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At least 847 records · Page 47

Accelerating the development of new solar absorbers by photoemission characterization coupled with density functional theory

Abstract The expectation to progress towards Terawatts production by solar technologies requires continuous development of new materials to improve efficiency and lower the cost of devices beyond what is currently available at industrial level. At the same time, the turnaround time to make the investment worthwhile is progressively shrinking. Whereas traditional absorbers have developed in a timeframe spanning decades, there is an expectation that emerging materials will be converted into industrially relevant reality in a much shorter timeframe. Thus, it becomes necessary to develop new approaches and techniques that could accelerate decision-making steps on whether further research on a material is worth pursuing or not. In this review, we will provide an overview of the photoemission characterization methods and theoretical approaches that have been developed in the past decades to accelerate the transfer of emerging solar absorbers into efficient devices.

14 SOLAR ENERGY↗

Energy Storage in Long-Term System Models: A Review of Considerations, Best Practices, and Research Needs

Technological change and policy support have heightened expectations for the role of energy storage in power systems, creating a need to enhance representations of energy storage in long-term models to inform decision-making. Energy storage technologies have complex and diverse cost, value, and performance characteristics that make them challenging to model, but there is limited guidance about best practices and research gaps for energy storage analysis. This paper reviews the literature and draws upon our collective experience to provide recommendations to analysts on approaches for representing energy storage in long-term electric sector models, navigating tradeoffs in model development, and identifying research gaps for existing tools and data. The review focuses on national-scale models with technological, temporal, and regional detail given their prevalence in planning and policy, though many insights are transferable to other modeling contexts. It also offers guidance to consumers of model outputs on proper use and interpretation based on model strengths and limitations. In particular, this review demonstrates the importance of capturing how the values of energy storage and other resources change as the system composition changes (e.g. with different levels of storage, renewables deployment, and emissions outcomes). These considerations require model detail like high spatiotemporal resolutions and endogenous investments that global integrated assessment models and price-taker frameworks do not typically resolve. Research gaps include linking tools of different resolutions, developing reduced-form representations of value streams, incorporating hybrid energy storage and renewable systems, and representing longer-duration energy storage technologies.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Magnesium- and intermetallic alloys-based hydrides for energy storage: modelling, synthesis and properties

Hydrides based on magnesium and intermetallic compounds provide a viable solution to the challenge of energy storage from renewable sources, thanks to their ability to absorb and desorb hydrogen in a reversible way with a proper tuning of pressure and temperature conditions. Therefore, they are expected to play an important role in the clean energy transition and in the deployment of hydrogen as an efficient energy vector. This review, by experts of Task 40 ‘Energy Storage and Conversion based on Hydrogen’ of the Hydrogen Technology Collaboration Programme of the International Energy Agency, reports on the latest activities of the working group ‘Magnesium- and Intermetallic alloys-based Hydrides for Energy Storage’. The following topics are covered by the review: multiscale modelling of hydrides and hydrogen sorption mechanisms; synthesis and processing techniques; catalysts for hydrogen sorption in Mg; Mg-based nanostructures and new compounds; hydrides based on intermetallic TiFe alloys, high entropy alloys, Laves phases, and Pd-containing alloys. Finally, an outlook is presented on current worldwide investments and future research directions for hydrogen-based energy storage.

Energy storage↗

Digital coded exposure formation of frames from event-based imagery

Abstract Event-driven neuromorphic imagers have a number of attractive properties including low-power consumption, high dynamic range, the ability to detect fast events, low memory consumption and low band-width requirements. One of the biggest challenges with using event-driven imagery is that the field of event data processing is still embryonic. In contrast, decades worth of effort have been invested in the analysis of frame-based imagery. Hybrid approaches for applying established frame-based analysis techniques to event-driven imagery have been studied since event-driven imagers came into existence. However, the process for forming frames from event-driven imagery has not been studied in detail. This work presents a principled digital coded exposure approach for forming frames from event-driven imagery that is inspired by the physics exploited in a conventional camera featuring a shutter. The technique described in this work provides a fundamental tool for understanding the temporal information content that contributes to the formation of a frame from event-driven imagery data. Event-driven imagery allows for the application of arbitrary virtual digital shutter functions to form the final frame on a pixel-by-pixel basis. The proposed approach allows for the careful control of the spatio-temporal information that is captured in the frame. Furthermore, unlike a conventional physical camera, event-driven imagery can be formed into any variety of possible frames in post-processing after the data is captured. Furthermore, unlike a conventional physical camera, coded-exposure virtual shutter functions can assume arbitrary values including positive, negative, real, and complex values. The coded exposure approach also enables the ability to perform applications of industrial interest such as digital stroboscopy without any additional hardware. The ability to form frames from event-driven imagery in a principled manner opens up new possibilities in the ability to use conventional frame-based image processing techniques on event-driven imagery.

47 OTHER INSTRUMENTATION↗

Techno-economic analysis of synthetic fuel production from existing nuclear power plants across the United States

Abstract Low carbon synfuel can reduce dependence on fossil fuels like diesel and jet fuel, and, with large-scale cost-effective production, contribute to global transportation sector decarbonization, Simultaneously, nuclear power plants are struggling economically due to falling wholesale electricity prices. Converting existing nuclear plants for synfuel production could preserve these low-carbon assets and enable large-scale synfuel production, yet no comprehensive technoeconomic analysis exists. This study evaluates the potential of integrating synthetic fuel production with five US nuclear plants, considering electricity and fuel markets and carbon dioxide source access. Such integration could enhance nuclear plant profitability by up to $792 million and offer a 10% return on investment over 20 years. The hydrogen production tax credit from the 2022 Inflation Reduction Act is crucial, comprising 75% of revenues on average. Carbon feedstock transportation has the highest cost at 35%, followed closely by synfuel production capital costs. Incentive policies are thus key for the decarbonization of the transportation sector and the economic importance of the geographic location of Integrated Energy Systems.

Garrouste, Marisol (ORCID:0000000168388644)↗

Computational and Systems Biology Advances to Enable Bioagent Agnostic Signatures

Enumerated threat agent lists have long driven biodefense priorities. The global SARS-CoV-2 pandemic demonstrated the limitations of searching for known threat agents as compared to a more agnostic approach. Recent technological advances are enabling agent-agnostic biodefense, especially through the integration of multi-modal observations of host-pathogen interactions directed by a human immunological model. Although well-developed technical assays exist for many aspects of human-pathogen interaction, the analytic methods and pipelines to combine and holistically interpret the results of such assays are immature and require further investments to exploit new technologies. In this manuscript, we discuss potential immunologically based bioagent-agnostic approaches and the computational tool gaps the community should prioritize filling.

59 BASIC BIOLOGICAL SCIENCES↗

White-tailed deer responses to acoustic predator cues are contingent upon past land use and contemporary fire regime

Prey can assess the immediate risk of predation by detecting cues of predator presence, and it is expected that prey should invest in costly antipredator behaviors when a cue of predator presence is detected. Features of the habitat in which the cue is detected, such as vegetative concealment, serve as indirect cues of risk and can mediate how prey respond to direct cues of predator presence. Past agricultural land use and contemporary fire regimes are common disturbances that may modify prey perceptions of risk and could, therefore, alter prey responses to direct cues of predator presence. Here we examined whether the overlap of these two disturbances affected white-tailed deer (Odocoileus virginianus) responses to cues of predator presence by measuring deer vigilance and foraging bout duration in response to coyote (Canis latrans) vocalizations across 20 woodlands that varied in past land use and contemporary fire regime. Frequent fire regimes consistently increased deer visibility to predators across both land-use history contexts. Deer exhibited no behavioral response to the predator cue in habitats containing infrequent fire regimes or agricultural legacies. Deer responded to the cue in frequently burned woodlands without agricultural legacies through increased vigilance and time spent at a foraging location. These findings reveal that land-use legacies and contemporary fire regimes can mediate how prey respond to direct cues of risk. They also suggest that prey may balance the uncertainty associated with cues of predation risk with the urgency of responding to a potential attack by being vigilant and remaining in place.

60 APPLIED LIFE SCIENCES↗

Viability, behavior, and color expression in the offspring of matings between common wall lizard Podarcis muralis color morphs

Abstract Color polymorphisms are widely studied to identify the mechanisms responsible for the origin and maintenance of phenotypic variability in nature. Two of the mechanisms of balancing selection currently thought to explain the long-term persistence of polymorphisms are the evolution of alternative phenotypic optima through correlational selection on suites of traits including color and heterosis. Both of these mechanisms can generate differences in offspring viability and fitness arising from different morph combinations. Here, we examined the effect of parental morph combination on fertilization success, embryonic viability, newborn quality, antipredator, and foraging behavior, as well as inter-annual survival by conducting controlled matings in a polymorphic lacertid Podarcis muralis, where color morphs are frequently assumed to reflect alternative phenotypic optima (e.g., alternative reproductive strategies). Juveniles were kept in outdoor tubs for a year in order to study inter-annual growth, survival, and morph inheritance. In agreement with a previous genome-wide association analysis, morph frequencies in the year-old juveniles matched the frequencies expected if orange and yellow expressions depended on recessive homozygosity at 2 separate loci. Our findings also agree with previous literature reporting higher reproductive output of heavy females and the higher overall viability of heavy newborn lizards, but we found no evidence for the existence of alternative breeding investment strategies in female morphs, or morph-combination effects on offspring viability and behavior. We conclude that inter-morph breeding remains entirely viable and genetic incompatibilities are of little significance for the maintenance of discrete color morphs in P. muralis from the Pyrenees.

Abalos, Javier↗

Open Hardware in Science: The Benefits of Open Electronics

Abstract Openly shared low-cost electronic hardware applications, known as open electronics, have sparked a new open-source movement, with much untapped potential to advance scientific research. Initially designed to appeal to electronic hobbyists, open electronics have formed a global “maker” community and are increasingly used in science and industry. In this perspective article, we review the current costs and benefits of open electronics for use in scientific research ranging from the experimental to the theoretical sciences. We discuss how user-made electronic applications can help (I) individual researchers, by increasing the customization, efficiency, and scalability of experiments, while improving data quantity and quality; (II) scientific institutions, by improving access to customizable high-end technologies, sustainability, visibility, and interdisciplinary collaboration potential; and (III) the scientific community, by improving transparency and reproducibility, helping decouple research capacity from funding, increasing innovation, and improving collaboration potential among researchers and the public. We further discuss how current barriers like poor awareness, knowledge access, and time investments can be resolved by increased documentation and collaboration, and provide guidelines for academics to enter this emerging field. We highlight that open electronics are a promising and powerful tool to help scientific research to become more innovative and reproducible and offer a key practical solution to improve democratic access to science.

Oellermann, Michael (ORCID:0000000153926737)↗

Wildfire impact on soil microbiome life history traits and roles in ecosystem carbon cycling

Abstract Wildfires, which are increasing in frequency and severity with climate change, reduce soil microbial biomass and alter microbial community composition and function. The soil microbiome plays a vital role in carbon (C) and nitrogen (N) cycling, but its complexity makes it challenging to predict post-wildfire soil microbial dynamics and resulting impacts on ecosystem biogeochemistry. The application of biogeochemically relevant conceptual trait-based frameworks to the soil microbiome can distill this complexity, enabling enhanced predictability of soil microbiome recovery following wildfire and subsequent impacts to biogeochemical cycles. Conceptual frameworks that have direct links to soil C and N cycling have been developed for the soil microbiome; the Y-A-S framework overviews soil microbiome life history strategies that have tradeoffs with one another and others have proposed frameworks specific to wildfire. Here, we aimed to delineate post-wildfire changes of bacterial traits in western US coniferous forests to inform how severe wildfire influences soil microbiome recovery and resultant biogeochemical cycling. We utilized a comprehensive metagenome-assembled genome catalog from post-wildfire soils representing 1 to 11 years following low- and high-severity burning to identify traits that enable the persistence of microbial taxa in burned soils and influence ecosystem C and N cycling. We found that high-severity wildfire initially selects for fast growers and, up to a decade post-fire, taxa that invest in genes for acquiring diverse resources from the external environment, which in combination could increase soil C losses. This work begins to disentangle how climate change–induced shifts in wildfire behavior might alter microbially mediated soil biogeochemical cycling.

Nelson, Amelia R.↗

Environment-specific virocell metabolic reprogramming

Abstract Viruses impact microbial systems through killing hosts, horizontal gene transfer, and altering cellular metabolism, consequently impacting nutrient cycles. A virus-infected cell, a “virocell,” is distinct from its uninfected sister cell as the virus commandeers cellular machinery to produce viruses rather than replicate cells. Problematically, virocell responses to the nutrient-limited conditions that abound in nature are poorly understood. Here we used a systems biology approach to investigate virocell metabolic reprogramming under nutrient limitation. Using transcriptomics, proteomics, lipidomics, and endo- and exo-metabolomics, we assessed how low phosphate (low-P) conditions impacted virocells of a marine Pseudoalteromonas host when independently infected by two unrelated phages (HP1 and HS2). With the combined stresses of infection and nutrient limitation, a set of nested responses were observed. First, low-P imposed common cellular responses on all cells (virocells and uninfected cells), including activating the canonical P-stress response, and decreasing transcription, translation, and extracellular organic matter consumption. Second, low-P imposed infection-specific responses (for both virocells), including enhancing nitrogen assimilation and fatty acid degradation, and decreasing extracellular lipid relative abundance. Third, low-P suggested virocell-specific strategies. Specifically, HS2-virocells regulated gene expression by increasing transcription and ribosomal protein production, whereas HP1-virocells accumulated host proteins, decreased extracellular peptide relative abundance, and invested in broader energy and resource acquisition. These results suggest that although environmental conditions shape metabolism in common ways regardless of infection, virocell-specific strategies exist to support viral replication during nutrient limitation, and a framework now exists for identifying metabolic strategies of nutrient-limited virocells in nature.

59 BASIC BIOLOGICAL SCIENCES↗

Bacterial population-level trade-offs between drought tolerance and resource acquisition traits impact decomposition

Microbes drive fundamental ecosystem processes, such as decomposition. Environmental stressors are known to affect microbes, their fitness, and the ecosystem functions that they perform; yet, understanding the causal mechanisms behind this influence has been difficult. We used leaf litter on soil surface as a model in situ system to assess changes in bacterial genomic traits and decomposition rates for 18 months with drought as a stressor. We hypothesized that genome-scale trade-offs due to investment in stress tolerance traits under drought reduce the capacity for bacterial populations to carry out decomposition, and that these population-level trade-offs scale up to impact emergent community traits, thereby reducing decomposition rates. We observed drought tolerance mechanisms that were heightened in bacterial populations under drought, identified as higher gene copy numbers in metagenome-assembled genomes. A subset of populations under drought had reduced carbohydrate-active enzyme genes that suggested—as a trade-off—a decline in decomposition capabilities. These trade-offs were driven by community succession and taxonomic shifts as distinct patterns appeared in populations. We show that trait–trade-offs in bacterial populations under drought could scale up to reduce overall decomposition capabilities and litter decay rates. Using a trait-based approach to assess the population ecology of soil bacteria, we demonstrate genome-level trade-offs in response to drought with consequences for decomposition rates.

59 BASIC BIOLOGICAL SCIENCES↗

Sulfide stress tolerance as a controller of methane production in temperate wetlands

Abstract Wetlands are a major source of methane emissions and contribute to the observed increase in atmospheric methane over the last 20 years. Methane production in wetlands is the final step of carbon decomposition performed by anaerobic archaea. Although hydrogen/carbon dioxide and acetate are the substrates most often attributed to methanogenesis, other substrates—such as methylated compounds—may additionally play important roles in driving methane production in wetland systems. Here we conducted mesocosm experiments combined with genome-resolved metatranscriptomics to investigate the impact of diverse methanogenic substrate amendment on methanogenesis in two high methane-emitting wetlands with distinct geochemistry, termed P7 and P8. Methanol amendment resulted in high methane production at both sites, whereas acetate and formate amendment only stimulated methanogenesis in P7 mesocosms, where aqueous sulfide concentrations were lower. In P7 sediments, formate amendment fueled acetogenic microbes that produced acetate, which was subsequently utilized by acetoclastic methanogens. In contrast to expression profiles in P7 mesocosms, active methylotrophic methanogen genomes from P8 showed increased expression of genes related to membrane remodeling and DNA damage repair, indicative of stress tolerance mechanisms to counter sulfide toxicity. Methylotrophic methanogenesis generates higher free energy yields than acetoclastic methanogenesis, which likely enables allocation of more energy toward stress responses. These findings contribute to the growing body of literature highlighting methylotrophic methanogenesis as an important methane production pathway in wetlands. By using less competitive substrates like methanol that provide greater energy yields, methylotrophic methanogens may invest in physiological strategies that provide competitive advantages across a range of environmental stresses.

Environmental Sciences & Ecology↗

Machine learning-enabled computer vision for plant phenotyping: a primer on AI/ML and a case study on stomatal patterning

Abstract Artificial intelligence and machine learning (AI/ML) can be used to automatically analyze large image datasets. One valuable application of this approach is estimation of plant trait data contained within images. Here we review 39 papers that describe the development and/or application of such models for estimation of stomatal traits from epidermal micrographs. In doing so, we hope to provide plant biologists with a foundational understanding of AI/ML and summarize the current capabilities and limitations of published tools. While most models show human-level performance for stomatal density (SD) quantification at superhuman speed, they are often likely to be limited in how broadly they can be applied across phenotypic diversity associated with genetic, environmental, or developmental variation. Other models can make predictions across greater phenotypic diversity and/or additional stomatal/epidermal traits, but require significantly greater time investment to generate ground-truth data. We discuss the challenges and opportunities presented by AI/ML-enabled computer vision analysis, and make recommendations for future work to advance accelerated stomatal phenotyping.

Plant Sciences↗

Pulse profile modelling of thermonuclear burst oscillations − I. The effect of neglecting variability

ABSTRACT We study the effects of the time-variable properties of thermonuclear X-ray bursts on modelling their millisecond-period burst oscillations. We apply the pulse profile modelling technique that is being used in the analysis of rotation-powered millisecond pulsars by the Neutron Star Interior Composition Explorer to infer masses, radii, and geometric parameters of neutron stars. By simulating and analysing a large set of models, we show that overlooking burst time-scale variability in temperatures and sizes of the hot emitting regions can result in substantial bias in the inferred mass and radius. To adequately infer neutron star properties, it is essential to develop a model for the time-variable properties or invest a substantial amount of computational time in segmenting the data into non-varying pieces. We discuss prospects for constraints from proposed future X-ray telescopes.

79 ASTRONOMY AND ASTROPHYSICS↗

Time for a drought experiment: Do you know your plants’ water status?

Abstract Drought stress is an increasing concern because of climate change and increasing demands on water for agriculture. There are still many unknowns about how plants sense and respond to water limitation, including which genes and cellular mechanisms are impactful for ecology and crop improvement in drought-prone environments. A better understanding of plant drought resistance will require integration of several research disciplines. A common set of parameters to describe plant water status and quantify drought severity can enhance data interpretation and research integration across the research disciplines involved in understanding drought resistance and would be especially useful in integrating the flood of genomic data being generated in drought studies. Water potential (ψw) is a physical measure of the free energy status of water that, along with related physiological measurements, allows unambiguous description of plant water status that can apply across various soil types and environmental conditions. ψw and related physiological parameters can be measured with relatively modest investment in equipment and effort. Thus, we propose that increased use of ψw as a fundamental descriptor of plant water status can enhance the insight gained from many drought-related experiments and facilitate data integration and sharing across laboratories and research disciplines.

Juenger, Thomas E. (ORCID:0000000195509288)↗

Respiratory energy demands and scope for demand expansion and destruction

Photosynthesis is the primary energy input to plants, but most plant metabolic processes are powered much or all of the time by ATP and NAD(P)H that come from respiratory oxidation of photosynthetically produced carbohydrates, that is, “dark respiration” (Amthor, 1994). The processes of growth, nutrient uptake and assimilation, active transport, and maintenance are thus all clients of respiration and compete for their share of a respiratory energy budget that is capped by photosynthate income. The economic principle of opportunity cost applies to these clients’ competing demands: spending respiratory energy on process A means missing the benefit of investing that energy in process B (Mahmoudabadi et al., 2019). This principle is key to assessing prospects for crop improvement by metabolic engineering. As de Lorenzo (2015) put it: “metabolism…frames and ultimately resolves whether a given genetic program (existing…or engineered) can be deployed or not.” Foreign or reconfigured native processes bolted on to a crop-plant’s metabolic chassis must compete for respiratory energy with native ones without crashing the energy economy. A proviso on plant carbon budgets is that photosynthetic carbon fixation (“source activity”) can in certain cases increase to meet increased carbon demand (“sink activity”), that is, budget envelopes are not always fixed (Smith et al., 2018). However, as there is some consensus that productivity is most often limited or co-limited by carbon supply (Ainsworth and Long, 2005; Körner, 2015; Sonnewald and Fernie, 2018), we make this our basal assumption in the analyses below.

59 BASIC BIOLOGICAL SCIENCES↗

Daylength variation affects growth, photosynthesis, leaf metabolism, partitioning, and metabolic fluxes

Abstract Daylength, a seasonal and latitudinal variable, exerts a substantial impact on plant growth. However, the relationship between daylength and growth is nonproportional, suggesting the existence of adaptive mechanisms. Thus, our study aimed to comprehensively investigate the adaptive strategies employed by plants in response to daylength variation. We grew false flax (Camelina sativa) plants, a model oilseed crop, under long-day (LD) and short-day (SD) conditions and used growth measurements, gas exchange measurements, and isotopic labeling techniques, including 13C, 14C, and 2H2O, to determine responses to different daylengths. Our findings revealed that daylength influences various growth parameters, photosynthetic physiology, carbon partitioning, metabolic fluxes, and metabolite levels. SD plants employed diverse mechanisms to compensate for reduced CO2 fixation in the shorter photoperiod. These mechanisms included enhanced photosynthetic rates and reduced respiration in the light (RL), leading to increased shoot investment. Additionally, SD plants exhibited reduced rates of the glucose 6-phosphate (G6P) shunt and greater partitioning of sugars into starch, thereby sustaining carbon availability during the longer night. Isotopic labeling results further demonstrated substantial alterations in the partitioning of amino acids and TCA cycle intermediates between rapidly and slowly turning over pools. Overall, the results point to multiple developmental, physiological, and metabolic ways in which plants adapt to different daylengths to maintain growth.

59 BASIC BIOLOGICAL SCIENCES↗