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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 19 records

Patient-Reported Outcomes in Pediatric Cancer Registration Trials: A US Food and Drug Administration Perspective

Pediatric patient-reported outcome (PRO) data can help inform the US Food and Drug Administration’s (FDA’s) benefit-risk assessment of cancer therapeutics by quantifying symptom and functional outcomes from the patient’s perspective. This study assessed use of PROs in commercial pediatric oncology trials submitted to the FDA for regulatory review. FDA databases were searched to identify pediatric oncology product applications approved between 1997 and 2020. Sponsor-submitted documents were reviewed to determine whether PRO data were collected, which instruments were used, and the quality of collected data (ie, sample size, completion rates, and use of fit-for-purpose instruments). The role of PROs in each trial (endpoint hierarchy) was also recorded in addition to whether any PRO endpoints were included in product labeling. We reviewed 17 pediatric oncology applications, 4 of which included PRO data: denosumab, tisagenlecleucel, larotrectinib, and selumetinib. In these 4 instances, PROs served as exploratory endpoints and were not incorporated in product labeling. Trials that collected PRO data were phase II or phase I/II single-arm studies with sample sizes of 28 to 88 patients. Symptomatic adverse events (AEs) were characterized using clinician-reported Common Terminology Criteria for Adverse Events (CTCAE) without additional patient self-report. PROs were infrequently used in pediatric cancer registration trials. When PROs were used, PRO data were limited by lack of a clear research objective and corresponding prospective statistical analysis plan. Contemporary PRO symptom libraries, such as the National Cancer Institute’s Pediatric PRO-CTCAE, may provide an opportunity to better evaluate the occurrence and impact of symptomatic AEs, from the patient’s perspective, in pediatric oncology trials.

Oncology↗

A Perspective on Quantum Computing Applications in Quantum Chemistry Using 25-100 Logical Qubits

The intersection of quantum computing and quantum chemistry represents a promising frontier for achieving quantum utility in domains of both scientific and societal relevance. Owing to the exponential growth of classical resource requirements for simulating quantum systems, quantum chemistry has long been recognized as a natural candidate for quantum computation. This perspective focuses on identifying scientifically meaningful use cases where early fault-tolerant quantum computers, which are considered to be equipped with approximately 25-100 logical qubits, could deliver tangible impact. While recent advances in classical computing have pushed the boundaries of tractable simulations to unprecedented scales, this logical-qubit regime represents the first window where quantum devices can pursue qualitatively distinct strategies, such as polynomial-scaling phase estimation, direct simulation of quantum dynamics, and active-space embedding, that remain challenging for classical solvers, such as multireference charge-transfer and conical-intersection states central to photochemistry and materials design. We highlight near-term opportunities in algorithm and software design, discuss representative chemical problems suited for quantum acceleration, and propose strategic roadmaps and collaborative pathways for advancing practical quantum utility in quantum chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Beyond Ion Migration in Metal Halide Perovskites: Toward a Broader Photoelectrochemistry Perspective

Ion migration is a broad term used to account for the degradation of halide perovskite materials and devices. However, ion mobility is only one piece of the full picture-mobile ions/defects are first created, then transported, and eventually annihilated or immobilized. In this Perspective, we summarize emerging work that shows how tractable photochemical and Faradaic reactions provide a continuous source of ions to migrate. Furthermore, we discuss strategies to fundamentally manipulate ion migration by targeting specific electrochemical and reduction/oxidation mechanisms. This highlights the important role of defect photoelectrochemistry, as well as the soft nature of the perovskite lattice, in ion migration and self-healing. We conclude that distinguishing more detailed processes involved in “ion migration”, with an emerging focus on the reactions that form mobile ionic defects, is necessary to greatly improve the stability of devices and open up more technological applications.

defects↗

Developing reactors for electrifying bio-methanation: a perspective from bio-electrochemistry

The integration of microbial synthesis with renewable electricity is an emerging route for both CO 2 utilization and seasonal energy storage in the form of stored bio-electrofuels. The major benefits of electrifying bioreactors include: using highly selective bio-catalysts for CO 2 conversion under mild reaction conditions; decoupling the production of more facile electrochemical intermediates, such as hydrogen, at the electrode from the production of bio-catalyzed multi-electron and/or carbon products, such as methane or acetate; using microbes as robust and self-regenerating catalysts enabling higher efficiency and durability in CO 2 conversion systems compared to inorganic catalysis. In this Perspective, we propose research aimed at developing electro-bioreactor components that will increase the productivity of the reactor while maintaining high energy efficiency and biocompatible reaction conditions to fully realize the benefits of electrified bioreactors. Furthermore, these developments include: flow reactors with tailored 3D electrodes to optimally use the reactor volume, electrocatalysts designed for peak performance in neutral pH electrolytes, high conductivity microbial media, and new membrane separator materials with high ion conductivity and low gas permeability. Production of methane via a hybrid electrical-biological approach is taken as a case study to motivate these developments. Finally, an iterative design–manufacture–test cycle, enabled by additive manufacturing and 3D printing technologies, is proposed to rapidly prototype components prior to large-scale manufacturing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Energy storage emerging: A perspective from the Joint Center for Energy Storage Research

Energy storage is an integral part of modern society. A contemporary example is the lithium (Li)-ion battery, which enabled the launch of the personal electronics revolution in 1991 and the first commercial electric vehicles in 2010. Most recently, Li-ion batteries have expanded into the electricity grid to firm variable renewable generation, increasing the efficiency and effectiveness of transmission and distribution. Important applications continue to emerge including decarbonization of heavy-duty vehicles, rail, maritime shipping, and aviation and the growth of renewable electricity and storage on the grid. This perspective compares energy storage needs and priorities in 2010 with those now and those emerging over the next few decades. The diversity of demands for energy storage requires a diversity of purpose-built batteries designed to meet disparate applications. Advances in the frontier of battery research to achieve transformative performance spanning energy and power density, capacity, charge/discharge times, cost, lifetime, and safety are highlighted, along with strategic research refinements made by the Joint Center for Energy Storage Research (JCESR) and the broader community to accommodate the changing storage needs and priorities. Innovative experimental tools with higher spatial and temporal resolution, in situ and operando characterization, first-principles simulation, high throughput computation, machine learning, and artificial intelligence work collectively to reveal the origins of the electrochemical phenomena that enable new means of energy storage. This knowledge allows a constructionist approach to materials, chemistries, and architectures, where each atom or molecule plays a prescribed role in realizing batteries with unique performance profiles suitable for emergent demands.

Trahey, Lynn↗

Perspective—Emergent Phases in Rare Earth Nickelate Heterostructure

The prediction of high T c superconductivity in layers of LaNiO 3 through orbital engineering has led to extensive research efforts over the last fifteen years. During this period, a plethora of thin films and heterostructures based rare-earth nickelate family with perovskite structure has been synthesized and explored. Here, in this short perspective, we briefly review the complexity of bulk RENiO 3 , spotlighting several recent findings of emergent phenomena in heterostructures containing the interface between RENiO 3 and another transition metal oxide. Finally, we outline potentially interesting future directions linked to time-domain dynamics to harness new Mott and topological phases in artificial structures of RENiO 3 .

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A cost and community perspective on the barriers to microbiome data reuse

Microbiome research is becoming a mature field with a wealth of data amassed from diverse ecosystems, yet the ability to fully leverage multi-omics data for reuse remains challenging. To provide a view into researchers’ behavior and attitudes towards data reuse, we surveyed over 700 microbiome researchers to evaluate data sharing and reuse challenges. We found that many researchers are impeded by difficulties with metadata records, challenges with processing and bioinformatics, and problems with data repository submissions. We also explored the cost constraints of data reuse at each step of the data reuse process to better understand “pain points” and to provide a more quantitative perspective from sixteen active researchers. The bioinformatics and data processing step was estimated to be the most time consuming, which aligns with some of the most frequently reported challenges from the community survey. From these two approaches, we present evidence-based recommendations for how to address data sharing and reuse challenges with concrete actions for future work.

59 BASIC BIOLOGICAL SCIENCES↗

A step forward from high-entropy ceramics to compositionally complex ceramics: a new perspective

High-entropy ceramics (HECs) have quickly gained attention since 2015. To date, nearly all work has focused on five-component, equimolar compositions. This perspective article briefly reviews different families of HECs and selected properties. Following a couple of our most recent studies, we propose a step forward to expand HECs to compositionally-complex ceramics (CCCs) to include medium-entropy and/or non-equimolar compositions. Here, using defective fluorite and ordered pyrochlore oxides as two primary examples, we further consider the complexities of aliovalent cations and anion vacancies as well as ordered structures with two cation sublattices. Better thermally-insulating yet stiff CCCs have been found in non-equimolar compositions with optimal amounts of oxygen vacancies and in ordered pyrochlores with large size disorder; it is demonstrated that medium-entropy ceramics (MECs) can prevail over their high-entropy counterparts. The diversifying classes of CCCs provide even more possibilities than HECs to tailor the composition, defects, disorder/order, and consequently various properties.

36 MATERIALS SCIENCE↗

Pitting Corrosion in 316L Stainless Steel Fabricated by Laser Powder Bed Fusion Additive Manufacturing: A Review and Perspective

Abstract 316L stainless steel (316L SS) is a flagship material for structural applications in corrosive environments, having been extensively studied for decades for its favorable balance between mechanical and corrosion properties. More recently, 316L SS has also proven to have excellent printability when parts are produced with additive manufacturing techniques, notably laser powder bed fusion (LPBF). Because of the harsh thermo-mechanical cycles experienced during rapid solidification and cooling, LPBF processing tends to generate unique microstructures. Strong heterogeneities can be found inside grains, including trapped elements, nano-inclusions, and a high density of dislocations that form the so-called cellular structure. Interestingly, LPBF 316L SS not only exhibits better mechanical properties than its conventionally processed counterpart, but it also usually offers much higher resistance to pitting in chloride solutions. Unfortunately, the complexity of the LPBF microstructures, in addition to process-induced defects, such as porosity and surface roughness, have slowed progress toward linking specific microstructural features to corrosion susceptibility and complicated the development of calibrated simulations of pitting phenomena. The first part of this article is dedicated to an in-depth review of the microstructures found in LPBF 316L SS and their potential effects on the corrosion properties, with an emphasis on pitting resistance. The second part offers a perspective of some relevant modeling techniques available to simulate the corrosion of LPBF 316L SS, including current challenges that should be overcome.

Voisin, T. (ORCID:0000000287462659)↗

Transfer learning for smart buildings: A critical review of algorithms, applications, and future perspectives

Smart buildings play a crucial role toward decarbonizing society, as globally buildings emit about one-third of greenhouse gases. In the last few years, machine learning has achieved a notable momentum that, if properly harnessed, may unleash its potential for advanced analytics and control of smart buildings, enabling the technique to scale up for supporting the decarbonization of the building sector. In this perspective, transfer learning aims to improve the performance of a target learner exploiting knowledge in related environments. The present work provides a comprehensive overview of transfer learning applications in smart buildings, classifying and analyzing 77 papers according to their applications, algorithms, and adopted metrics. The study identified four main application areas of transfer learning: (1) building load prediction, (2) occupancy detection and activity recognition, (3) building dynamics modeling, and (4) energy systems control. Furthermore, the review highlighted the role of deep learning in transfer learning applications that has been used in more than half of the analyzed studies. The paper also discusses how to integrate transfer learning in a smart building's ecosystem, identifying, for each application area, the research gaps and guidelines for future research directions.

Pinto, G↗

Challenges and future perspectives on sodium and potassium ion batteries for grid-scale energy storage

The energy crisis and environmental pollution require the advancement of large-scale energy storage techniques. Among the various commercialized technologies, batteries have attracted enormous attention due to their relatively high energy density and long cycle life. Nevertheless, the limited supply and uneven distribution of lithium minerals, as well as their high cost, has greatly hindered the application of lithium-ion batteries in large-scale energy storage. Therefore, building next-generation alternative rechargeable batteries that feature low cost, long service life, and high safety is of the utmost importance. Over the past several years, we have witnessed many successful research outcomes for sodium and potassium ion batteries (SIBs and PIBs) in regard to electrode and electrolyte materials. In this Perspective, we summarize the current developments on SIBs/PIBs and their challenges when facing practical applications, including their cost, energy density, ion diffusivity in solids/electrolytes/interphases, cycle life, and safety concerns. Furthermore, we provide an overview of strategies to overcome the remaining challenges for achieving better electrochemical performance. Finally, we outline several possible directions for the future development of these two battery chemistries, with the hope of aiding the transition from the laboratory to next-generation practical applications for SIBs/PIBs batteries in grid-scale energy storage.

Energy Storage↗

State preparation and evolution in quantum computing: a perspective from Hamiltonian moments

Quantum algorithms on the noisy intermediate-scale quantum (NISQ) devices are expected to simulate quan- tum systems that are classically intractable to demonstrate quantum advantages. However, the non-negligible gate error on the NISQ devices impedes the conventional quantum algorithms to be implemented. Practical strategies usually exploit hybrid quantum-classical quantum algorithms to demonstrate potentially useful ap- plications of quantum computing in the NISQ era. Among the numerous hybrid quantum-classical algorithms, recent efforts highlight the development of quantum algorithms based upon quantum computed Hamiltonian moments, ?f|Hˆn|f? (n = 1, 2, · · · ), with respect to quantum state |f?. In this tutorial, we will give a brief review of these quantum algorithms with focuses on the typical ways of computing Hamiltonian moments using quantum hardware and improving the accuracy of the estimated state energies based on the quantum computed moments. Furthermore, we will present a tutorial to show how we can measure and compute the Hamiltonian moments of a four-site Heisenberg model, and compute the energy and magnetization of the model utilizing the imaginary time evolution in the real IBM-Q NISQ hardware environment. Along this line, we will further discuss some practical issues associated with these algorithms. We will conclude this tutorial review by overviewing some possible developments and applications in this direction in the near future.

Aulicino, Joseph C.↗

Perspectives on the FESAC transformative enabling capabilities: Priorities, plans, and Status

In early 2017, the Fusion Energy Sciences Advisory Committee (FESAC), an advisory committee to the United States Department of Energy, was charged with identifying transformative enabling capabilities (TECs) “that could promote efficient advance toward fusion energy, building on burning plasma science and technology.” A subcommittee with broad expertise was formed and sought feedback from scientific experts, including experts from outside the fusion community. Three workshops were conducted, and a report was approved by FESAC in 2018 that identified four of the “most promising” TECs: advanced algorithms, high-critical-temperature superconductors, advanced materials and manufacturing, and novel technologies for tritium fuel cycle control. In addition, one “promising” TEC was identified: fast flowing liquid metal plasma-facing components. This paper will give details on the promising TECs and an overview on considerations of these TECs in the United States since the publication of the report.

Lumsdaine, Arnold↗