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At least 199 records · Page 11

A view of Kanerva's sparse distributed memory

Pentti Kanerva is working on a new class of computers, which are called pattern computers. Pattern computers may close the gap between capabilities of biological organisms to recognize and act on patterns (visual, auditory, tactile, or olfactory) and capabilities of modern computers. Combinations of numeric, symbolic, and pattern computers may one day be capable of sustaining robots. The overview of the requirements for a pattern computer, a summary of Kanerva's Sparse Distributed Memory (SDM), and examples of tasks this computer can be expected to perform well are given.

Denning, P. J.↗

Graduating Sustainable Industrial Decarbonization Solutions from the Laboratory to Real-World Deployments

Accelerating innovation and integration of industrial decarbonization technology solutions is crucial for achieving industry-wide net-zero greenhouse gas emissions targets. This can be accomplished in various ways through increased utilization of low-embodied carbon materials and the adoption of advanced manufacturing techniques in construction practices. At the National Renewable Energy Laboratory (NREL), we facilitate dialogue and action across all sectors to uncover industry needs to inform innovation, and explore ways we can help with implementation of emerging solutions in the real world. As an applied laboratory, NREL sits between academia and industry to fully bridge the gap from foundational science research to examining the feasibility of market applications. Integration of innovative technologies and solutions that are efficient, resilient, and grid-interactive will play a pivotal role in supporting a clean energy future. However, it is imperative that these solutions prioritize equitable outcomes, addressing the challenges faced by all communities. By embracing decarbonization, the construction industry can revolutionize itself, promoting sustainability, reducing carbon emissions, conserving resources, while enhancing performance and durability - all major steps toward a greener and more sustainable future.

cement↗

Uncertainties in estimating global potential yields and their impacts for long-term modeling

Estimating realistic potential yields by crop type and region is challenging; such yields depend on both biophysical characteristics (e.g., soil characteristics, climate, etc.), and the crop management practices available in any site or region (e.g., mechanization, irrigation, crop cultivars). A broad body of literature has assessed potential yields for selected crops and regions, using several strategies. In this study we first analyze future potential yields of major crop types globally by two different estimation methods, one of which is based on historical observed yields (“Empirical”), while the other is based on biophysical conditions (“Simulated”). Potential yields by major crop and region are quite different between the two methods; in particular, Simulated potential yields are typically 200% higher than Empirical potential yields in tropical regions for major crops. Applying both of these potential yields in yield gap closure scenarios in a global agro-economic model, GCAM, the two estimates of future potential yields lead to very different outcomes for the agricultural sector globally. In the Simulated potential yield closure scenario, Africa, Asia, and South America see comparatively favorable outcomes for agricultural sustainability over time: low land use change emissions, low crop prices, and high levels of self-sufficiency. In contrast, the Empirical potential yield scenario is characterized by a heavy reliance on production and exports in temperate regions that currently practice industrial agriculture. At the global level, this scenario has comparatively high crop commodity prices, and more land allocated to crop production (and associated land use change emissions) than either the baseline or Simulated potential yield scenarios. This study highlights the importance of the choice of methods of estimating potential yields for agro-economic modeling.

60 APPLIED LIFE SCIENCES↗

Higher Energy-Content Jet Blending Components Derived from Ethanol (CRADA 467)

This project aims to develop a new sustainable aviation fuel (SAF) that comprises favorable properties, such as high energy density, excellent thermal stability, and favorable cold fold properties. Through catalyst development, this work will provide a route to control the cycloalkane/n-alkane/iso alkane content of a next-generation fuel with minimal or no aromatic content. Combining n-alkane and iso-alkane streams (high specific energy, MJ/kg) with cycloalkanes (higher energy density, MJ/L), is expected to enable at least a 4% net increase in combined (specific (MJ/kg) and volumetric (MJ/L)) energy content without impacting ‘drop-in’ fuel requirements, such as seal swelling. PNNL and LanzaTech have already demonstrated a sustainable, non-petroleum, route to isoalkanes. However, economically attractive cycloalkane production from waste and biomass is challenged by large hydrogen requirements, preferential selectivity to aromatic compounds and low yields to jet fuel range components. Many gaps in understanding cycloalkane properties and performance in complex jet fuel mixtures remain. The close tie and integration of Purdue’s fuel property analysis, with PNNL’s process development, can lead to an economically attractive process. The fuel analysis and testing by Purdue will enable a robust understanding of the properties and behavior of the cycloalkanes produced to inform process development. Additionally, seal-swelling analysis will quantify the ability of fuel blends with zero or minimal aromatics content to satisfy the seal swell requirement of O rings. Lastly, Purdue’s system-level analysis will lead to the development of a roadmap for deployment in key regions that considers system pressures such as hydrogen, water, energy efficiency, and ease of infrastructure access.

10 SYNTHETIC FUELS↗

Multi-Sectoral Urban Interactions: Fundamental Science Needs to Inform Pathways to More Resilient Communities in a Changing Climate Multi-Sectoral Urban Interactions: Fundamental Science Needs to Inform Pathways to More Resilient Communities in a Changing Climate

Urban areas and the supply networks that support their resource use are inherently multisectoral systems composed of infrastructural, environmental, and socio-institutional components. These systems are vulnerable to accelerating and interacting stresses from climate change, population growth, resource scarcity, and land-use pressure at the same time as they have a major influence on regional and global systems. For instance, a majority of the world’s greenhouse gas emissions, food consumption, and economic activity can be attributed to urban areas. Urban areas are highly heterogenous, both across and within cities in terms of their socio-demographic, environmental, and infrastructural characteristics. This heterogeneity shapes how urban systems interact and co-evolve and contributes to different economic, environmental, and health outcomes for communities within urban areas. Urban heterogeneity also generates differential vulnerabilities to stressors and differential capacity for adapting to change. The evolution of urban space is thus critical in shaping how human societies respond to global change as they seek to improve resilience to stressors, support prosperous and equitable communities, and use natural resources in a sustainable manner. Developing fundamental scientific understanding of urban heterogeneity and system interactions across sectors and scales is critical for mapping the resilience, sustainability, and equity implications of alternative future pathways. On July 2021 the MSD Urban Systems Working Group organized this workshop to provide a venue for coordination and identification of shared objectives, research themes, and major knowledge gaps, as well as developing a shared strategy for addressing these gaps. This report summarizes the outcomes of this workshop.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Wide bandgap optical switch circuit breaker

A high-voltage switch is adapted for use as a medium-voltage direct current circuit breaker, which provides a low-cost, small-footprint device to mitigate system faults. In one example, a method for operating a wideband optical device includes illuminating the wide bandgap optical device with a light within a first range of wavelengths and a first average intensity, allowing a current to propagate therethrough without substantial absorption of the current, illuminating the wide bandgap optical device with light within the first range of wavelengths and a second average intensity that is lower than the first average intensity to allow a sustained current flow though the wide bandgap optical device, and illuminating the wide bandgap optical device with light within a second range of wavelengths to stop or substantially restrict propagation of the current through the wide gap material.

Voss, Lars F.↗

Wide bandgap optical switch circuit breaker for controlling propagation of current therethrough a wide bandgap optical device

A high-voltage switch is adapted for use as a medium-voltage direct current circuit breaker, which provides a low-cost, small-footprint device to mitigate system faults. In one example, a method for operating a wideband optical device includes illuminating the wide bandgap optical device with a light within a first range of wavelengths and a first average intensity, allowing a current to propagate therethrough without substantial absorption of the current, illuminating the wide bandgap optical device with light within the first range of wavelengths and a second average intensity that is lower than the first average intensity to allow a sustained current flow though the wide bandgap optical device, and illuminating the wide bandgap optical device with light within a second range of wavelengths to stop or substantially restrict propagation of the current through the wide gap material.

Voss, Lars F.↗

Biofuel Air Emissions Analysis

U.S. has goals to produce 3 billion gallons of sustainable aviation fuel (SAF) annually by 2030, increasing to 35 billion gallons by 2050 to decarbonize the aviation sector. Meeting these production targets will require large number of biorefineries to be set up. However, ability to comply with federal air quality standards is prerequisite to being issued a construction permit. Negotiating the permitting process for a new biorefinery can be quite onerous and cost the investors significant time and money. Although there can be numerous reasons for delayed biorefinery construction, air permitting is fraught with pitfalls because the permitting process relies on precedence, which the future SAF biorefineries lack. NREL's Biofuel Air Emissions Analysis project is unique and innovative in terms of the tools, approaches, and analyses provided. NREL is the only national laboratory that is actively working at the intersection of Federal air quality regulations, emissions and air quality analysis across the supply chain, and process design. This project is focused on providing much needed data and analyses that address biorefinery air permitting. This project develops models and quantitative analyses and measures progress towards meeting air quality regulatory requirements. These models and methods are applied to analyze air permitting related to wastewater sludge to biofuel conversion pathways using hydrothermal liquefaction (HTL), impacts of HTL pathway on local and regional air quality including an assessment of health and equity impacts. In addition to filling research gaps, this project also disseminates the findings to the relevant stakeholders at BETO, other national labs, and regulatory agencies.

air quality↗

Geologic hydrogen: a review of resource potential, subsurface dynamics, exploration, production, transportation, and research opportunities

Hydrogen is a versatile resource with critical roles in decarbonization, industrial manufacturing, and energy integration. However, most hydrogen today is produced from fossil fuels, resulting in high emissions and energy consumption. Although low-carbon hydrogen production methods, such as steam methane reforming with carbon capture and renewable-powered electrolysis, are advancing, their high costs hinder large-scale deployment. Identifying alternative pathways for producing low-cost, low-emission hydrogen is therefore essential. Geologic hydrogen, referring to natural and stimulated hydrogen generated in the Earth's subsurface, has attracted growing attention as a potential source of sustainable, economically viable, and environmentally favorable hydrogen. This paper provides a comprehensive review of geologic hydrogen, covering its resource potential, origins, migration and trapping mechanisms, exploration techniques, production strategies, and pipeline transportation. It also identifies key knowledge gaps and proposes a roadmap for future research. The review indicates that geologic hydrogen has vast resource potential and can leverage existing subsurface technologies and geophysical exploration methods. However, major challenges persist, including uncertain hydrogen generation rates, limited understanding and control of serpentinization processes, costly transportation infrastructure, the lack of validated techno-economic analysis, and potential social and environmental issues. As the field is still in its early stages, progress will require interdisciplinary collaboration spanning geoscience, engineering, economics, environmental science, and policy and regulation.

42 ENGINEERING↗

Topological Gaseous Plasmon Polariton in Realistic Plasma

Nontrivial topology in bulk matter has been linked with the existence of topologically protected interfacial states. In this work, we show that a gaseous plasmon polariton (GPP), an electromagnetic surface wave existing at the boundary of magnetized plasma and vacuum, has a topological origin that arises from the nontrivial topology of magnetized plasma. Because a gaseous plasma cannot sustain a sharp interface with discontinuous density, one must consider a gradual density falloff with scale length comparable to or longer than the wavelength of the wave. We show that the GPP may be found within a gapped spectrum in present-day laboratory devices, suggesting that platforms are currently available for experimental investigation of topological wave physics in plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Three-Dimensional Aerodynamic Instabilities In Multi-Stage Axial Compressors

This thesis presents the conceptualization and development of a computational model for describing three-dimensional non-linear disturbances associated with instability and inlet distortion in multistage compressors. Specifically, the model is aimed at simulating the non-linear aspects of short wavelength stall inception, part span stall cells, and compressor response to three-dimensional inlet distortions. The computed results demonstrated the first-of-a-kind capability for simulating short wavelength stall inception in multistage compressors. The adequacy of the model is demonstrated by its application to reproduce the following phenomena: (1) response of a compressor to a square-wave total pressure inlet distortion; (2) behavior of long wavelength small amplitude disturbances in compressors; (3) short wavelength stall inception in a multistage compressor and the occurrence of rotating stall inception on the negatively sloped portion of the compressor characteristic; (4) progressive stalling behavior in the first stage in a mismatched multistage compressor; (5) change of stall inception type (from modal to spike and vice versa) due to IGV stagger angle variation, and "unique rotor tip incidence" at these points where the compressor stalls through short wavelength disturbances. The model has been applied to determine the parametric dependence of instability inception behavior in terms of amplitude and spatial distribution of initial disturbance, and intra-blade-row gaps. It is found that reducing the inter-blade row gaps suppresses the growth of short wavelength disturbances. It is also concluded from these parametric investigations that each local component group (rotor and its two adjacent stators) has its own instability point (i.e. conditions at which disturbances are sustained) for short wavelength disturbances, with the instability point for the compressor set by the most unstable component group. For completeness, the methodology has been extended to describe finite amplitude disturbances in high-speed compressors. Results are presented for the response of a transonic compressor subjected to inlet distortions.

Tan, Choon S.↗

Architecture and Data Management Challenges in GEOSS and IEOS

The international Group on Earth Observations (GEO) was initiated in 2003 to engage all the nations of the Earth in building a coordinated, comprehensive, and sustained Earth observation capability, known as the Global Earth Observation System (GEOSS). The GEO website describes GEOSS this way: "GEOSS will build on and add value to existing Earth-observation systems by coordinating their efforts, addressing critical gaps, supporting their interoperability, sharing information, reaching a common understanding of user requirements, and improving delivery of information to users." Each member nation has responded to GEO by establishing some sort of coordinating body; within the United States, that is the United States Group on Earth Observations (USGEO). This paper will describe the establishment of GEO and USGEO, will provide an overview of the activities and challenges in the area of architecture and data management, and will highlight some of the major efforts underway within USGEO today.

Fontaine, Kathleen S.↗

Machine learning for modern power distribution systems: Progress and perspectives

The application of machine learning (ML) to power and energy systems (PES) is being researched at an astounding rate, resulting in a significant number of recent additions to the literature. As the infrastructure of electric power systems evolves, so does interest in deploying ML techniques to PES. However, despite growing interest, the limited number of reported real-world applications suggests that the gap between research and practice is yet to be fully bridged. To help highlight areas where this gap could be narrowed, this article discusses the challenges and opportunities in developing and adapting ML techniques for modern electric power systems, with a particular focus on power distribution systems. These systems play a crucial role in transforming the electric power sector and accommodating emerging distributed technologies to mitigate the impacts of climate change and accelerate the transition to a sustainable energy future. The objective of this article is not to provide an exhaustive overview of the state-of-the-art in the literature, but rather to make the topic accessible to readers with an engineering or computer science background and an interest in the field of ML for PES, thereby encouraging cross-disciplinary research in this rapidly developing field. To this end, the article discusses the ways in which ML can contribute to addressing the evolving operational challenges facing power distribution systems and identifies relevant application areas that exemplify the potential for ML to make near-term contributions. At the same time, key considerations for the practical implementation of ML in power distribution systems are discussed, along with suggestions for several potential future directions.

Marković, Marija (ORCID:0000000247839837)↗

Effectiveness of nature-based solutions to reduce flooding in Quad Cities Metro Area (QCMA) using SWMM-HEC based flood model

Nature-based solutions (NbS) have gained significant attention as strategies for addressing urban environmental challenges, particularly since the establishment of the UN Sustainable Development Goals (SDGs) for 2030. However, the current research on NbS for urban flood management lacks comprehensive methodological approaches for identifying suitable areas and evaluating their effectiveness across different urban settings. Here, this study attempts to fill this gap by proposing a methodological framework integrating multi-criteria analysis with a SWMM-HEC-based hydrologic and hydraulic (HH) model to assess the suitability of NbS for the Quad Cities Metro Area (QCMA), consisting of Davenport, Bettendorf, Moline, and Rock Island. Eight NbS options-green roofs, rain gardens, infiltration trenches, permeable pavements, vegetative swales, dry detention basins, retention ponds, and rain barrels/cisterns - were considered based on volumetric efficiency and runoff reduction efficiency. The study reveals that implementing the proposed NbS could have substantially reduced flood depths in key historical flood events by 21% in 1993, 15% in 2008, 16% in 2011, 23% in 2014, 40% in 2019, and 10% in 2023. The findings highlight a critical trade-off between peak runoff and NbS implementation: while NbS effectively reduce flood impacts, they also enhance volumetric efficiency by approximately 43%. In high-density areas of the QCMA, flood depth reductions of around 20% suggest that NbS are a viable solution for dense urban environments with limited space. This shows the potential for integrating NbS into existing infrastructure, offering a promising approach for cities facing increasing flooding risks. The proposed methodology provides a practical framework for incorporating NbS into urban stormwater management, addressing gaps in optimizing NbS performance, and offering a pathway to scale their application in other urban areas with various environmental and social contexts.

CMIP6↗

Roadmap for transforming heterogeneous catalysis with artificial intelligence

Artificial intelligence (AI) is poised to transform heterogeneous catalysis, opening avenues for catalytic materials discovery. By uncovering intricate patterns in high-dimensional data, AI has been reshaping our pursuit of sustainable catalytic processes across the energy, environmental and chemical sectors. This promise, however, hinges on overcoming fundamental barriers, including limitations in data availability and quality, challenges in the generalizability and interpretability of data-augmented decisions, and the persistent gap between in silico predictions and experiments. Furthermore, we outline a forward-looking roadmap for deeply integrating AI into heterogeneous catalysis with an AI-ready data ecosystem, multimodal foundation models, and ultimately autonomous laboratories to accelerate the development of next-generation catalytic technologies via AI-empowered human–machine collaboration.

Computational methods↗

Use of Split‐Intein Proteins to Design a Small Molecule Biosensor in Plants

Understanding how plants perceive their environment is fundamental to advancing agricultural productivity and sustainability. Many biological small molecules, including those involved in microbial recognition, act rapidly at the plant cell surface, but the absence of tools to visualise these dynamics has limited our ability to dissect plant–microbe communication. To address this gap, we sought to create a genetically encoded biosensor that couples ligand-induced protein dimerization with the production of a fluorescent reporter. Inteins are peptide regions that excise themselves from precursor proteins and ligate the flanking chains (exteins). When each half of a split intein is fused to one of two dimerizing proteins, ligand binding brings them into proximity, inducing intein splicing and ligation of flanking extein sequences (Kang et al. 2022). Similar to previous studies, we split the yeast vacuolar ATPase subunit 1 (VMA1) intein, creating a protein biosensor that produces eGFP upon protein dimerization after ligand binding (Figure 1A) (Mootz et al. 2003). Specifically, eGFP halves (i.e., non-functional N- and C-terminal GFP fragments) were fused to the intein halves, resulting in two fusion proteins: N-terminal GFP::N-terminal intein and C-terminal intein::C-terminal GFP (Figure 1A).

Boone, Brandon A. [Oak Ridge National Laboratory (↗

Concepts for a NASA Applied Spaceflight Environments Office

The National Aeronautics and Space Administration (NASA) is launching a bold and ambitious new space initiative. A significant part of this new initiative includes exploration of new worlds, the development of more innovative technologies, and expansion our presence in the solar system. A common theme to this initiative is the exploration of space beyond Low Earth Orbit (LEO). As currently organized, NASA does not have an Agency-level office that provides coordination of space environment research and development. This has contributed to the formation of a gap between spaceflight environments knowledge and the application of this knowledge for multi-program use. This paper outlines a concept to establish a NASA-level Applied Spaceflight Environments (ASE) office that will provide coordination and funding for sustained multi-program support in three technical areas that have demonstrated these needs through customer requests. These technical areas are natural environments characterization and modeling, materials and systems analysis and test, and operational space environments modeling and prediction. This paper will establish the need for the ASE, discuss a concept for organizational structure and outline the scope in the three technical areas

Edwards, David L.↗