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Results for “roadmap”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Understanding WIMP-baryon interactions with direct detection: a roadmap
We study prospects of dark-matter direct-detection searches for probing non-relativistic effective theory for WIMP-baryon scattering. We simulate a large set of noisy recoil-energy spectra for different scattering scenarios (beyond the standard momentum-independent contact interaction), for Generation 2 and futuristic experiments. We analyze these simulations and quantify the probability of successfully identifying the operator governing the scattering, if a WIMP signal is observed. We find that the success rate depends on a combination of factors: the WIMP mass, the mediator mass, the type of interaction, and the experimental energy window. For example, for a 20 GeV WIMP, Generation 2 is only likely to identify the right operator if the interaction is Coulomb-like, and is unlikely to do so in any other case. For a WIMP with a mass of 200 GeV or higher, success is almost guaranteed. We also find that, regardless of the scattering model and the WIMP parameters, a single Generation 2 experiment is unlikely to successfully discern the momentum dependence of the underlying operator on its own, but prospects improve drastically when experiments with different target materials and energy windows are analyzed jointly. Furthermore, we examine the quality of parameter estimation and degeneracies in the multi-dimensional parameter space of the effective theory. We find in particular that the resulting WIMP mass estimates can be severely biased if data are analyzed assuming the standard (momentum-independent) operator while the actual operator has momentum-dependence. Finally, we evaluate the ultimate reach of direct detection, finding that the prospects for successful operator selection prior to reaching the irreducible backgrounds are excellent, if the signal is just below the current limits, but slim if Generation 2 does not report WIMP detection.
Roadmap on plasmonics
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Roadmap on exsolution for energy applications
Over the last decade, exsolution has emerged as a powerful new method for decorating oxide supports with uniformly dispersed nanoparticles for energy and catalytic applications. Due to their exceptional anchorage, resilience to various degradation mechanisms, as well as numerous ways in which they can be produced, transformed and applied, exsolved nanoparticles have set new standards for nanoparticles in terms of activity, durability and functionality. In conjunction with multifunctional supports such as perovskite oxides, exsolution becomes a powerful platform for the design of advanced energy materials. In the following sections, we review the current status of the exsolution approach, seeking to facilitate transfer of ideas between different fields of application. We also explore future directions of research, particularly noting the multi-scale development required to take the concept forward, from fundamentals through operando studies to pilot scale demonstrations.
A roadmap for the functional annotation of protein families: a community perspective
Over the last 25 years, biology has entered the genomic era and is becoming a science of ‘big data’. Most interpretations of genomic analyses rely on accurate functional annotations of the proteins encoded by more than 500 000 genomes sequenced to date. By different estimates, only half the predicted sequenced proteins carry an accurate functional annotation, and this percentage varies drastically between different organismal lineages. Such a large gap in knowledge hampers all aspects of biological enterprise and, thereby, is standing in the way of genomic biology reaching its full potential. A brainstorming meeting to address this issue funded by the National Science Foundation was held during 3–4 February 2022. Bringing together data scientists, biocurators, computational biologists and experimentalists within the same venue allowed for a comprehensive assessment of the current state of functional annotations of protein families. Further, major issues that were obstructing the field were identified and discussed, which ultimately allowed for the proposal of solutions on how to move forward.
Collider signals of baryogenesis and dark matter from B mesons: A roadmap to discovery
Not Available
Towards a data-centric research and development roadmap for large-scale science user facilities
© 2017 IEEE. The U.S. Department of Energy (DOE) Office of Science (SC) operates approximately four dozen large-scale science user facilities (SUFs), each of which generates a tremendous amount of scientific data from experiments, observations and computations. To better understand the data needs and challenges, DOE has run many workshops in recent years to identify and articulate data-centric challenges and opportunities at varying resolution, from facility to community scale. Building on those workshop reports, as well as others from elsewhere in the community, this article goes beyond the findings-recommendations typical of workshop reports to consider how one might structure a broad, technology- and data-centric, coordinated research effort that would realize progress towards solutions that address the well documented challenges and opportunities. We focus on identifying practical issues of strategic relevance, along with offering a view about the focal points for a coordinated research and development effort that would target meeting data-centric needs of a broad set of science users and SUFs. These focal points would, by their nature, engage a spectrum of researchers from computer science, computational and experimental sciences, and data science in a coordinated fashion.
Roadmapping Minigrid Innovations for Cost Reduction
Electrification of the world's rural regions is a high priority for both the private and public sectors, as it has been linked to economic development, improved education and public health. Minigrid systems, opposed to grid extension, have been identified as the favorable solution for electrification in many cases. However, the life cycle costs of minigrid systems remain too high for widespread implementation. To address this, Colorado State University (CSU) and the National Renewable Energy Laboratory (NREL) hosted a series of 3 workshops to engage a range of minigrid stakeholders to determine common issues underlying the cost of minigrid systems. The series identified numerous areas for further development in technology and business, with equal emphasis on pre-installation, capital/equipment, and operational costs. In addition, the workshop series emphasized the need for better market intelligence and a better understanding of productive use as a means of stimulating energy demand.
Superconductor Electronics and the International Roadmap for Devices and Systems.
Abstract not provided.
A roadmap for research on crassulacean acid metabolism (CAM) to enhance sustainable food and bioenergy production in a hotter, drier world
Crassulacean acid metabolism (CAM) is a specialized mode of photosynthesis that features nocturnal CO₂ uptake, facilitates increased water-use efficiency (WUE), and enables CAM plants to inhabit water-limited environments such as semi-arid deserts or seasonally dry forests. Human population growth and global climate change now present challenges for agricultural production systems to increase food, feed, forage, fiber, and fuel production. One approach to meet these challenges is to increase reliance on CAM crops, such as Agave and Opuntia , for biomass production on semi-arid, abandoned, marginal, or degraded agricultural lands. Major research efforts are now underway to assess the productivity of CAM crop species and to harness the WUE of CAM by engineering this pathway into existing food and bioenergy crops. An improved understanding of CAM gained through intensive and expanded research efforts has potential for high returns on research investment in the foreseeable future. To help realize the potential of sustainable dryland agricultural systems, it is necessary to address scientific questions related to the genomic features, regulatory mechanisms, and evolution of CAM; CAM-into-C3 engineering; and the production of CAM crops. Answering these questions requires collaborative efforts to build infrastructure for CAM model systems, field trials, mutant collections, and data management.
A roadmap for improving the representation of photosynthesis in Earth System Models
Accurate representation of photosynthesis in terrestrial biosphere models (TBMs) is essential for robust projections of global change. However, current representations vary markedly between TBMs, contributing uncertainty projections of global carbon fluxes.
A roadmap to understanding and anticipating microbial gene transfer in soil communities
Engineered microbes are being programmed using synthetic DNA for applications in soil to overcome global challenges related to climate change, energy, food security, and pollution. However, we cannot yet predict gene transfer processes in soil to assess the frequency of unintentional transfer of engineered DNA to environmental microbes when applying synthetic biology technologies at scale. This challenge exists because of the complex and heterogeneous characteristics of soils, which contribute to the fitness and transport of cells and the exchange of genetic material within communities. Here, we describe knowledge gaps about gene transfer across soil microbiomes. Here, we propose strategies to improve our understanding of gene transfer across soil communities, highlight the need to benchmark the performance of biocontainment measures in situ, and discuss responsibly engaging community stakeholders. We highlight opportunities to address knowledge gaps, such as creating a set of soil standards for studying gene transfer across diverse soil types and measuring gene transfer host range across microbiomes using emerging technologies. By comparing gene transfer rates, host range, and persistence of engineered microbes across different soils, we posit that community-scale, environment-specific models can be built that anticipate biotechnology risks. Such studies will enable the design of safer biotechnologies that allow us to realize the benefits of synthetic biology and mitigate risks associated with the release of such technologies.
Semantic Technologies in Practical Demand Response: An Information Requirement-based Roadmap
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STREAM: Strategic Technology Roadmapping and Energy, Environmental, and Economic Analysis Model
This is the implementation of the framework for the planning of the technological makeup of the industrial sector. Motivated by the efforts to achieve carbon neutrality, the model of this framework modifies the portfolio of technologies over time for the sector of interest such that, - Net Present Value (NPV) is minimized - Constraint on Greenhouse Emissions (GHG), e.g. carbon dioxide, is satisfied - Demand of the underlying commodity is satisfied - The current implementation reflects a case study for the electric power sector. The for a given initial set of capacities of different vintages, the space of decisions include, - Retirement of the existing capacities. - Retrofitting the existing capacities to alternative characteristics. - Creation of new capacities from a technology portfolio. All the associated quantities with the deployments, e.g. CO2, heat requirement, etc.
A Roadmap for the Future of Systems Biology in Cancer Research
Cancer systems biology seeks to understand how cancer arises as a system of interconnected molecules, cells, and tissues, with the goal of understanding, predicting, and controlling the disease. In the last decade, the field has rapidly grown as advances in experimental, computational, and analytic technologies have improved our ability to capture and recapitulate the complexities of cancer at multiple scales. However, the field’s promise to understand how specific molecular changes give rise to altered cancer outcomes remains incompletely fulfilled. Fortunately, an opportunity exists to accelerate progress by better coordinating modeling and data-gathering efforts across the cancer systems biology community. This will create the foundation for building accurate, multiscale cancer models that can better predict and identify improved therapeutic interventions. Here, in this study, we outline some of the current challenges in cancer systems biology research, how they can be addressed, and actions that the community can take to accelerate progress in the field.
HUMAN-ARTIFICIAL INTELLIGENCE TEAMING FOR THE U.S. NAVY: DEVELOPING A HOLISTIC RESEARCH ROADMAP
With the ever-increasing deluge of data and demand for warfighters to make decisions upon its analysis, U.S. defense strategy has prioritized the development of artificial intelligence (AI)/machine learning (ML) systems that can analyze multi-source data streams and suggest courses of action. However, there is a history of systems that have failed to be adopted by the warfighter due not only to unsolved technical challenges, but also a lack of usability or contributions to mission effectiveness, perceived or otherwise. To avoid this, research into human-AI teaming shows promise for developing AI systems that work with frontline operators. A recent National Academies of Sciences, Engineering, and Medicine report (NASEM, 2022) presented 57 research objectives in this area; however, the U.S. Navy requires a more-focused set of priorities, as it is impossible to tackle every priority. A workshop involving 23 human factors scientists, computer scientists, and active-duty sailors was organized at the Naval Information Warfare Center Pacific, resulting in a set of five research priorities spanning near-, mid-, and far-term time frames. This panel will summarize the results of this workshop, with a focus on the big questions both going into this workshop and coming out of it. The panel participants come from government, academia, and industry, providing perspective from the different kinds of organizations required to accomplish these research goals.
A metagenomics roadmap to the uncultured genome diversity in hypersaline soda lake sediments
Not Available