Progress and directions in low-cost redox flow batteries for large-scale energy storage
This article reviews recent progresses and directions of redox flow battery technologies.
Li, Bin↗
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Linking atmospheric pollution to cryospheric change in the Third Pole region: current progress and future prospects
ABSTRACT The Tibetan Plateau and its surroundings are known as the Third Pole (TP). This region is noted for its high rates of glacier melt and the associated hydrological shifts that affect water supplies in Asia. Atmospheric pollutants contribute to climatic and cryospheric changes through their effects on solar radiation and the albedos of snow and ice surfaces; moreover, the behavior and fates within the cryosphere and environmental impacts of environmental pollutants are topics of increasing concern. In this review, we introduce a coordinated monitoring and research framework and network to link atmospheric pollution and cryospheric changes (APCC) within the TP region. We then provide an up-to-date summary of progress and achievements related to the APCC research framework, including aspects of atmospheric pollution's composition and concentration, spatial and temporal variations, trans-boundary transport pathways and mechanisms, and effects on the warming of atmosphere and changing in Indian monsoon, as well as melting of glacier and snow cover. We highlight that exogenous air pollutants can enter into the TP’s environments and cause great impacts on regional climatic and environmental changes. At last, we propose future research priorities and map out an extended program at the global scale. The ongoing monitoring activities and research facilitate comprehensive studies of atmosphere–cryosphere interactions, represent one of China's key research expeditions to the TP and the polar regions and contribute to the global perspective of earth system science.
54 ENVIRONMENTAL SCIENCES↗
DNA Sequence-Based Identification of Fusarium : A Work in Progress
Accurate species-level identification of an etiological agent is crucial for disease diagnosis and management because knowing the agent’s identity connects it with what is known about its host range, geographic distribution, and toxin production potential. This is particularly true in publishing peer-reviewed disease reports, where imprecise and/or incorrect identifications weaken the public knowledge base. This can be a daunting task for phytopathologists and other applied biologists that need to identify Fusarium in particular, because published and ongoing multilocus molecular systematic studies have highlighted several confounding issues. Paramount among these are: (i) this agriculturally and clinically important genus is currently estimated to comprise more than 400 phylogenetically distinct species (i.e., phylospecies), with more than 80% of these discovered within the past 25 years; (ii) approximately one-third of the phylospecies have not been formally described; (iii) morphology alone is inadequate to distinguish most of these species from one another; and (iv) the current rapid discovery of novel fusaria from pathogen surveys and accompanying impact on the taxonomic landscape is expected to continue well into the foreseeable future. To address the critical need for accurate pathogen identification, our research groups are focused on populating two web-accessible databases (FUSARIUM-ID v.3.0 and the nonredundant National Center for Biotechnology Information nucleotide collection that includes GenBank) with portions of three phylogenetically informative genes (i.e., TEF1, RPB1, and RPB2) that resolve at or near the species level in every Fusarium species. The objectives of this Special Report, and its companion in this issue ( Torres-Cruz et al. 2022 ), are to provide a progress report on our efforts to populate these databases and to outline a set of best practices for DNA sequence-based identification of fusaria.
Plant Sciences↗
Imaging the Progression of Radiolytic Damage in Molecular Crystals with Scanning Nanobeam Electron Diffraction
Almost every electron microscopy experiment is fundamentally limited by radiation damage. Nevertheless, little is known about the onset and progression of radiolysis in beam-sensitive materials. Here we apply ambient-temperature scanning nanobeam electron diffraction to record simultaneous dual-space movies of organic and organometallic nanocrystals at sequential stages of beam-induced radiolytic decay. We show that the underlying mosaic of coherently diffracting domains undergoes internal rearrangement as a function of accumulating electron fluence, causing the intensities of some associated Bragg reflections to fade nonmonotonically. Furthermore, we demonstrate that repeated irradiation at a single probe position leads to the isotropic propagation of delocalized radiolytic damage well beyond the direct footprint of the incident beam. We refer to these expanding tides of amorphization as “impact craters.”
59 BASIC BIOLOGICAL SCIENCES↗
Single-Net Continual Learning with Progressive Segmented Training
There is an increasing need of continual learning in dynamic systems, such as the self-driving vehicle, the surveillance drone, and the robotic system. Such a system requires learning from the data stream, training the model to preserve previous information and adapt to a new task, and generating a single-headed vector for future inference. Different from previous approaches with dynamic structures, this work focuses on a single network and model segmentation to prevent catastrophic forgetting. Leveraging the redundant capacity of a single network, model parameters for each task are separated into two groups: one important group which is frozen to preserve current knowledge, and secondary group to be saved (not pruned) for a future learning. A fixed-size memory containing a small amount of previously seen data is further adopted to assist the training. Without additional regularization, the simple yet effective approach of Progressive Segmented Training (PST) successfully incorporates multiple tasks and achieves the state-of-the-art accuracy in the single-head evaluation on CIFAR-10 and CIFAR-100 datasets. Moreover, the segmented training significantly improves computation efficiency in continual learning at the edge.
Du, Xiaocong↗
Progress Towards Prognostic Health Management of Passive Components in Advanced Small Modular Reactors
Sustainable nuclear power to promote energy security and to reduce greenhouse gas emissions are two key national energy priorities. The development of deployable small modular reactors (SMRs) is expected to support these objectives by developing technologies that improve the reliability, sustain safety, and improve affordability of new reactors. Advanced SMRs (AdvSMRs) refer to a specific class of SMRs and are based on modularization of advanced reactor concepts. Prognostic health management (PHM) systems can benefit both the safety and economics of deploying AdvSMRs and can play an essential role in managing the inspection and maintenance of passive components in AdvSMR systems. This paper describes progress on development of a prototypic PHM system for AdvSMR passive components, with thermal creep chosen as the target degradation mechanism.
prognostics, small modular reactors, passive compo↗
Progress Towards Prognostic Health Management of Passive Components in Advanced Reactors – Model Selection and Evaluation
This paper presents recent progress towards developing a prognostic health management framework for passive components of advanced reactors (AR). The focus of this paper is on lifecycle prognostics for passive components using a Bayesian prognostic algorithm that provides a natural framework for incorporating different sources of variability, and uncertainties inherent in the operations of AR. High-temperature creep damage, a prototypic failure mechanism in AR materials, is used as the context for this research. A Bayesian model selection approach is implemented to select the appropriate creep degradation model at any given time, using relevant sensor measurements reflecting the material degradation state. The model selection approach, based on reversible jump Markov chain Monte Carlo methods, is integrated with Bayesian particle filter-based prognostic framework. The proposed approach is evaluated using strain measurements obtained from accelerated creep testing of stainless steel specimens. Results indicate feasibility of the proposed approach in accurately identifying the creep degradation stage from the available measurements at a given time. Effect of uncertainties in material degradation model and measurement noise on the performance of the prognostic algorithm is also investigated.
advanced reactor prognostics↗
Updates on the Progress of the Alternate Topology Modulator (AT-HVCM) to support the Proton Power Upgrade (PPU) at the Spallation Neutron Source
The AT-HVCM, achieved by series-stacking the dual-function resonant filter capacitors following each rectification stage, is the baseline design for the PPU project at the SNS [1]. The project requires three AT-HVCM modulators to power 28 additional 700kW klystrons and associated high beta cavities to accelerate 38mA of beam current to 1.3GeV. Each modulator produces an 82 kV, 120A output pulse of 1.35ms duration at a 60Hz repetition rate. The AT design approach improves upon the existing HVCM topology, reducing stresses on the H bridge IGBTs using zero voltage (ZVS) and current switching (ZCS) techniques and on the resonant filter capacitors by limiting voltage reversal. This paper reviews the prototype development progress, currently focused on evaluating system reliability, and discusses some design techniques to achieve the modulator performance requirements.
Solley, Dennis J.↗
Mitigation of Dust Impact on Solar Collectors by Water-Free Cleaning With Transparent Electrodynamic Films: Progress and Challenges
Energy-yield loss caused by soiling of photovoltaic modules and concentrated solar power (CSP) mirrors in utility- scale power plants installed in semiarid lands and deserts would result in unsustainable demands for fresh water needed for clean- ing. This paper reviews the progress of the electrodynamic screen (EDS) film technology for frequent water-free cleaning with low- energy requirements. Results presented here, based on laboratory- scale EDS-film-laminated solar panel cleaning, show that the output power can be restored higher than 95% of the initial power under clean conditions. For solar mirrors, the specular reflection efficiency can be maintained over 90% ensuring high efficiency of the CSP plants. Operation of the EDS film for main- taining high optical efficiency of solar collectors requires less than 0.2 Wh/ma 2 /cleaning cycle. Here, principles, optical modeling, construc- tion, lamination of the EDS films on modules and mirrors, and experimental data showing optical efficiency restoration without water consumption are presented. Lastly, current challenges in developing electrodes that would meet optical and conduction properties
14 SOLAR ENERGY↗
Lithium-Ion Battery Technologies for Electric Vehicles: Progress and challenges
Electric Vehicle (EV) sales and adoption have seen a significant growth in recent years, thanks to advancements and cost reduction in lithium-ion battery technology, attractive performance of EVs, governments' incentives, and the push to reduce greenhouse gases and pollutants. In this article, we will explore the progress in lithium-ion batteries and their future potential in terms of energy density, life, safety, and extreme fast charge. Here we will also discuss material sourcing, supply chain, and end-of-life-cycle management as they have become important considerations in the ecosystem of batteries for the sustained growth and adoption of EVs. With significant government and private sector investments in research and development, processing, and manufacturing and advances in anodes (lithium and silicon), cathodes (high nickel), designs, supply chain development, and the circularity of lithium-ion batteries, lithium-based batteries are on track to make EVs mainstream, addressing climate concerns of fossil-fueled vehicles.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Reinforcement Learning for Volt- Var Control: A Novel Two-stage Progressive Training Strategy
This paper develops a reinforcement learning (RL) approach to solve a cooperative, multi-agent Volt-Var Control (VVC) problem for high solar penetration distribution systems. The ingenuity of our RL method lies in a novel two-stage progressive training strategy that can effectively improve training speed and convergence of the machine learning algorithm. In Stage 1 (individual training), while holding all the other agents inactive, we separately train each agent to obtain its own optimal VVC actions in the action space: fconsume, generate, do-nothingg. In Stage 2 (cooperative training), all agents are trained again coordinatively to share VVC responsibility. Rewards and costs in our RL scheme include (i) a system-level reward (for taking an action), (ii) an agent-level reward (for doing-nothing), and (iii) an agent-level action cost function. This new framework allows rewards to be dynamically allocated to each agent based on their contribution while accounting for the trade-off between control effectiveness and action cost. The proposed methodology is tested and validated in a modified IEEE 123-bus system using realistic PV and load profiles. Simulation results confirm that the proposed approach is robust and computationally efficient; and it achieves desirable volt-var control performance under a wide range of operation conditions.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Progress on the Development of the Nb 3 Sn 11T Dipole for the High Luminosity Upgrade of LHC
The high-luminosity large hadron collider (LHC) project at CERN entered into the production phase in October 2015 after the completion of the design study phase. In the meantime, the development of the 11 T dipole needed for the upgrade of the collimation system of the machine made significant progress with very good performance of the first two-in-one magnet model of 2-m length made at CERN. The 11 T dipole, which is more powerful than the current main dipoles of LHC, can be made shorter with an equivalent integrated field. This will allow creating space for the installation of additional collimators in specific locations of the dispersion suppressor regions. Following tests carried out during heavy ions runs of LHC in the end of 2015, and a more recent review of the project budget, the installation plan for the 11 T dipole was revised. Consequently, one 11 T dipole full assembly containing two 11 T dipoles of 5.5-m length will be installed on either side of interaction point 7. These two units shall be installed during the long shutdown 2 in years 2019-2020. After a brief reminder on the design features of the magnet, this paper describes the current status of the development activities, in particular the short model programme and the construction of the first full scale prototype at CERN. Finally, critical operations such as the reaction treatment and the coil impregnation are discussed, the quench performance tests results of the two-in-one model are reviewed and finally, the plan toward the production for the long shut down 2 is described.
43 PARTICLE ACCELERATORS↗
Hyperspectral X-ray Imaging: Progress Towards Chemical Analysis in the SEM
The Hyperspectral X-ray Imaging (HXI) project will enable non-destructive chemical-state determination of nano-scale samples in the electron microscope for nuclear safeguards applications. To efficiently measure chemical state through electron-excited X-ray emission requires a combination of wide spectral bandwidth, high resolution, and high count rate capability. We are building a next-generation X-ray detector based on an array of transition edge sensors (TESs) to make these measurements possible and routine in the scanning electron microscope (SEM). Leveraging the large pixel densities afforded by microwave multiplexing readout and continuous, uninterrupted operation of a cryogen-free dilution refrigerator, this instrument will have efficiency to allow chemical species identification of nano-scale samples in hours instead of days to weeks. We describe prototype pixel designs for this HXI instrument, comprising three pixel types that will make up the hybrid TES array. Engineering design of the integrated HXI cryostat and SEM system is in progress, with full detector commissioning expected in Spring 2021 followed closely by full-scale integration with the SEM. Furthermore, we also report on the commissioning of a complementary TES-based X-ray emission spectroscopy platform for bulk samples to build a spectral library for HXI sample identification.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Cross talk between RNA N6‐methyladenosine methyltransferase‐like 3 and miR‐186 regulates hepatoblastoma progression through Wnt/β‐catenin signalling pathway
Abstract Objectives N6‐methyladenosine (m6A) is a ubiquitous epigenetic RNA modification that plays a pivotal role in tumour development and metastasis. In this study, we aimed to investigate the expression profiling, clinical significance, biological function and the regulation of m6A‐related genes in hepatoblastoma (HB). Materials and Methods The mRNA and protein expression levels of m6A‐related genes were analysed using Gene Expression Omnibus (GEO) and tissue microarray (TMA) cohort. Kaplan‐Meier analysis was performed to evaluate the prognostic value of m6A‐related genes in HB. Knockdown of m6A‐related genes was conducted to analyse its function on cell proliferation, migration and invasion. Furthermore, bioinformatics analysis and experimental verification were used to explore the potential molecular mechanism and signalling pathway. Results We found that most m6A‐related genes were significantly upregulated in HB tumour tissues. High levels of methyltransferase‐like 3 (METTL3, P = .013), YTHDF2 ( P = .037) and FTO ( P = .032) indicated poor clinical outcomes, and the upregulation of METTL3 was an independent prognostic factor in HB patients. Functional assays showed that knockdown of METTL3 could dramatically suppress the proliferation, migration and invasion of HB cells. In addition, METTL3 was identified to be a direct target of microRNA‐186 (miR‐186). Consistently, miR‐186 was low expressed in HB tumour tissues. Moreover, overexpression of miR‐186 significantly inhibited cell aggressive phenotype both in vitro and in vivo, while the inhibitory effect could be reversed by METTL3 overexpression. Mechanism study indicated that miR‐186/METTL3 axis contributed to the progression of HB via the Wnt/β‐catenin signalling pathway. Conclusions M6A‐related genes were frequently dysregulated in HB. miR‐186/METTL3/Wnt/β‐catenin axis might serve as novel therapeutic targets and prognostic biomarkers in HB.
Cui, Xichun↗
Progress toward a universal biomedical data translator
Clinical, biomedical, and translational science has reached an inflection point in the breadth and diversity of available data and the potential impact of such data to improve human health and well-being. However, the data are often siloed, disorganized, and not broadly accessible due to discipline-specific differences in terminology and representation. To address these challenges, the Biomedical Data Translator Consortium has developed and tested a pilot knowledge graph-based “Translator” system capable of integrating existing biomedical data sets and “translating” those data into insights intended to augment human reasoning and accelerate translational science. Having demonstrated feasibility of the Translator system, the Translator program has since moved into development, and the Translator Consortium has made significant progress in the research, design, and implementation of an operational system. Herein, we describe the current system’s architecture, performance, and quality of results. We apply Translator to several real-world use cases developed in collaboration with subject-matter experts. Finally, we discuss the scientific and technical features of Translator and compare those features to other state-of-the-art, biomedical graph-based question-answering systems.
60 APPLIED LIFE SCIENCES↗
Increased leaf area index and efficiency drive enhanced production under elevated atmospheric [ CO 2 ] in a pine‐dominated stand showing no progressive nitrogen limitation
Abstract Enhancement of net primary production (NPP) in forests as atmospheric [CO 2 ] increases is likely limited by the availability of other growth resources. The Duke Free Air CO 2 Enrichment (FACE) experiment was located on a moderate‐fertility site in the southeastern US, in a loblolly pine ( Pinus taeda L.) plantation with broadleaved species growing mostly in mid‐canopy and understory. Duke FACE ran from 1994 to 2010 and combined elevated [CO 2 ] (eCO 2 ) with nitrogen (N) additions. We assessed the spatial and temporal variation of NPP response using a dataset that includes previously unpublished data from 6 years of the replicated CO 2 × N experiment and extends to 2 years beyond the termination of enrichment. Averaged over time (1997–2010), NPP of pine and broadleaved species were 38% and 52% higher under eCO 2 compared to ambient conditions. Furthermore, there was no evidence of a decline in enhancement over time in any plot regardless of its native site quality. The relation between spatial variation in the response and native site quality was suggested but inconclusive. Nitrogen amendments under eCO 2 , in turn, resulted in an additional 11% increase in pine NPP. For pine, the eCO 2 ‐induced increase in NPP was similar above‐ and belowground and was driven by both increased leaf area index ( L ) and production efficiency (PE = NPP/ L ). For broadleaved species, coarse‐root biomass production was more than 200% higher under eCO 2 and accounted for the entire production response, driven by increased PE. Notably, the fraction of annual NPP retained in total living biomass was higher under eCO 2 , reflecting a slight shift in allocation fraction to woody mass and a lower mortality rate. Our findings also imply that tree growth may not have been only N‐limited, but perhaps constrained by the availability of other nutrients. The observed sustained NPP enhancement, even without N‐additions, demonstrates no progressive N limitation.
59 BASIC BIOLOGICAL SCIENCES↗
Breeding progress and preparedness for mass‐scale deployment of perennial lignocellulosic biomass crops switchgrass, miscanthus, willow and poplar
Abstract Genetic improvement through breeding is one of the key approaches to increasing biomass supply. This paper documents the breeding progress to date for four perennial biomass crops (PBCs) that have high output–input energy ratios: namely Panicum virgatum (switchgrass), species of the genera Miscanthus (miscanthus), Salix (willow) and Populus (poplar). For each crop, we report on the size of germplasm collections, the efforts to date to phenotype and genotype, the diversity available for breeding and on the scale of breeding work as indicated by number of attempted crosses. We also report on the development of faster and more precise breeding using molecular breeding techniques. Poplar is the model tree for genetic studies and is furthest ahead in terms of biological knowledge and genetic resources. Linkage maps, transgenesis and genome editing methods are now being used in commercially focused poplar breeding. These are in development in switchgrass, miscanthus and willow generating large genetic and phenotypic data sets requiring concomitant efforts in informatics to create summaries that can be accessed and used by practical breeders. Cultivars of switchgrass and miscanthus can be seed‐based synthetic populations, semihybrids or clones. Willow and poplar cultivars are commercially deployed as clones. At local and regional level, the most advanced cultivars in each crop are at technology readiness levels which could be scaled to planting rates of thousands of hectares per year in about 5 years with existing commercial developers. Investment in further development of better cultivars is subject to current market failure and the long breeding cycles. We conclude that sustained public investment in breeding plays a key role in delivering future mass‐scale deployment of PBCs.
09 BIOMASS FUELS↗
Root system architecture in cereals: progress, challenges and perspective
We report roots are essential multifunctional plant organs involved in water and nutrient uptake, metabolite storage, anchorage, mechanical support, and interaction with the soil environment. Understanding of this ‘hidden half’ provides potential for manipulation of root system architecture (RSA) traits to optimize resource use efficiency and grain yield in cereal crops. Unfortunately, root traits are highly neglected in breeding due to the challenges of phenotyping, but could have large rewards if the variability in RSA traits can be fully exploited. Until now, a plethora of genes have been characterized in detail for their potential role in improving RSA. The use of forward genetics approaches to find sequence variations in genes underpinning desirable RSA would be highly beneficial. Advances in computer vision applications have allowed image-based approaches for high-throughput phenotyping of RSA traits that can be used by any laboratory worldwide to make progress in understanding root function and dissection of the genetics. At the same time, the frontiers of root measurement include non-invasive methods like X-ray computer tomography and magnetic resonance imaging that facilitate new types of temporal studies. Root physiology and ecology are further supported by spatiotemporal root simulation modeling. The discovery of component traits providing improved resilience and yield advantage in target environments is a key necessity for mainstreaming root-based cereal breeding. The integrated use of pan-genome resources, now available in most cereals, coupled with new in-field phenotyping platforms has the potential for precise selection of superior genotypes with improved RSA.
59 BASIC BIOLOGICAL SCIENCES↗