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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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We summarize the influence of polymer coatings on cathode particles for electrochemical energy storage applications. We report on the effect of different polymer types, their properties, and their influence on thermo-electro-chemical behavior.
Disorders in intermetallic systems belonging to the CeNiSi 2 -family are frequently overlooked. Even compounds presumed to be stoichiometric, such as YFeGe 2 , can be misidentified. Here, in this study, we report a series of Y 4 Fe x Ge 8 (1.0 ≤ x ≤ 1.5) compounds and show, using high-resolution synchrotron X-ray diffraction, that they feature asymmetrical structural distortions in the Fe and Ge sites that lead to a superstructure with partially ordered Fe vacancies and distorted Ge square-net in the triclinic crystal system, space group P[1 with combining macron] with a = 11.4441(3) Å, b = 32.7356(7) Å, c = 11.4456(3) Å, α = 79.6330(10)°, β = 88.3300(10)°, and γ = 79.6350 (10)°. The unit cell is 16 times the conventional orthorhombic cell with the space group Cmcm. We identified the lower and upper limits for Fe in Y 4 Fe x Ge 8 (1.0 ≤ x ≤ 1.5). Our physical property measurements yielded a Sommerfeld coefficient γ = 39.8 mJ mole −1 K −2 , a Kadowaki–Woods ratio of 1.2 × 10 −5 μΩ cm mole 2 K 2 mJ −2 , and a Wilson ratio of 1.83, suggesting heavy fermion behavior in the absence of f electrons, a rather rare case. Furthermore, we observed strong spin frustration and noted findings indicating possible superconductivity associated with the Fe content.
The selection of pretreatment methods is critical to achieving high product yields during bioconversion of lignocellulosic biomass. Hydrothermal, soaking-in-aqueous ammonia, and ionic liquid pretreatment methods are viable candidates for minimizing sugar decomposition, permitting the effective hydrolysis of structural carbohydrates, and producing a fermentable substrate suitable for achieving industrial ethanol titers and yields. In this study, the effect of these three pretreatment methods on non-modified sugarcane cultivar CP88-1762 and two transgenic lipid-accumulating sugarcane lines, oilcane 1565 and oilcane 1566, were investigated and compared in terms of lipid recovery, sugar yield, and ethanol yields within the lignocellulosic biomass conversion pipeline. Fed-batch enzymatic hydrolysis at high solid loading yielded hydrolysates capable of supporting industrial bioethanol titers across all conditions. The highest sugar yields were obtained on ammonia-pretreated biomass hydrolysate (253.73 g L −1 ), followed by hydrothermally pretreated hydrolysate (213.10 g L −1 ) and ionic liquid-pretreated hydrolysate (154.20 g L −1 ). Commercially viable ethanol titers of 100.62 g L −1 , 64.47 g L −1 , and 52.95 g L −1 were achieved from ammonia, hydrothermal, and ionic liquid pretreated hydrolysate with the corresponding ethanol productivities of 2.08 g L −1 h −1 , 0.53 g L −1 h −1 , and 0.36 g L −1 h −1 . The lower acetic acid concentration in ammonia-pretreated hydrolysate may have enhanced its fermentability relative to the hydrothermal pretreatment condition, as indicated by the differences in ethanol titer and productivity. Lower sugar yields and ethanol productivities under the ionic liquid conditions likely resulted from the inhibitory effect of cholinium lysinate. Oilcane 1565 and oilcane 1566 bagasse accumulated over 16- and 3 times higher lipids than the non-modified sugarcane CP88-1762. The total fatty acid content in the oilcane samples was reduced in ammonia and ionic liquid-pretreated bagasse relative to the hydrothermal pretreatment condition. While all pretreatment techniques tested are industrially viable, the observed differences in titer, productivity, and lipid content indicate that careful selection and validation of upstream processing methods can contribute to improved economic and environmental outcomes.
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A new class of ceramics, called entropy stabilized oxides, High Entropy Oxides (HEOs), multicomponent oxides, compositionally complex oxides, or polycation oxides, has generated considerable research interest since the first report in 2015. This multicomponent approach has created new opportunities for materials design and discovery. This Perspective will highlight some current research developments and possible applications while also providing an overview of the many successfully synthesized HEO systems to date. The polycation approach to composition development will be discussed along with a few case studies, challenges, and future possibilities afforded by this novel class of materials.
Nonthermal atmospheric pressure plasmas transform input electrical energy efficiently into reactive species, charged particles, and photons. This “activated gas” is being investigated as solutions for a range of environmental and health problems facing society today. In this Perspective, we take a cursory look at a few of these societal problems and the reflected role that plasmas may play in charting the pathway to a solution buoyed by supporting research. Here, we survey the plasma-based opportunities in the removal of trace contaminants in water supporting methodologies such as water reuse, which addresses scarcity and pollution, the opportunity posed by plasmas-based chemical depolymerization for plastics recycling, and the application of plasmas for food security, which includes sterilization of foodstuffs and the improvement of crop yield. Finally, we also included a short review on how plasmas may help control disease spread. In each case, the scope of the problem is presented along with the potential plasma-based solution.
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Pyrene fluorescence after a high-energy electronic excitation exhibits a prominent band shoulder not present after excitation at low energies. The standard assignment of this shoulder as a non-Kasha emission from the second-excited state (S 2 ) has been recently questioned. To elucidate this issue, we simulated the fluorescence of pyrene using two different theoretical approaches based on vertical convolution and nonadiabatic dynamics with nuclear ensembles. To conduct the necessary nonadiabatic dynamics simulations with high-lying electronic states and deal with fluorescence timescales of about 100 ns of this large molecule, we developed new computational protocols. The results from both approaches confirm that the band shoulder is, in fact, due to S 2 emission. We show that the non-Kasha behavior is a dynamic-equilibrium effect not caused by a metastable S 2 minimum. However, it requires considerable vibrational energy, which can only be achieved in collisionless regimes after transitions into highly excited states. This strict condition explains why the S 2 emission was not observed in some experiments.
While there are several bottlenecks in hybrid organic–inorganic perovskite (HOIP) solar cell production steps, including composition screening, fabrication, material stability, and device performance, machine learning approaches have begun to tackle each of these issues in recent years. Different algorithms have successfully been adopted to solve the unique problems at each step of HOIP development. Specifically, high-throughput experimentation produces vast amount of training data required to effectively implement machine learning methods. Here, we present an overview of machine learning models, including linear regression, neural networks, deep learning, and statistical forecasting. Experimental examples from the literature, where machine learning is applied to HOIP composition screening, thin film fabrication, thin film characterization, and full device testing, are discussed. These paradigms give insights into the future of HOIP solar cell research. As databases expand and computational power improves, increasingly accurate predictions of the HOIP behavior are becoming possible.
As photonic technologies grow in multidimensional aspects, integrated photonics holds a unique position and continuously presents enormous possibilities for research communities. Applications include data centers, environmental monitoring, medical diagnosis, and highly compact communication components, with further possibilities continuously growing. Herein, we review state-of-the-art integrated photonic on-chip sensors that operate in the visible to mid-infrared wavelength region on various material platforms. Among the different materials, architectures, and technologies leading the way for on-chip sensors, we discuss the optical sensing principles that are commonly applied to biochemical and gas sensing. Our focus is on passive optical waveguides, including dispersion-engineered metamaterial-based structures, which are essential for enhancing the interaction between light and analytes in chip-scale sensors. We harness a diverse array of cutting-edge sensing technologies, heralding a revolutionary on-chip sensing paradigm. Our arsenal includes refractive-index-based sensing, plasmonics, and spectroscopy, which forge an unparalleled foundation for innovation and precision. Furthermore, we include a brief discussion of recent trends and computational concepts, incorporating Artificial Intelligence & Machine Learning (AI/ML) and deep learning approaches over the past few years to improve the qualitative and quantitative analysis of sensor measurements.
We report on the magnetic properties of biphase iron oxide nanorods (NRs) consisting of ferrimagnetic Fe 3 O 4 and antiferromagnetic α-Fe 2 O 3 phases. Annealing as-prepared NRs at 250 °C for 5h, significantly improved the crystallinity of the Fe 3 O 4 phase and enhanced the volume fraction of the α-Fe 2 O 3 phase. Magnetometry data consistently reveal these two magnetically distinct phases, which are not in proximity to each other but separated by a region of disordered spins giving rise to enhanced magnetization at low temperatures when the sample was cooled down from 300 K in the presence of a 1T field to 10 K. This phenomenon which is also known as the pinning effect is much more pronounced in the annealed sample, resulting from the increased volume fraction of the α-Fe 2 O 3 phase which could strengthen the interfacial spin frustration between these two phases and enhance the density of disordered spins at the interface.
Orthorhombic air-stable two-dimensional (2D) antiferromagnet (AFM) CrSBr has attracted much research interest lately thanks to its rich magnetic behaviors together with its remarkable electronic, excitonic, and polaritonic properties. Here, we report a reliable electrochemical intercalation method by inserting large tetrabutylammonium (TBA + ) ions into CrSBr layers. Magnetically, such intercalation efficiently suppresses the interlayer AFM and induces a ferromagnetic (FM) order with a much-enhanced transition temperature up to 200 K, nearly 70 K higher than the AFM onset of 132 K in pristine CrSBr. Electronically, the TBA + intercalation not only increases the electric conductivity of CrSBr, which is further enhanced by magnetic fields, but also introduces a giant negative irreversible magnetoresistance. This work demonstrates the tunable magnetic and electronic properties of CrSBr as well as their interplay, paving the way for advanced spintronic and magnetic memory devices.
Humanity’s curiosity of and intrigue for exploring space has been with our species since we first looked up into the night sky. This age-old curiosity has driven humankind to innovate technologies for millennia, including efforts ranging from the construction of Stonehenge to track the annual movements of the sun to the investigation of advanced propulsion systems capable of transporting people to distant planets. Today’s technical communities dedicated to researching and developing innovative technologies for space exploration have seen a recent reinvigoration. Over the past few years, impressive progress made by industry, with exceptional support from government agencies, to reestablish and develop new capabilities has renewed confidence in humanity’s ability to reach the stars—a confidence that has not been present since the days of the Apollo program. Moreover, history shows that innovation and collaboration within the scientific and engineering communities reaches unparalleled pinnacles during periods of astrophilia. Finally, given the advancements in computational capacities for advanced modeling and simulation, unprecedented breakthroughs in commercializing advanced manufacturing techniques, and powerful collaborative relationships between industry and national scientific organizations, today we are limited only by our own imaginations.
Rising interest in molten salt reactors for commercial power production presents an opportunity to evaluate the techniques used to characterize materials of nuclear forensic interest. Since extensive research has been performed to identify and develop signatures of light water reactor (LWR) materials (e.g. uranium ore concentrates and uranium dioxide fuel pellets), we use this as a basis to explore possibilities for molten salt signature development. Through this comparative method, nuclear forensic signatures used today to identify the provenance of nuclear materials found out of regulatory control are adapted to molten salt reactor (MSR) fuel cycle materials. Radiological, elemental composition, isotopic composition, and model age signatures will likely not need large adaptations before being applied to MSR materials but may need to expand to be applicable to both thorium- and uranium-fueled systems. The liquid nature of molten salt fuel may erase signatures related to production and irradiation history that are informative for typical LWR materials. However, it may also lead to opportunities for new signatures, such as cooling rate–controlled morphology. Targets identified for further research include radiological attributes of fuel salts; elemental, chemical, and isotopic analysis of salts with differing production routes; morphological effects of various thermodynamic environments; and relevant fuel cycle radiochronometers. Additionally, the comparative nature of the proposed signatures implies a need for MSR-relevant databases and the production of salt standard reference materials.
Over the past decade, loop-mediated isothermal amplification (LAMP) technology has played an important role in molecular diagnostics. Amongst numerous nucleic acid amplification assays, LAMP stands out in terms of sample-to-answer time, sensitivity, specificity, cost, robustness, and accessibility, making it ideal for field-deployable diagnostics in resource-limited regions. In this review, we outline the front-end LAMP design practices for point-of-care (POC) applications, including sample handling and various signal readout methodologies. Next, we explore existing LAMP technologies that have been validated with clinical samples in the field. We summarize recent work that utilizes reverse transcription (RT) LAMP to rapidly detect SARS-CoV-2 as an alternative to standard PCR protocols. Finally, we describe challenges in translating LAMP from the benchtop to the field and opportunities for future LAMP assay development and performance reporting. Despite the popularity of LAMP in the academic research community and a recent surge in interest in LAMP due to the COVID-19 pandemic, there are numerous areas for improvement in the fundamental understanding of LAMP, which are needed to elevate the field of LAMP assay development and characterization.
Parabacteroides distasonis is the type strain for the genus Parabacteroides, a group of gram-negative anaerobic bacteria that commonly colonize the gastrointestinal tract of numerous species. First isolated in the 1930s from a clinical specimen as Bacteroides distasonis, the strain was re-classified to form the new genus Parabacteroides in 2006. Currently, the genus consists of 15 species, 10 of which are listed as 'validly named' (P. acidifaciens, P. chartae, P. chinchillae, P. chongii, P. distasonis, P. faecis, P. goldsteinii, P. gordonii, P. johnsonii, and P. merdae) and 5 'not validly named' (P. bouchesdurhonensis, P. massiliensis, P. pacaensis, P. provencensis, and P. timonensis) by the List of Prokaryotic names with Standing in Nomenclature. The Parabacteroides genus has been associated with reports of both beneficial and pathogenic effects in human health. Herein, we review the literature on the history, ecology, diseases, antimicrobial resistance, and genetics of this bacterium, illustrating the effects of P. distasonis on human and animal health.
Abstract We report a systematic investigation of the magnetic properties including the exchange bias (EB) effect in an iron oxide nanocube system with tunable phase and average size (10, 15, 24, 34, and 43 nm). X-ray diffraction and Raman spectroscopy reveal the presence of Fe 3 O 4 , FeO, and α -Fe 2 O 3 phases in the nanocubes, in which the volume fraction of each phase varies depending upon particle size. While the Fe 3 O 4 phase is dominant in all and tends to grow with increasing particle size, the FeO phase appears to coexist with the Fe 3 O 4 phase in 10, 15, and 24 nm nanocubes but disappears in 34 and 43 nm nanocubes. The nanocubes exposed to air resulted in an α -Fe 2 O 3 oxidized surface layer whose thickness scaled with particle size resulting in a shell made of α -Fe 2 O 3 phase and a core containing Fe 3 O 4 or a mixture of both Fe 3 O 4 and FeO phases. Magnetometry indicates that the nanocubes undergo Morin (of the α -Fe 2 O 3 phase) and Verwey (of the Fe 3 O 4 phase) transitions at ∼250 K and ∼120 K, respectively. For smaller nanocubes (10, 15, and 24 nm), the EB effect is observed below 200 K, of which the 15 nm nanocubes showed the most prominent EB with optimal antiferromagnetic (AFM) FeO phase. No EB is reported for larger nanocubes (34 and 43 nm). The observed EB effect is ascribed to the strong interfacial coupling between the ferrimagnetic (FiM) Fe 3 O 4 phase and AFM FeO phase, while its absence is related to the disappearance of the FeO phase. The Fe 3 O 4 / α -Fe 2 O 3 (FiM/AFM) interfaces are found to have negligible influence on the EB. Our findings shed light on the complexity of the EB effect in mixed-phase iron oxide nanosystems and pave the way to design exchange-coupled nanomaterials with desirable magnetic properties for biomedical and spintronic applications.
The approaching end of Moore's Law scaling has significantly accelerated multiple fields of research including neuromorphic-, quantum-, and photonic computing, each of which possesses unique benefits unobtained through conventional binary computers. One of the most compelling arguments for neuromorphic computing systems is power consumption, noting that computations made in the human brain are approximately 106 times more efficient than conventional CMOS logic. This review article focuses on the materials science and physical mechanisms found in metal chalcogenides that are currently being explored for use in neuromorphic applications. We begin by reviewing the key biological signal generation and transduction mechanisms within neuronal components of mammalian brains and subsequently compare with observed experimental measurements in chalcogenides. With robustness and energy efficiency in mind, we will focus on short-range mechanisms such as structural phase changes and correlated electron systems that can be driven by low-energy stimuli, such as temperature or electric field. We aim to highlight fundamental materials research and existing gaps that need to be overcome to enable further integration or advancement of metal chalcogenides for neuromorphic systems.