SEARCH · Engineering Papers
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Join open writing teams to collaborate on commentaries for a special collection describing approaches that embody synthesis, cross-disciplinary integration, and open science across geosciences.
Abstract Vegetation responds dynamically to local microclimates at both short and long time scales via mechanisms ranging from physiological behaviors, such as stomatal closure, to acclimation and adaptation. These responses influence the carbon, water, and energy cycles directly and are therefore crucial to understanding and predicting Earth system responses to a changing climate. Several recent studies have demonstrated that differences in microclimate can induce structural and functional acclimations, and potentially adaptations, within the same ecosystem. Such microclimate divergence can be caused by variability in slopes, disturbance history, or even localized resource availability. Ecosystem stressors such as low soil water availability, limited photoperiod, or high vapor pressure deficit have been shown to reveal the large impact of the subtle differences within these systems such as the number of sun versus shade leaves or differences in whole‐plant water acquisition and use. These findings highlight the linkages between plant canopy structure and ecosystem function, alongside the need for comprehensive analyses of vegetation within the broader context of its environment. This commentary addresses some of the key implications of ecosystem stress responses and accompanying acclimations across three ecosystem types for ecosystem ecology, plant physiology, ecohydrology and trait‐based modeling of vegetation‐climate dynamics.
Hydrologic sciences depend on data monitoring, analyses, and simulations of hydrologic processes to ensure safe, sufficient, and equal water distribution. These hydrologic data come from but are not limited to primary (lab, plot, and field experiments) and secondary sources (remote sensing, UAVs, hydrologic models) that typically follow FAIR Principles (Findable, Accessible, Interoperable, and Reusable: (go-fair.org)). Easy availability of FAIR data has become possible because the hydrology-oriented organizations have pushed the community to increase coordination of the protocols for generating data and sharing model platforms. In addition, networking at all levels has emerged with an invigorated effort to activate community science efforts that complement conventional data collection methods. However, it has become difficult to decipher various complex hydrologic processes with increasing data. Machine learning, a branch of artificial intelligence, provide more accurate and faster alternatives to better understand different hydrological processes. The Integrated, Coordinated, Open, Networked (ICON) framework provides a pathway for water users to include and respect diversity, equity, and inclusivity. In addition, ICONs support the integration of peoples with historically marginalized identities into this professional discipline of water sciences. This article comprises three independent commentaries about the state of ICON principles in hydrology and discusses the opportunities and challenges of adopting them.
Abstract Agrivoltaics (AV), conceived in the early 1980s, promise to ameliorate competition between solar energy generation and crop production for arable land. The premise behind AV is that excess light not used in photosynthesis can be used for energy production. There are opportunities for maximizing photosynthesis by targeting particular wavelengths (e.g., red) to be transmitted through semi‐transparent photovoltaic (PV) cells depending on crop type and environmental conditions. Camporese and Abou Najm (2022, https://doi.org/10.1029/2022EF002900 ) developed a numerical model that accommodates the various wavelengths of the incoming light spectrum to predict photosynthesis, stomatal conductance, and transpiration. This commentary seeks to place those and other recent findings about the modifications to the plant micro‐environment by PV cells in the context of maximum attainable aboveground biomass.
Abstract Climate impacts increasingly unfold in interlinked systems of people, nature, and infrastructure. The cascading consequences are revealing sometimes surprising connections across sectors and regions, and prospects for climate responses also depend on complex, difficult‐to‐understand interactions. In this commentary, we build on the innovations of the United States Fifth National Climate Assessment to suggest a framework for understanding and responding to complex climate challenges. This approach involves: (a) integration of disciplines and expertise to understand how intersectionality shapes complex climate impacts and the wide‐ranging effects of climate responses, (b) collaborations among diverse knowledge holders to improve responses and better encompass intersectionality, and (c) sustained experimentation with and learning about governance approaches capable of handling the complexity of climate change. Together, these three pillars underscore that usability of climate‐relevant knowledge requires transdisciplinary coordination of research and practice. We outline actionable steps for climate research to incorporate intersectionality, integration, and innovative governance, as is increasingly necessary for confronting climate complexity and sustaining equitable, ideally vibrant climate futures.
Characterizing the impact of human actions on terrestrial water fluxes and storages at multi-basin, continental, and global scales has long been on the agenda of scientists engaged in climate science, hydrology, and water resources systems analysis. This need has resulted in a variety of modeling efforts focused on the representation of water infrastructure operations. Yet, the representation of human-water interactions in large-scale hydrological models is still relatively crude, fragmented across models, and often achieved at coarse resolutions (~10–100 km) that cannot capture local water management decisions. In this commentary, we argue that the concomitance of four drivers and innovations is poised to change the status quo: “hyper-resolution” hydrological models (~0.1–1 km), multi-sector modeling, satellite missions able to monitor the outcome of human actions, and machine learning are creating a fertile environment for human-water research to flourish. We then outline four challenges that chart future research in hydrological modeling: (a) creating hyper-resolution global data sets of water management practices, (b) improving the characterization of anthropogenic interventions on water quantity, stream temperature, and sediment transport, (c) improving model calibration and diagnostic evaluation, and (d) reducing the computational requirements associated with the successful exploration of these challenges. Overcoming them will require addressing modeling, computational, and data development needs that cut across the hydrology community, thereby requiring a major communal effort.
Recent trends within computational and data sciences show an increasing recognition and adoption of computational workflows as tools for productivity and reproducibility that also democratize access to platforms and processing know-how. As digital objects to be shared, discovered, and reused, computational workflows benefit from the FAIR principles, which stand for Findable, Accessible, Interoperable, and Reusable. The Workflows Community Initiative’s FAIR Workflows Working Group (WCI-FW), a global and open community of researchers and developers working with computational workflows across disciplines and domains, has systematically addressed the application of both FAIR data and software principles to computational workflows. We present recommendations with commentary that reflects our discussions and justifies our choices and adaptations. These are offered to workflow users and authors, workflow management system developers, and providers of workflow services as guidelines for adoption and fodder for discussion. The FAIR recommendations for workflows that we propose in this paper will maximize their value as research assets and facilitate their adoption by the wider community.
The demand for portable electronic devices has increased rapidly during the past decade, and has driven a concordant growth in battery production. Since their development as a commercial energy storage solution in the 1990s, lithium-ion batteries (LIBs) have attracted significant attention in both science and industry due to their long cycle life, high energy density, low self-discharge rate, and high working voltage. Production of LIBs requires large amounts of a polymeric binder – commonly polyvinylidene difluoride (PVDF) – for processing and performance purposes. However, since this material is petrochemically-derived, it is far from “green” or sustainable. On the other hand, polymers and their building blocks are found widely throughout nature and can be renewably sourced from biomass at low cost; therefore, replacing PVDF with biomass-derived binders is a promising approach to reduce the environmental footprint of LIBs. Additionally, polymer binders play a critical role in next-generation battery performance. For instance, silicon (Si) is a promising high-capacity anode material for LIBs because of its high theoretical capacity (4200 mA h g –1 ), low working potential, and high abundance in Earth's crust. However, its huge volume change during charge/discharge tends to result in a shortened cycle life, since conventional binders interact only weakly with silicon's native surface and cannot maintain long-term integrity of the electrode. Naturally derived polymers have found better success in this role due to their high structural advantages. In this review, we summarize recent developments in silicon anode binders derived from various biomass sources, with a focus on polymer properties and their effect on battery performance. Further, we propose various perspectives based on our own assessment of these works, and provide a brief commentary on the future outlook of the field.
For several decades, heterogeneous catalytic processes have been improved through utilizing supercritical fluids (SCFs) as solvents. While numerous experimental studies have been established across a range of chemistries, such as oxidation, pyrolysis, amination, and Fischer-Tropsch synthesis, still there is little fundamental, molecular-level information regarding the role of the SCF on elementary heterogeneous catalytic steps. In this study, the influence of hexane solvent on the adsorption of carbon monoxide on Co(0001), as the first step in the reaction mechanism of many processes involving syngas conversion, is probed. Simulations are performed at various bulk hexane densities, ranging from ideal gas conditions (no SCF hexane) to various near- and super-critical hexane densities. For this purpose, both density functional theory and molecular dynamics simulations are employed to determine the adsorption energy and free energy change during CO chemisorption. Potential of mean force calculations, utilizing umbrella sampling and the weighted histogram analysis method, provide the first commentary on SCF solvent effects on the energetic aspects of the chemisorption process. Simulation results indicate an enhanced stability of CO adsorption on the catalyst surface in the presence of supercritical hexane within the reduced pressure range of 1.0–1.5 at a constant temperature of 523 K. Furthermore, it is shown that the maximum stability of CO in the adsorbed state as a function of supercritical hexane density at 523 K nearly coincides with the maximum isothermal compressibility of bulk hexane at this temperature.
Murine models have been extensively used in recent decades to identify and test drug candidates for subsequent human trials (1–3). However, few of these human trials have shown success (4–7). The success rate is even worse for those trials in the field of inflammation, a condition present in many human diseases. To date, there have been nearly 150 clinical trials testing candidate agents intended to block the inflammatory response in critically ill patients, and every one of these trials failed (8–11). Despite commentaries that question the merit of an overreliance of animal systems to model human immunology (3, 12, 13), in the absence of systematic evidence, investigators and public regulators assume that results from animal research reflect human disease. To date, there have been no studies to systematically evaluate, on a molecular basis, how well the murine clinical models mimic human inflammatory diseases in patients. The Inflammation and Host Response to Injury, Large Scale Collaborative Research Program has completed multiple studies on the genomic responses to systemic inflammation in patients and human volunteers as well as murine models (14–18). These datasets include genome-wide expression analysis on white blood cells obtained from serial blood draws in 167 patients up to 28 d after severe blunt trauma (15), 244 patients up to 1 y after burn injury, and 4 healthy humans for 24 h after administration of low-dose bacterial endotoxin (14) and expression analysis on analogous samples from well-established mouse models of trauma, burns, and endotoxemia (16 treated and 16 controls per model) (16–18). In humans, severe inflammatory stress produces a genomic storm affecting all major cellular functions and pathways (15) and therefore, provided sufficient perturbations to allow comparisons between the genes in the human conditions and their orthologs in the murine models. In this article, we report on a systematic comparison of the genomic response between human inflammatory diseases andmurine models. First, we compared the correlations of gene expression changes with trauma, burns, and endotoxemia between human subjects and corresponding mouse models. Second, we characterized and compared the temporal gene response patterns seen in these human conditions and models. Third, we also identified the major signaling pathways significantly regulated in the inflammatory response to human injuries and compared them with the human in vivo endotoxemia model and three murine models. Fourth, we sought and evaluated representative patient and murine studies of several additional acute inflammatory diseases. These results show that the genomic responses to different acute inflammatory stresses are highly similar in humans, but these responses are not reproduced in the current mouse models. New approaches need be explored to improve the ways that human diseases are studied.
The International Atomic Energy Agency (IAEA) defines uranium with a 235 U isotope concentration of 20 percent as the threshold between low-enriched uranium (LEU) and highly enriched uranium (HEU), and as a significant waypoint on the path towards weapon-grade uranium (typically above 90 percent 235 U enrich-ment). Furthermore, the distinction between LEU and HEU is widely used in shaping nonproliferation policy, and it has featured prominently in commentary over Iran’s nuclear program and the series of Nuclear Security Summits that since 2010 have sought to minimize civilian stockpiles and use of HEU. Yet the origin of this threshold is obscure, dating back 6 decades. Our research note traces the political origin and the technical basis for this limit.
Despite 30 years of effort, we do not have an effective HIV-1 vaccine. Over the past decade, the HIV-1 vaccine field has shifted emphasis toward antibody-based vaccine strategies, following a lack of efficacy in CD8+ T-cell-based vaccine trials. Several lines of evidence, however, suggest that improved CD8+ T-cell-directed strategies could benefit an HIV-1 vaccine. First, T-cell responses often correlate with good outcomes in non-human primate (NHP) challenge models. Second, subgroup studies of two no-efficacy human clinical vaccine trials found associations between CD8+ T-cell responses and protective effects. Finally, improved strategies can increase the breadth and potency of CD8+ T-cell responses, direct them toward preferred epitopes (that are highly conserved and/or associated with viral control), or both. Optimized CD8+ T-cell vaccine strategies are promising in both prophylactic and therapeutic settings. This commentary briefly outlines some encouraging findings from T-cell vaccine studies, and then directly compares key features of some T-cell vaccine candidates currently in the clinical pipeline.
This Special Issue, edited by Ilya Nemenman, celebrates the Eighth q-bio Conference, which took place in Santa Fe, New Mexico from August 13 to 16, 2014. Here, it consists of a commentary, two reviews, and five primary reports, which represent ideas and work discussed at the meeting.
The energy sector generates over 70% of global greenhouse gas (GHG) emissions, but existing energy-climate policies do little to reduce GHG emissions to prevent climate change. We present a new carbon tax policy concept in which energy users would be taxed an amount equal to the cost of cleaning up the emissions that they create, wherein the tax revenues would be used to operate negative emissions technologies. The policy is based on applying the zero-emissions cost (ZEC) metric to energy prices, which includes the 'regular' cost of an energy source plus the cost of sequestering its emissions. Using the ZEC, (a) the energy sector would be emissions-neutral, (b) biofuels would be cheaper than petroleum fuels, and (c) renewable electricity would be cheaper than fossil-fuel electricity. We calculate the energy spending as a fraction of gross domestic product for 'regular' and ZEC cost scenarios. Implementing the ZEC carbon-tax policy would enable a monumental shift to a net-zero emissions energy sector, but carries a significant risk of causing an economic recession. The summary point of this commentary is to demonstrate a pathway to achieve net-zero GHG emissions from the US energy sector, and to contemplate the associated economic impacts on our society.
Abstract Entropy, once overlooked, is an essential aspect of electrolytes. Recently emerged high-entropy electrolytes with multiple components provide vast compositional space and interfacial chemistry possibilities for electrolyte design. It is noteworthy that high-entropy electrolytes exhibit extraordinarily high ionic conductivity at low temperatures, thereby creating a new direction for batteries to operate at ultra-low temperatures. This commentary discusses the underlying mechanism, challenges encountered, and potential solutions of high-entropy electrolyte design in the hope of sparking future research in this subject.
Wet conditions across the US Midwest have forced farmers to delay planting of corn into June 2019, leading to a four-year low in projected corn yields. This event is part of a broader pattern that extends further back in history and is expected to worsen in future (Naz et al. 2016), raising concerns about the future sustainability of the corn-based economy. In this commentary, we suggest that deep-rooted perennial biomass crops will have considerable advantages for farmers under future climate once markets for cellulosic biofuels mature. Beyond climate-resilient cropping systems, research is suggesting that plants tolerant of wet conditions could benefit wetland conservation efforts while producing sustainable biomass for energy (Avellan et al. 2017, Melts et al. 2019).
This scientific commentary refers to ‘Exacerbation of C1q dysregulation, synaptic loss and memory deficits in tau pathology linked to neuronal adenosine A2A receptors’, by Carvalho et al. (doi:10.1093/brain/awz288).
Abstract Photosynthesis—the conversion of energy from sunlight into chemical energy—is essential for life on Earth. Yet there is much we do not understand about photosynthetic energy conversion on a fundamental level: how it evolved and the extent of its diversity, its dynamics, and all the components and connections involved in its regulation. In this commentary, researchers working on fundamental aspects of photosynthesis including the light-dependent reactions, photorespiration, and C4 photosynthetic metabolism pose and discuss what they view as the most compelling open questions in their areas of research.