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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

Advancements in Manufacturing of High-Performance Perovskite Solar Cells and Modules Using Printing Technologies

Perovskite photovoltaic technology carries immense opportunity for the solar industries because of its remarkable efficiency and prospect for cost-effective production. However, the successful deployment of perovskite solar modules (PSMs) in the solar market necessitates tackling stability-based obstacles, scalability, and environmental considerations. This paper unveils a comprehensive examination of the cutting-edge advancements in the manufacturing of perovskite solar cells (PSCs) and modules, with an emphasis on high-speed, large-area printing. The paper underscores the substantial progress achieved in printed PSCs and PSMs, demonstrating promising electrical performance and long-term device durability. This review paper categorizes printing techniques compatible with large-area high-speed manufacturing into three distinct families: blade coating, slot die coating, and screen printing, as these common printing practices offer precise control, scalability, cost-effectiveness, high resolution, and efficient material usage. Additionally, this paper presents an in-depth investigation and comparison of superior PSCs and PSMs fabricated by printing on power conversion efficiency (PCE), stability, and scalability.

14 SOLAR ENERGY↗

Progress in ITER ECE diagnostic design and integration

The ITER electron cyclotron emission (ECE) diagnostic system has primary roles in providing measurements of the core electron temperature profile and the electron temperature fluctuation associated with the neoclassical tearing modes. The ITER ECE system includes a radial and oblique line-of-sight. Four 43-meter long low-loss transmission lines (TLs) are designed to transmit millimeter wave power in the frequency range of 70–1000 GHz in both X- and O-mode polarization from the port plug to the ECE instrumentation room in the diagnostic building. The measurement instrumentation includes two Fourier transform spectrometer (FTS) systems and two radiometer systems. The Indian Domestic Agency (IN-DA) and United States Domestic Agency share the responsibility. The IN-DA scope excluding instrumentation and control has passed its preliminary design review and is progressing towards the final design review (FDR). In parallel, the diagnostic integration in different areas is ongoing. Furthermore, several captive components for the TLs have passed FDR and will be manufactured for installation in the tokamak building soon. A peer review meeting has been held on the prototype hot calibration source, and its integration and new thermal analysis in the diagnostic shield module are continuing. A prototype TL is being tested. A prototype polarizing Martin-Puplett type FTS, operating in the frequency range 70–1000 GHz, features an in-vacuo fast scanning mechanism and a cryo-cooled dual-channel THz detector system. Its performance has been assessed in detail against ITER requirements.

47 OTHER INSTRUMENTATION↗

A Review of Carbon-14 Removal by Ion Exchange Resins and Potential Remediation Application in the 100-K Area

During operations at the U.S. Department of Energy Hanford Site, releases of chemical and radioactive waste resulted in contamination of the soil and groundwater beneath portions of the site, including inadvertent releases of carbon-14 in the 100-K Area. Ongoing environmental cleanup efforts in the 100-K Area are focused on hexavalent chromium [Cr(VI)] and thus have not yet addressed the two carbon-14 groundwater plumes.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Interactions Between Diabetes Mellitus and Osteoarthritis: From Animal Studies to Clinical Data

Diabetes mellitus (DM) and osteoarthritis (OA) are commonly known metabolic diseases that affect a large segment of the world population. These two conditions share several risk factors such as obesity and aging; however, there is still no consensus regarding the direct role of DM on OA development and progression. Interestingly, both animal and human studies have yielded conflicting results, with some showing a significant role for DM in promoting OA, while others found no significant interactions between these conditions. In this review, we will discuss preclinical and clinical data that assessed the interaction between DM and OA. We will also discuss possible mechanisms associated with the effect of high glucose on the articular cartilage and chondrocytes. An emerging theme dominates the breath of published work in this area: most of the studies discussed in this review do not take into consideration the role of other factors such as the type of diabetes, age, biological sex, type of animal model, body mass index, and the use of pain medications when analyzing and interpreting data. Therefore, future studies should be more rigorous when designing experiments looking at DM and its effects on OA and should carefully account for these confounding factors, so that better approaches can be developed for monitoring and treating patients at risk of OA and DM.

59 BASIC BIOLOGICAL SCIENCES↗

PTSFA QA Review of Container Procurements: Information Use Procedure

The purpose of this Packaging and Transportation Safety Functional Area (PTSFA) procedure is to describe the process in which the PTSFA Quality Assurance Engineer (QAE) or designee reviews and approves the documentation associated with the procurements of containers to be used for onsite transfer or off-site transportation of hazardous materials and waste.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

A practical guide to quartz crystal microbalance with dissipation monitoring of thin polymer films

Quartz crystal microbalance with dissipation (QCM-D) monitoring is a powerful tool used to sensitively examine the real-time responses of polymer films to external responses. For example, the technique is commonly used to monitor film growth, material adsorption, thin film swelling, and ion exchange. With its rapidly expanding use, this review is intended to introduce new users to the basic principles of QCM-D, along with practical challenges and remedies specific to polymer thin films. For both new and experienced users, specific case studies are highlighted including layer-by-layer assembly, electrochemical QCM-D, swelling, sensing, and biological application. Finally, the review recommends future directions for research and areas of growth.

36 MATERIALS SCIENCE↗

New approaches to secondary metabolite discovery from anaerobic gut microbes

The animal gut microbiome is a complex system of diverse, predominantly anaerobic microbiota with secondary metabolite potential. These metabolites likely play roles in shaping microbial community membership and influencing animal host health. As such, novel secondary metabolites from gut microbes hold significant biotechnological and therapeutic interest. Despite their potential, gut microbes are largely untapped for secondary metabolites, with gut fungi and obligate anaerobes being particularly under-explored. To advance understanding of these metabolites, culture-based and (meta)genome-based approaches are essential. Culture-based approaches enable isolation, cultivation, and direct study of gut microbes, and (meta)genome-based approaches utilize in silico tools to mine biosynthetic gene clusters (BGCs) from microbes that have not yet been successfully cultured. In this mini-review, we highlight recent innovations in this area, including anaerobic biofoundries like ExFAB, the NSF BioFoundry for Extreme & Exceptional Fungi, Archaea, and Bacteria. These facilities enable high-throughput workflows to study oxygen-sensitive microbes and biosynthetic machinery. Such recent advances promise to improve our understanding of the gut microbiome and its secondary metabolism.

59 BASIC BIOLOGICAL SCIENCES↗

Machine learning in materials science: From explainable predictions to autonomous design

The advent of big data and algorithmic developments in the field of machine learning (and artificial intelligence, in general) have greatly impacted the entire spectrum of physical sciences, including materials science. Materials data, measured or computed, combined with various techniques of machine learning have been employed to address a myriad of challenging problems, such as, development of efficient and predictive surrogate models for a range of materials properties, screening and down-selection of novel candidate materials for targeted applications, new methodologies to improve and further expedite molecular and atomistic simulations, with likely many more important developments to come in the foreseeable future. While the applications thus far have provided a glimpse of the true potential data-enabled routes have to offer, it has also become clear that further progress in this direction hinges on our ability to understand, explain and rationalize findings of a machine learning model in light of the domain-knowledge. This focused review provides an overview of the main areas where machine learning has been widely and successfully used in materials science. Subsequently, a brief discussion of several techniques that have been helpful in extracting physically-meaningful insights, causal relationships and design-centric knowledge from materials data is provided. Finally, we identify some of the imminent opportunities and challenges that materials community faces in this exciting and rapidly growing field.

36 MATERIALS SCIENCE↗

Advancements in conventional and 3D printed feed spacers in membrane modules

Plate & frame and spiral-wound modules are used for gas separation, pervaporation, reverse osmosis, nanofiltration, ultrafiltration, microfiltration, electro-dialysis, electro-deionization, membrane distillation and forward osmosis membrane processes. Feed channel spacers are an integral part of both module types – providing mechanical support for a cross-flow channel through the module and, in most cases, promoting mixing to enhance mass transfer to reduce concentration polarization and fouling. However, enhanced mass transfer comes at a cost of increased hydraulic pressure losses and stagnant zones wherever a spacer filament touches a membrane surface. Further, these stagnant zones exacerbate membrane fouling and make cleaning more difficult. Efforts to improve feed spacer performance largely focus on adjusting the chemistry or geometry of the spacer to mitigate these challenges. Additive manufacturing (i.e. 3D printing) offers new degrees of freedom in feed spacer design and production, which opens up a new area of research in membrane technology. This review critically assesses the peer-reviewed literature on conventional net- or mesh-style feed spacers in addition to various novel spacer geometries and chemistries produced via 3D printing. We further review and evaluate conventional spacer manufacturing methods and discuss advantages and disadvantages of 3D printed spacers.

3D printing↗

From multivariate to functional data analysis: Fundamentals, recent developments, and emerging areas

Functional data analysis (FDA), which is a branch of statistics on modeling infinite dimensional random vectors resided in functional spaces, has become a major research area for Journal of Multivariate Analysis. We review some fundamental concepts of FDA, their origins and connections from multivariate analysis, and some of its recent developments, including multi-level functional data analysis, high-dimensional functional regression, and dependent functional data analysis. Here, we also discuss the impact of these new methodology developments on genetics, plant science, wearable device data analysis, image data analysis, and business analytics. Two real data examples are provided to motivate our discussions.

97 MATHEMATICS AND COMPUTING↗

Design and Challenges of Edge Computing ASICs on Front-End Electronics

In situ or hardware-embedded data processing of raw signals, close to their source, in radiation detectors is expected to provide dramatic improvements in data quality and volumes. However, the implementation of artificial neural networks (ANNs) in the front-end electronics, and the design of custom integrated circuits (ASICs), comes with challenges. In addition, detectors have to operate with limited power budget and implement complex functionalities in a very dense space. They often are exposed to extreme conditions as they work in high-radiation environments and/or cryogenic temperatures. This paper presents examples of applications and design methodologies for in-situ ANNs, along with the challenges of retaining the fidelity of the trained networks. For illustration, we use the problem of estimating the energy deposited by the radiation from digitized waveforms. The proposed implementation starts with an ML algorithm trained in Qkeras and eventually leads to an equivalent ASIC implementation. The associated design challenges in realizing energy and area efficient implementations in CMOS processes are reviewed. Novel approaches that employ hybrid technologies (combination of CMOS with memristors), in-memory computing models, and bio-inspired spiking neural networks are also highlighted

47 OTHER INSTRUMENTATION↗

Literature Review for Sensor Impact Evaluation and Verification Use Cases - Building Controls and Fault Detection and Diagnosis (FDD)

This report summarizes a comprehensive literature review for the selected sensor suites used in building controls and fault detection and diagnostics (FDD), which is a Q2 deliverable of the Sensor Impact Evaluation and Verification project. The project’s overarching goal is to develop a framework for investigating the impact of sensor deployment and configuration for building energy optimization, fault detection and diagnosis (FDD), occupants’ thermal comfort, and potential grid efficiency. While the first phase of the literature review performed in Q1 reviewed the current methods of various sensor selection and placements and their impact, this report focuses on high impactful potential use cases for the selected sensor suites in building control and FDD. The use cases identified in this literature review will be further investigated and be included in the final sensor impact evaluation framework. For the review, the multi-laboratory team reviewed 241 research papers, technical reports, and books to identify existing technologies, the potential impact on energy savings and thermal comfort, and future research opportunities for the selected use cases in building controls and FDD. Along with the literature review, the team conducted a series of interviews with experts in sensors and controls area to identify the state-of-art sensor technologies, and the most impactful use cases in controls and FDD areas. The interview results will also be incorporated with the findings from the literature review in the next quarter, and the final use cases to be evaluated will be selected.

47 OTHER INSTRUMENTATION↗

External Review Committee Report on the California Geological Survey

In May and June of 2021, the External Review Committee (ERC) assessed the activities and major programs of the California Geological Survey (CGS). The ERC reviewed materials from the five CGS program areas and upper management, as well as online presentations from program leaders and the California Department of Conservation (DOC), which oversees CGS.

58 GEOSCIENCES↗

Application of Systems Engineering Principles and Techniques in Biological Big Data Analytics: A Review

In the past few decades, we have witnessed tremendous advancements in biology, life sciences and healthcare. These advancements are due in no small part to the big data made available by various high-throughput technologies, the ever-advancing computing power, and the algorithmic advancements in machine learning. Specifically, big data analytics such as statistical and machine learning has become an essential tool in these rapidly developing fields. As a result, the subject has drawn increased attention and many review papers have been published in just the past few years on the subject. Different from all existing reviews, this work focuses on the application of systems, engineering principles and techniques in addressing some of the common challenges in big data analytics for biological, biomedical and healthcare applications. Specifically, this review focuses on the following three key areas in biological big data analytics where systems engineering principles and techniques have been playing important roles: the principle of parsimony in addressing overfitting, the dynamic analysis of biological data, and the role of domain knowledge in biological data analytics.

dynamic analysis↗

Catalysis: Volume 36 (Preface)

This volume reviews the extensive literature published in the area of microwave-assisted catalytic approaches for waste conversion, non-reductive CO2 conversion, CO₂ utilization, heterogeneous catalysis and its integration with solid oxide electrolysis cell (SOEC) systems for chemical production, mechanistic pathways in ethylene epoxidation.

CO2 utilization↗

Application of Mobile Energy Storage for Enhancing Power Grid Resilience: A Review

Natural disasters can lead to large-scale power outages, affecting critical infrastructure and causing social and economic damages. These events are exacerbated by climate change, which increases their frequency and magnitude. Improving power grid resilience can help mitigate the damages caused by these events. Mobile energy storage systems, classified as truck-mounted or towable battery storage systems, have recently been considered to enhance distribution grid resilience by providing localized support to critical loads during an outage. Compared to stationary batteries and other energy storage systems, their mobility provides operational flexibility to support geographically dispersed loads across an outage area. This paper provides a comprehensive and critical review of academic literature on mobile energy storage for power system resilience enhancement. As mobile energy storage is often coupled with mobile emergency generators or electric buses, those technologies are also considered in the review. Allocation of these resources for power grid resilience enhancement requires modeling of both the transportation system constraints and the power grid operational constraints. These aspects are discussed, along with a discussion on the cost–benefit analysis of mobile energy resources. The paper concludes by presenting research gaps, associated challenges, and potential future directions to address these challenges.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Prospects of Nanoscience with Nanocrystals: 2025 Edition

Abstract Nanocrystals (NCs) of various compositions have made important contributions to science and technology, with their impact recognized by the 2023 Nobel Prize in Chemistry for the discovery and synthesis of semiconductor quantum dots (QDs). Over four decades of research into NCs has led to numerous advancements in diverse fields, such as optoelectronics, catalysis, energy, medicine, and recently, quantum information and computing. The last 10 years since the predecessor perspective “Prospect of Nanoscience with Nanocrystals” was published in ACS Nano have seen NC research continuously evolve, yielding critical advances in fundamental understanding and practical applications. Mechanistic insights into NC formation have translated into precision control over NC size, shape, and composition. Emerging synthesis techniques have broadened the landscape of compounds obtainable in colloidal NC form. Sophistication in surface chemistry, jointly bolstered by theoretical models and experimental findings, has facilitated refined control over NC properties and represents a trusted gateway to enhanced NC stability and processability. The assembly of NCs into superlattices, along with two-dimensional (2D) photolithography and three-dimensional (3D) printing, has expanded their utility in creating materials with tailored properties. Applications of NCs are also flourishing, consolidating progress in fields targeted early on, such as optoelectronics and catalysis, and extending into areas ranging from quantum technology to phase-change memories. In this perspective, we review the extensive progress in research on NCs over the past decade and highlight key areas where future research may bring further breakthroughs.

Chemistry↗

Advanced Perovskite Solar Cells and Modules

The “Advanced perovskite Cells and Modules” research project was the final agreement focused on enhancing perovskite solar cell (PSC) technologies funded by the US Department of Energy's Solar Energy Technologies Office. The project was designed to address three crucial areas in PSC development: stability, manufacturability, and efficiency. The project was then structured around three main tasks, each targeting one of these strategic goals. The team of experienced researchers in these materials worked collaboratively to address the targets outlined in the technical work plan. building on existing PSC research while also exploring promising new concepts arising in the field. An overview of each primary task is summarized below: Task 1 Stability: This first task, aims to identify material characteristics and metrics that can help predict the primary degradation mechanisms impacting PSC stability. This involved developing specific device tests based on hypotheses regarding mechanisms impacting stability, including fast failure procedures to speed up PSC development and improvement. Various strategies to enhance stability, like incorporating additives, post-treatments, novel contact materials etc. were developed using this fast feedback approach. The relationships between indoor and outdoor stresses were also validated. Task 2 Manufacturability: This second task, focused on creating a scalable production process for PSCs. Initially the objective is to establish a best-known method for a 182 cm2 minimodule. However, given resource limitations, these metrics were modified to focus on the other goal of outlined in the TWP. Specifically, this task worked to demonstrate the transferability of this best-known method to another research institution. Work scope in this area was expanded to material purity and understanding of reagent/process relationships. Examination of other difficulties in PSC production and potential solutions for large-scale production were also evaluated. Given challenges observed in process transfer, work to develop data infrastructure and recording tools for processing of material and devices was then also prioritized in this task. Task 3 Efficiency: This task was focused on improvements to PCE, while still considering Task 1 and Task 2 goal. The efforts targeted a PCE greater than 22% with a T95 exceeding 1000 hours at 25°C in a nitrogen environment for lab-scale devices (approximately 0.1 cm2 devices) across a range of solar-relevant perovskite compositions, including wide-gap (around 1.7 eV) and low-gap (around 1.3 eV) materials, using standard metal contacts. This work then provides a foundation for MHP-based tandem efforts undertaken in other projects and the All-MHP tandem efforts outlined in this projects TWP. Work in this project emphasized disseminating its findings through peer-reviewed publications (PRP), conference presentations, and industrial collaborations. Significant products were produced in all these areas, over 53 peer reviewed publications, 32 conference presentations and industrial investment based on NLR assistance on precompetitive challenges. The team also developed significant intellectual property and awards for their technical excellence, innovations and leadership. The team also leveraged traditional and social media platforms to engage with stakeholders and the public.

14 SOLAR ENERGY↗