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At least 1,513 records · Page 84

Physics for neuromorphic computing

Neuromorphic computing takes inspiration from the brain to create energy-efficient hardware for information processing, capable of highly sophisticated tasks. Systems built with standard electronics achieve gains in speed and energy by mimicking the distributed topology of the brain. Scaling-up such systems and improving their energy usage, speed and performance by several orders of magnitude requires a revolution in hardware. Here, we discuss how including more physics in the algorithms and nanoscale materials used for data processing could have a major impact in the field of neuromorphic computing. We review striking results that leverage physics to enhance the computing capabilities of artificial neural networks, using resistive switching materials, photonics, spintronics and other technologies. We discuss the paths that could lead these approaches to maturity, towards low-power, miniaturized chips that could infer and learn in real time.

device physics↗

Microwave impedance microscopy and its application to quantum materials

We report materials in which quantum mechanical effects lead to novel properties on the macroscopic scale are of interest both fundamentally and for applications. For such quantum materials, the ability to measure local conductivity and permittivity with nanoscale spatial resolution, minimal sample preparation, in a contact-free fashion and under a wide range of external conditions (such as temperature and magnetic field) is highly desirable. To this end, microwave impedance microscopy, a scanning probe technique that measures tip–sample admittance (inverse of impedance) in a non-contact geometry at microwave frequencies, has matured over the past decade to become a tool that can do just that. This Technical Review describes its fundamental working principles and practical implementations, discusses its application to a wide range of quantum materials, including correlated, topological and 2D van der Waals materials, and outlines future opportunities in expanding the capabilities of microwave impedance microscopy.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Host cell and viral protease targets of human SERPINs identified by in silico docking

Serine protease inhibitors (SERPINs) are involved in various physiological processes and diseases, such as inflammation, cancer metastasis, and neurodegeneration. Their role in viral infections is poorly understood, as their expression patterns during infection and the range of proteases they target have yet to be fully characterized. Here, we show widespread expression of human SERPINs in response to respiratory virus infections, both in bronchioalveolar lavages from COVID-19 patients and in polarized human airway epithelial cultures. Using in silico docking of 10 SERPINs to 48 host proteases, we confirm known targets and predict new interactions. Protease activity assays validated selected interactions, confirming the newly predicted host targets for PAI-1 (SERPINE1) and PAI-2 (SERPINB2). PAI-1 inhibits cathepsin L, essential for SARS-CoV-2 maturation, and suppresses multi-cycle replication of both ancestral SARS-CoV-2 WA-1 and its variant Omicron BA.1. In addition, we identify PAI-2 as an antiviral SERPIN that reduces infectivity of human adenovirus 5 by directly inhibiting the adenoviral protease. Our study leverages in silico docking using full-length 3D protein structures to uncover new SERPIN targets, offering a range of candidate targets for therapeutic interventions.

59 BASIC BIOLOGICAL SCIENCES↗

Considerations for the Global Commercialization of Floating Offshore Wind Energy

Floating offshore wind (FOW) has the potential to unlock access to wind resources in deep water where fixed-bottom turbines are not feasible, enabling coastal regions around the world to meet growing energy demands. Although fixed-bottom offshore wind is commercially mature, FOW, which may be needed for water deeper than 60 m, must progress in multiple ways to reach full commercial viability. In this Perspective, we examine the status of the global FOW industry's commercial development across three key areas - technical innovation, industrialization and cross-cutting value. Technical innovation has enabled FOW turbines to perform as well as fixed-bottom turbines, with the promise of future cost reductions. However, the complex architecture of FOW turbines, combining floating structures with more than 8,000 electrical and mechanical parts in wind turbines, requires industrialization efforts such as standardization and supply-chain integration to enable commercial project deployment. FOW can potentially offer unique benefits, including reduced environmental impacts and strengthened economic development in coastal regions, through substantial regional economic activity. Successful coordination across these three areas could help to position FOW as a major contributor to a competitive, reliable and resilient global energy system.

17 WIND ENERGY↗

Quantum sensing for emerging energy technologies

The ability to exploit quantum phenomena has enabled sensing technologies with detection limits below the classical limit. Sensors with applications in energy discovery, production, transportation, and consumption can be enhanced through quantum or hybrid quantum-classical sensors. Here, in this Review, we provide an overview of commercial and emerging quantum sensor platforms and their opportunity areas specific to advanced energy technologies. Key examples include: power grid-enhancing-technologies, where quantum magnetometers can detect powerline and transformer faults; electric vehicle-to-grid applications, where chip-scale atomic clocks can enable grid synchronization; and carbon capture and storage, where quantum gravimeters and single-photo LiDAR can detect microscopic leaks. Quantum sensor deployment requires further research into miniaturization and ruggedization for field deployment, cost-reduction, and workforce development. The maturation of clean energy technologies and quantum sensors provide opportunities for synergy, with the integration of quantum sensors into advanced energy technologies maximizing their security, reliability, and efficiency.

critical metals↗

Cyclic strain enhances the early stage mineral nucleation and the modulus of demineralized bone matrix

The adaptive response of bones to mechanical loading is essential for musculoskeletal development. Despite the importance of collagen in bone mineralization, little is known about how cyclic strain influences physicochemical responses of collagen, especially at the early stage of mineralization when the levels of strain are higher than those in mature bones. The findings in this study show that, without any cell-mediated activity, cyclic strain increases nucleation rates of calcium phosphate (CaP) nanocrystals in highly-organized collagen matrices. The cyclic strain enhances the transport of mineralization fluids with nucleation precursors into the matrix, thus forming more CaP nanocrystals and increasing the elastic modulus of the collagen matrix. The results also suggest that the multiscale spatial distribution of nanocrystals in the fibrous collagen network determines tissue-level mechanical properties more critically than the total mineral content. Furthermore, by linking nano- and micro-scale observations with tissue-level mechanical properties, we provide new insights into designing better biomaterials.

36 MATERIALS SCIENCE↗

Optimal design and integration of decentralized electrochemical energy storage with renewables and fossil plants

Increasing renewable energy requires improving the electricity grid flexibility. Existing measures include power plant cycling and grid-level energy storage, but they incur high operational and investment costs. Using a systems modeling and optimization framework, we study the integration of electrochemical energy storage with individual power plants at various renewable penetration levels. Furthermore, our techno-economic analysis includes both Li-ion and NaS batteries to encompass different technology maturity levels. A California case-study indicates localized integration to be cost-effective for greater grid flexibility. Li-ion batteries can mitigate the residual demand fluctuations of small to medium-sized plants, while NaS batteries would be best-suited for larger storage with higher renewable penetration. Overall, the battery-enabled renewable integration could reduce the unmet grid demand by 75%, the renewable curtailment by 58%, and the CO 2 emission intensity by 16% while including the life cycle emissions of the battery and the renewable farm. Our scenario-based analysis also indicates that rather than replacing all fossil power plants, it is more economical to combine batteries and renewables with individual fossil plants to achieve a clean energy grid.

25 ENERGY STORAGE↗

Emerging concepts in intermediate carbon dioxide emplacement to support carbon dioxide removal

Substantial upscaling of carbon dioxide capture is possible in the coming decades but existing solutions for storage are projected to be limited in annual capacity by as much as 2–10 GtCO 2 per year until mid-century. Temporary storage of CO 2 in a solid or liquid state could prove useful for filling this gap in capacity, until more permanent and ideally lucrative CO 2 sequestration options come online. There are several concepts for reversible solid-state and chemical CO 2 storage, but their advantages and limitations have yet to be reviewed in this context. This article focuses on the physical and chemical aspects of CO 2 storage via liquid and solid chemical carriers and sorbents, and gives an overview of the energetics around their use, as well as prospects for their future development. Exciting opportunities for coupling capture and medium to high maturity multi-year storage technologies could support carbon removal in the coming decades. Highlights of the analysis are the remarkable storage capacity of oxalic acid and formic acid (CO 2 -density of 1857 kg m –3 and 1152 kg m –3 , compared with condensed liquid CO 2 at 993–1096 kg m –3 , respectively), the relative scalability and compatibility of carbonate salts for stationary storage with direct air capture, and the potential promise of multiple carriers for CO 2 transportation. Solid sorbents do not achieve such ultra-high storage capacities, but could improve storage over compressed gas tanks on a capacity and energetics basis.

54 ENVIRONMENTAL SCIENCES↗

Development of an ammonia pretreatment that creates synergies between biorefineries and advanced biomass logistics models

In this study, a novel ammonia-based pretreatment for densified lignocellulosic biomass was developed to reduce ammonia usage and integrate with viable biomass logistics scenarios. The COmpacted Biomass with Recycled Ammonia (COBRA) pretreatment performed at 100 °C allows >95% conversion of sugarcane bagasse (SCB) carbohydrates into soluble monomeric and oligomeric sugars (glucose and xylose) using industrially relevant 6% glucan loading (~21% solids loading) enzymatic hydrolysis conditions at reduced enzyme loadings. Pretreatment via COBRA with simultaneous lignin extraction (COBRA-LE) improved Saccharomyces cerevisiae 424A(LNH-ST) metabolic yield from 89% to 97.5% relative to COBRA without delignification, allowing a process ethanol yield of 71.6%. A technoeconomic analysis on SCB biorefining to ethanol in the state of São Paulo, Brazil, compared COBRA to other mature technologies, such as AFEX and steam-explosion. Amongst all scenarios studied, biorefineries based on COBRA-LE pretreatment offered the lowest average minimum ethanol selling price of US$1.45 per gallon ethanol. COBRA pretreatment was subsequently tested on perennial grasses and hardwoods, and >80% total sugar yields were achieved for all cases.

09 BIOMASS FUELS↗

Structural incorporation into goethite fractionates rare earth elements

Up to 20% of rare earth elements (REEs) in ion adsorption deposits (IADs) are associated with iron oxide minerals, primarily goethite. Often termed “non-extractable”, goethite-hosted REEs are thought to be structurally incorporated into the mineral lattice. The large mismatch in size and charge density between REEs (ionic radius, r = 0.86–1.03 Å) and Fe 3+ (r = 0.65 Å), however, makes direct substitution energetically unfavorable. To determine REE compatibility with and incorporation into goethite on the atomic level, we used X-ray pair distribution function analysis (PDF) and LIII-edge extended X-ray absorption fine structure (EXAFS) spectroscopy. The compatibility of REEs with goethite and the precursor ferrihydrite (FH) is Lu ≥ Yb ≫ Dy > Nd for both phases. Nd and Dy primarily form secondary amorphous phases, with <30% Nd and Dy incorporated into goethite. In the FH precursor at pH 6.8, Yb and Lu assumed a local REE-OOH like structure with next nearest neighbor Fe. The Yb, Lu, and Nd-FH samples were also matured at ambient conditions for 100 days; despite the presence of only ∼5% goethite, Lu and Yb were 42% and 100% in goethite-like structural environments, respectively, whereas the PDF and EXAFS of Nd showed little evidence of any incorporation. Using ab initio molecular dynamics (AIMD) to model the EXAFS, we determined the presence of protonated Fe vacancies, edge-sharing with structural Lu and Yb, likely helped accommodate these REEs in the goethite structure. Incorporation into Fe oxyhydroxides thus potentially fractionates the REEs during weathering associated with formation of lateritic and ion adsorption deposits.

Mergelsberg, Sebastian T. [Pacific Northwest Natio↗

Decoding co-/post-transcriptional complexities of plant transcriptomes and epitranscriptome using next-generation sequencing technologies

Next-generation sequencing (NGS) technologies - Illumina RNA-seq, Pacific Biosciences isoform sequencing (PacBio Iso-seq), and Oxford Nanopore direct RNA sequencing (DRS) - have revealed the complexity of plant transcriptomes and their regulation at the co-/post-transcriptional level. Global analysis of mature mRNAs, transcripts from nuclear run-on assays, and nascent chromatin-bound mRNAs using short as well as full-length and single-molecule DRS reads have uncovered potential roles of different forms of RNA polymerase II during the transcription process, and the extent of co-transcriptional pre-mRNA splicing and polyadenylation. These tools have also allowed mapping of transcriptome-wide start sites in cap-containing RNAs, poly(A) site choice, poly(A) tail length, and RNA base modifications. The emerging theme from recent studies is that reprogramming of gene expression in response to developmental cues and stresses at the co-/post-transcriptional level likely plays a crucial role in eliciting appropriate responses for optimal growth and plant survival under adverse conditions. Although the mechanisms by which developmental cues and different stresses regulate co-/post-transcriptional splicing are largely unknown, a few recent studies indicate that the external cues target spliceosomal and splicing regulatory proteins to modulate alternative splicing. In this review, we provide an overview of recent discoveries on the dynamics and complexities of plant transcriptomes, mechanistic insights into splicing regulation, and discuss critical gaps in co-/post-transcriptional research that need to be addressed using diverse genomic and biochemical approaches.

Biochemistry & Molecular Biology↗

Chapter 1: Introduction - Motivation of Polycrystalline Thin-Film Solar Cells

Thin-film solar cell development may be conceptualized as improving processes to lower costs and improve performance, with characterization as a guide along the way. Yet, pushing the boundaries of characterization is as much at the core of thin-film solar cell development as material synthesis. As PV continues to mature, there is an endless drive to improve performance to compete. Hence, PV technology is striving for increasing levels of perfection, requiring a corresponding sophistication in characterization and understanding. Consequently, the topic of this book -advanced characterization-is timely and critical to develop the potential of thin-film solar technology.

material synthesis↗

Development of a Fast-Spectrum Self-Powered Neutron Detector for Molten Salt Experiments in the Versatile Test Reactor

The self-powered neutron detector (SPND) is a widely used flux monitor in thermal nuclear reactors. Although this is a mature technology, the current state of the art is tuned for a thermal neutron spectrum, so many of the devices currently in use lack sensitivity to fast neutrons. Because current in SPNDs is produced through nuclear reactions with the neutron flux inside a reactor, sensitivity in SPNDs is determined by the neutron cross section of the neutron-sensitive portion of the detector, termed the emitter. This neutron cross section drops by orders of magnitude between thermal and fast neutron energies for many emitters in currently used SPNDs, with a corresponding drop in current from the detector. This paper discusses efforts to develop a fast-spectrum self-powered neutron detector (FS-SPND) that is sensitive to neutrons with energies ranging from 0.025 eV up to 1 MeV. An in-depth analysis of Evaluated Nuclear Data File (ENDF)/B-VII.1 neutron-capture cross sections was performed, and four new materials were identified that are suitable emitter candidates for use in measuring fast neutrons. All four materials are stable mid-shell nuclei in the region between doubly magic 132Sn and 208Pb. Each candidate was simulated with the Geant4 Monte Carlo simulation toolkit to optimize overall detector efficiency.

Goetz, Callie↗

Integration of RNTuple in ATLAS Athena

After using ROOT’s TTree I/O subsystem for over two decades and storing more than an exabyte of compressed High Energy Physics (HEP) data, advances in technology have motivated a complete redesign, RNTuple, which breaks backward-compatibility to take better advantage of these storage options. The RNTuple I/O subsystem has been designed to address performance bottlenecks and other shortcomings of TTree. Specifically, RNTuple comes with an updated, more compact binary data format that can be stored both in ROOT files and natively in object stores. It is designed for modern storage hardware (e.g. high-throughput low-latency NVMe SSDs), and provides robust and easy to use interfaces. The binary format of RNTuple is scheduled to become production grade in 2024, and recently has become mature enough to start exploring the integration into software used by HEP experiments. In this contribution, we discuss the developments to support the features as required by the ATLAS analysis Event Data Model (EDM) in RNTuple, which will enable its integration into the Athena software framework. With these developments in place, we evaluate the performance of the current most recent versions of RNTuple-based ATLAS data sets and compare this to that of TTree.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Automated Electric Vehicle Fleet Operations for On-Demand Service: Challenges and Opportunities

Automated/autonomous vehicle fleet operations within automated mobility districts have been studied over the past five years by the National Renewable Energy Laboratory, a US Department of Energy federally funded research and development center. This paper extends the analysis in this third phase of research underway to include considerations for electric vehicle operations and charging within a fleet of right-sized automated vehicles providing on-demand public mobility services. The current focus of research is on the operational complexities and associated challenges for automated/autonomous vehicles employing electric drivetrains and the resultant need for an efficient battery charging process while vehicles are operating in an "on-demand" mode of service. The blossoming of microtransit with shared-ride and point-to-point dispatching of each vehicle instills complex operations, with multiple mobility-on-demand transit operating sites being deployed, studied, and analyzed across North America. As a starting point, the authors' experience over the past 20 years with the analysis of automated transit network systems operating on and within dedicated and protected transitways provides initial insights into the system-level operational implications for maintaining a sufficient battery charge for a fleet of automated vehicles. Lessons learned through the prior analyses of automated transit network systems operating in on-demand service are identified, along with the capital cost implications for the requisite operating fleet size and charging station infrastructure for various approaches. These costs are summarized in juxtaposition with the benefits of realizing the higher goals of reducing environmental impacts and energy use within automated mobility districts as automated/autonomous vehicle technology matures. Finally, the discussion addresses key aspects of battery-electric propulsion for managed fleets in fully automated operation that will be studied as the third phase of research continues.

ADVANCED PROPULSION SYSTEMS↗

Proton-conducting oxides for energy conversion and storage

Proton-conducting oxides are a class of solid-state ion-conducting ceramic materials that demonstrate significant hydrogen ion (proton) conductivity at intermediate temperatures (e.g., 300–700 °C). They are garnering significant attention due to several unique characteristics that distinguish them from both higher temperature oxygen ion conducting oxides and lower temperature proton-conducting polymers. By enabling proton-mediated electrochemistry under both dry and wet environments at moderate temperatures, protonic ceramics provide unique opportunities to enhance or synergize a diverse range of complementary electrochemical and thermochemical processes. Because of this potential, significant efforts have been devoted to advancing numerous energy-related applications using these materials. This review aims to comprehensively summarize these applications and analyze the most up-to-date and future developments of proton-conducting oxides. We aim to bring together this diverse subject matter by integrating the fundamentals of proton-conducting oxides with application-oriented insights. We begin with a historical roadmap, followed by a basic overview of the materials, theories and fundamentals, and fabrication and processing technologies underlying the field. The central section of our review summarizes major applications and developments of proton-conducting ceramics, ranging from maturing applications approaching commercialization to embryonic technologies just now emerging from the lab. These include protonic ceramic fuel cells, protonic ceramic electrolysis cells, reversible protonic ceramic electrochemical cells, protonic ceramic membrane reactors, and protonic ceramic electrochemical reactors. For each application, we analyze both the prospects and challenges and offer recommendations for future research directions so that tomorrow's researchers can continue to advance the development and commercialization of these fascinating materials.

Duan, Chuancheng (ORCID:0000000218261415)↗

Scaling and merging time-resolved pink-beam diffraction with variational inference

Time-resolved x-ray crystallography (TR-X) at synchrotrons and free electron lasers is a promising technique for recording dynamics of molecules at atomic resolution. While experimental methods for TR-X have proliferated and matured, data analysis is often difficult. Extracting small, time-dependent changes in signal is frequently a bottleneck for practitioners. Recent work demonstrated this challenge can be addressed when merging redundant observations by a statistical technique known as variational inference (VI). However, the variational approach to time-resolved data analysis requires identification of successful hyperparameters in order to optimally extract signal. In this case study, we present a successful application of VI to time-resolved changes in an enzyme, DJ-1, upon mixing with a substrate molecule, methylglyoxal. We present a strategy to extract high signal-to-noise changes in electron density from these data. Furthermore, we conduct an ablation study, in which we systematically remove one hyperparameter at a time to demonstrate the impact of each hyperparameter choice on the success of our model. We expect this case study will serve as a practical example for how others may deploy VI in order to analyze their time-resolved diffraction data.

47 OTHER INSTRUMENTATION↗