combined with a metaheuristic optimizer. The framework is designed to augment an existing control system and is purely data-driven, like most industrial Model Predictive Control applications. Several recurrent neural network models are compared as well as several metaheuristic optimizers. Hyperparameters and optimizer parameters are tuned with parameter sweeps, and the resulting values are reported. Further, the best parameters for each optimizer and model combination are demonstrated in closed-loop control of a dynamic simulation, and several recommendations are made for generalizing this framework to other systems. Up to 0.953% improvement is realized over the non-optimized case for a simulated coal-fired boiler. While this is not a large improvement in percentage, the total economic impact is $991,000 per year, and this study builds a foundation for future machine learning with dynamic optimization.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Desalination for a circular water economy

Today's water systems are enabled by ample fresh water sources, low-cost centralized treatment, and facile wastewater disposal. Climatic change, aging infrastructure, and source water contamination have exposed the vulnerabilities of this linear water paradigm. While seawater desalination enables coastal communities to augment their supply, more broadly securing water systems for municipal, industrial, and agricultural water users will require distributed desalination and fit-for-purpose reuse of nontraditional water sources. Our linear water economy must evolve into a resilient circular water economy, where water is continuously reused and “contaminants” become the feedstocks for other economically valuable processes. Additionally, technology innovation is needed to deliver autonomous, precise, resilient, intensified, modular, and electrified desalination systems that reduce the cost, improve the performance, and enhance the resilience of nontraditional water reuse systems. Meanwhile, strong federal leadership and coordination is needed to accelerate desalination research, promote information gathering efforts to direct technology development, and create an expanded role for non-profit organizations in knowledge dissemination.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Automated annotation of scientific texts for ML-based keyphrase extraction and validation

Advanced omics technologies and facilities generate a wealth of valuable data daily; however, the data often lack the essential metadata required for researchers to find, curate, and search them effectively. The lack of metadata poses a significant challenge in the utilization of these data sets. Machine learning (ML)–based metadata extraction techniques have emerged as a potentially viable approach to automatically annotating scientific data sets with the metadata necessary for enabling effective search. Text labeling, usually performed manually, plays a crucial role in validating machine-extracted metadata. However, manual labeling is time-consuming and not always feasible; thus, there is a need to develop automated text labeling techniques in order to accelerate the process of scientific innovation. This need is particularly urgent in fields such as environmental genomics and microbiome science, which have historically received less attention in terms of metadata curation and creation of gold-standard text mining data sets. In this paper, we present two novel automated text labeling approaches for the validation of ML-generated metadata for unlabeled texts, with specific applications in environmental genomics. Our techniques show the potential of two new ways to leverage existing information that is only available for select documents within a corpus to validate ML models, which can then be used to describe the remaining documents in the corpus. The first technique exploits relationships between different types of data sources related to the same research study, such as publications and proposals. The second technique takes advantage of domain-specific controlled vocabularies or ontologies. In this paper, we detail applying these approaches in the context of environmental genomics research for ML-generated metadata validation. Our results show that the proposed label assignment approaches can generate both generic and highly specific text labels for the unlabeled texts, with up to 44% of the labels matching with those suggested by a ML keyword extraction algorithm.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Functional Divergence in a Multi-gene Family Is a Key Evolutionary Innovation for Anaerobic Growth in Saccharomyces cerevisiae

The amplification and diversification of genes into large multi-gene families often mark key evolutionary innovations, but this process often creates genetic redundancy that hinders functional investigations. When the model budding yeast Saccharomyces cerevisiae transitions to anaerobic growth conditions, the cell massively induces the expression of seven serine/threonine-rich anaerobically-induced cell wall mannoproteins (anCWMPs): TIP1, TIR1, TIR2, TIR3, TIR4, DAN1, and DAN4. Here, we show that these genes likely derive evolutionarily from a single ancestral anCWMP locus, which was duplicated and translocated to new genomic contexts several times both prior to and following the budding yeast whole genome duplication (WGD) event. Based on synteny and their phylogeny, we separate the anCWMPs into four gene subfamilies. To resolve prior inconclusive genetic investigations of these genes, we constructed a set of combinatorial deletion mutants to determine their contributions toward anaerobic growth in S. cerevisiae. We found that two genes, TIR1 and TIR3, were together necessary and sufficient for the anCWMP contribution to anaerobic growth. Overexpressing either gene alone was insufficient for anaerobic growth, implying that they encode non-overlapping functional roles in the cell during anaerobic growth. We infer from the phylogeny of the anCWMP genes that these two important genes derive from an ancient duplication that predates the WGD event, whereas the TIR1 subfamily experienced gene family amplification after the WGD event. Taken together, the genetic and molecular evidence suggests that one key anCWMP gene duplication event, several auxiliary gene duplication events, and functional divergence underpin the evolution of anaerobic growth in budding yeasts.

59 BASIC BIOLOGICAL SCIENCES↗

Development of Stable Solid Oxide Electrolysis Cells for Low-Cost Hydrogen Production

The project objective was to demonstrate a solid oxide cell-based steam electrolysis stack that exhibits robustness, reliability, endurance, hydrogen purity, and produces hydrogen at elevated pressure of 2 to 3 bar. Innovative materials and processing methods were evaluated to improve degradation characteristics. Performance improvement focused on nearly all layers involved in the cell and stack assembly. Primary attention was paid to zirconia-ceria interface resistance control via sintering optimization and decrease in degradation from the oxygen electrode by evaluating low strontium (Sr) or Sr-free composition for both the oxygen electrode and current collection layer. Stack robustness was addressed by validating redox tolerance of fuel electrode, confirming capability of cells to survive repeated thermal cycles, studying the effect of pressure on performance and degradation, evaluating the effect of contamination on fuel and oxygen electrode performance and degradation, and identifying mitigation strategies to improve performance. The characterization included evaluation of electrochemical performance and stability followed by microstructural analysis. At the cell level, performance and stability improvements were achieved by incorporating a Sr-free oxygen electrode and a denser oxygen electrode barrier layer. At the stack level, pressurized operation reduces demand on first stage compression, the redox tolerant fuel electrode mitigates risk from service interruptions, and improvements to interconnect coating alleviate chromium (Cr) contamination effects. The denser barrier layer was achieved by adding a sintering aid to the samaria-doped ceria (SDC) composition that reduced sintering temperature by 150 °C. The resulting density was on par with the baseline SDC barrier layer density and the lower sintering temperature resulted in less resistive phase formation during sintering. Button cell tests did not demonstrate a change in performance when exposed to silicon (Si) or manganese (Mn) impurities to the fuel electrode and Cr impurity to the oxygen electrode. More detailed study however is warranted. The project addressed SOEC performance and stability at the cell and stack levels through a systematic approach to known sources of degradation that were combined and tested in three stack tests using an electrolyte supported cell design to allow for evaluation of a variety of fuel and oxygen electrode compositions. STK-82 and STK-83 had identical compositions. STK-100 incorporated the best materials and processing variables developed under this and concurrent projects, and was tested at elevated pressure in steam electrolysis. • STK-82 recovered performance after redox and thermal cycling, demonstrating the robustness of the stack and seals. It exhibited stable performance in testing for 500 hours in SOEC mode, followed by 300 hours of cycling between SOEC and SOFC tests. Degradation during SOEC operation was 1.8 %/ 1,000 hours. • STK-83 generated hydrogen at >80% steam conversion, and oxygen above 98.5 % purity during pressurized operation. Both hydrogen and oxygen were generated at 3 barg pressure without the use of a pressure vessel. In addition to balanced pressure, electrolysis operation at 1 bar differential pressure across anode and cathode was also demonstrated to substantial the robustness of the cell and seal. • STK-100 measured at initial ambient pressure conditions showed an area specific resistance of 1.1 ohm-cm 2 , and STK-83 had 1.3 ohm-cm 2 .

08 HYDROGEN↗

Adroit Materials Final Scientific/Technical Report kV-class GaN-based Junction Barrier Schottky diodes using ion implantation

The primary aim of this research was to develop GaN-based Junction Barrier Schottky (JBS) diodes using an innovative ion implantation process previously established in ARPA-E funded projects. The central focus of our proposed technology revolves around selective area p-type doping, accomplished through the implantation of Mg ions. This approach builds upon our successes in the ARPA-E PNDIODES program, advancing towards commercial device integration. Selective area p-doping plays a pivotal role in realizing the next generation of GaN-based power devices, capable of significantly reducing the carbon footprint in the United States by several million tons. While ion implantation is a well-established technique for achieving selective area doping in SiC and Si materials, its feasibility in GaN had not been demonstrated until now. To fabricate high voltage GaN JBS diodes, we initially created thick n-type drift layers with high carrier concentrations ranging from 5×1015 cm-3 to 2×1016 cm-3 and very high mobilities. Subsequently, Mg ions were selectively implanted to form p-type islands within the n-type drift layer. To reduce electric field crowding at the edge of the diode and to achieve high breakdown voltage, junction edge termination (JTE) and floating field rings (FFRs) were formed using Mg implantation. A high temperature, high-pressure post-implantation annealing process was carried out to activate the implanted Mg ions. As a result, we were able to demonstrate GaN JBS diodes with a breakdown voltage of 915 V and an on-resistance of 0.6 mΩ·cm2. These diodes exhibited a forward bias current density of 1 kA/cm2 at 1.5 V. Subsequently, we achieved GaN JBS diodes with a remarkable breakdown voltage of 1900 V and an on-resistance of 1.9 mΩ·cm2, capable of sustaining a forward bias current density of 0.5 kA/cm2 at 1.5 V. Importantly, the ON and OFF state performance of these GaN JBS diodes surpassed that of Si and SiC-based power diodes reported in existing literature. Lastly, we successfully grew 60 μm thick GaN:Si layers using HVPE with a carrier concentration of approximately 3 to 5×1015 cm-3. Based on simulation and empirical data these devices represent 5 kV GaN JBS power diodes, leveraging the developed processes in this project.

36 MATERIALS SCIENCE↗

Simulation Tools for Characterizing Stress Distribution in Laser Welded Dissimilar Joints

This project focuses on developing a thermo-metallurgical-mechanical modeling method to accurately predict the microstructural evolution and residual stress in laser welding between dissimilar metals, such as HSLA steel and high carbon equivalent (CE) gear steel. The method leverages a comprehensive material database to model the temperature and rate dependent phase transformations, along with their associated effects on material properties, such as thermal expansion and flow stress, throughout the welding process. A key innovation is the incorporation of phase transformation and phase-specific properties, which enhances the accuracy of residual stress predictions. The mixture material in the fusion zone due to the dissimilar metals will also be addressed in the numerical model. This is especially critical in scenarios involving phase transformations in the fusion zone and heat-affected zone (HAZ), where the phase changes can induce substantial residual stress variations. The material database has been generated using JMatPro. The modeling approach is implemented through a custom User Material (UMAT) subroutine, executed with the commercial finite element software Abaqus.

36 MATERIALS SCIENCE↗

Develop an efficient and cost-effective novel anaerobic digestion system producing high purity of methane from diverse waste biomass

This project focuses on developing an advanced, intensified anaerobic digestion system aimed at transforming the treatment and conversion of organic wastes into valuable products, specifically renewable natural gas. The motivation for this research stems from the limitations of conventional anaerobic digestion technologies, which often face challenges such as long retention times, high operational costs, and incomplete organic material degradation. The new technology called Intensified Versatile Anaerobic Digestion (IVAD), is developed to address these challenges by incorporating innovative reactors and processes that enhance the overall efficiency and output of anaerobic digestion. The significance of this project lies in its potential to revolutionize waste management practices and waste biomass utilization. The IVAD system integrates a hyperthermophilic anaerobic acidification reactor, a hydrothermal treatment (HTT) unit, and both thermophilic and mesophilic methanogenic reactors. This combination enables a higher rate of organic breakdown and energy recovery, resulting in faster processing times, reduced reactor sizes, and lower operational costs compared to traditional systems. Key data include an increase in methane productivity to 1.18 m 3 /m 3 /day, a significant improvement compared to the baseline technology’s 0.64 m 3 /m 3 /day. Additionally, the IVAD system achieves a 45% reduction in levelized cost of energy (LCOE), down to $\$$10.04/MMBTU, and an energy return on investment (EROI) of 3.19, representing an 87% increase over baseline levels. Technical and economic analyses highlight that the IVAD system significantly reduces hydraulic retention time (HRT) and solid retention time (SRT). The HRT for the HTT reactor can be reduced from 1 hour to 0.5 hours, while decoupling SRT from HRT in the anaerobic acidification reactor (AAR) allows for further reductions. These design optimizations lead to smaller reactor volumes, cutting down equipment and construction costs. Despite these advancements, energy consumption remains comparable to conventional methods due to a novel heat recovery strategy, enhancing overall process productivity. The system also achieves in-situ CO 2 removal and ammonia stripping features, resulting in biogas with a methane purity level of 75%, and produces high-quality nitrogen fertilizer as an additional by-product. Public benefits of the IVAD system are substantial, contributing to sustainable waste management and renewable energy production. By providing a scalable solution that can be adopted by dairy farms and similar agricultural operations, the IVAD system helps reduce waste, produce renewable natural gas (RNG) suitable for transportation fuel, and generate fertilizer, supporting a circular economy. This project plays a role in achieving broader environmental objectives by mitigating greenhouse gas emissions and promoting energy independence. Additionally, it offers a pathway for farmers to lower operational costs while adopting practices that are both environmentally sustainable and economically advantageous.

03 NATURAL GAS↗

Simulation Tools for Characterizing Stress Distribution in Laser Welded Dissimilar Joints

This project focuses on developing a thermo-metallurgical-mechanical modeling method to accurately predict the microstructural evolution and residual stress in laser welding between dissimilar metals, such as HSLA steel and high carbon equivalent (CE) gear steel. The method leverages a comprehensive material database to model the temperature and rate dependent phase transformations, along with their associated effects on material properties, such as thermal expansion and flow stress, throughout the welding process. A key innovation is the incorporation of phase transformation and phase-specific properties, which enhances the accuracy of residual stress predictions. The mixture material in the fusion zone due to the dissimilar metals will also be addressed in the numerical model. This is especially critical in scenarios involving phase transformations in the fusion zone and heat-affected zone (HAZ), where the phase changes can induce substantial residual stress variations. The material database has been generated using JMatPro. The modeling approach is implemented through a custom User Material (UMAT) subroutine, executed with the commercial finite element software Abaqus.

36 MATERIALS SCIENCE↗

Urban development applications project. Urban technology transfer study

Technology transfer is defined along with reasons for attempting to transfer technology. Topics discussed include theoretical models, stages of the innovation model, communication process model, behavior of industrial organizations, problem identification, technology search and match, establishment of a market mechanism, applications engineering, commercialization, and management of technology transfer.

Source record↗

An automated oxide and diffusion facility for IC's

Report discusses totally-automated oxidation and diffusion facility for fabricating IC's. Several innovations are demonstrated: process controller specifically designed for semiconductor processing; automatic loading system to accept wafers from air track, insert them in quartz carrier, and place carrier on paddle for insertion into furnace; automatic unloading of wafers back onto air track; and boron diffusion using diborane.

Kennedy, B. W.↗

Considerations of technology transfer barriers in the modification of strategic superalloys for aircraft turbine engines

A typical innovation-to-commercialization process for the development of a new hot section gas turbine material requires one to two decades with attendant costs in the tens of millions of dollars. This transfer process is examined to determine the potential rate-controlling steps for introduction of future low strategic metal content alloys or processes. Case studies are used to highlight the barriers to commercialization as well as to identify the means by which these barriers can be surmounted. The opportunities for continuing joint government-university-industry partnerships in planning and conducting strategic materials R&D programs are also discussed.

Stephens, J. R.↗

Report of the In Situ Resources Utilization Workshop

The results of a workshop of 50 representatives from the public and private sector which investigated the potential joint development of the key technologies and mechanisms that will enable the permanent habitation of space are presented. The workshop is an initial step to develop a joint public/private assessment of new technology requirements of future space options, to share knowledge on required technologies that may exist in the private sector, and to investigate potential joint technology development opportunities. The majority of the material was produced in 5 working groups: (1) Construction, Assembly, Automation and Robotics; (2) Prospecting, Mining, and Surface Transportation; (3) Biosystems and Life Support; (4) Materials Processing; and (5) Innovative Ventures. In addition to the results of the working groups, preliminary technology development recommendations to assist in near-term development priority decisions are presented. Finally, steps are outlined for potential new future activities and relationships among the public, private, and academic sectors.

Fairchild, Kyle↗