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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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At least 127 records · Page 7

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DOE OSTI2023

Implementation of Smart Materials for Actuation of Traditional Valve Technology for Hybrid Energy Systems

The ever-changing nature of the power industry will require the implementation of hybrid energy systems. Integration of tightly coupled components in hybrids often involves the diversion of exhaust gas flow. An innovative smart material actuation technology is proposed to replace traditional electro-mechanical actuated valve mechanisms with lighter and less expensive actuators. A shape memory alloy (SMA) spring-actuated valve was designed for high-temperature service to demonstrate the promise of smart materials in control valve applications. With SMA springs only generating a maximum force of 3.2 N, an innovative valve design was necessary. To demonstrate the concept, a 3-inch Nominal Pipe Size valve was designed, and 3D printed using the stereolithography technique. Increasing the electrical current to actuate the SMA springs reduced actuation time. The maximum current of 10 A produced the lowest actuation time of 2.85 s, with an observed maximum stroke rate of more than 100 stroke completion %/s (considering actuation open/close as 100% stroke) at the midrange. The final assembly of the valve was estimated to provide a cost reduction of more than 30% and a weight reduction of more than 80% compared to the other available automatic valves in the present market.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Rewritable Surface‐Grafted Polymer Brushes with Dynamic Covalent Linkages

Abstract Surface grafting of polymer brushes drastically modifies surface properties, including wettability, compatibility, responsiveness, etc. A broad variety of functionalities can be introduced to the surface via different types of polymers. Bringing together properties of two or more types of polymer brushes to one surface opens up even more possibilities in brush‐modified materials. However, while it is generally feasible to introduce several chemical compositions along the brushes via copolymerization, it is challenging to vary the types of polymer brushes along a surface. Although previous studies have demonstrated binary brushes via orthogonal polymerization techniques or partial deactivation/regrafting, they commonly limit the number of polymer types to two. Here, we propose a strategy to introduce dynamic covalent diketoenamine linkages at the root of polymer brushes. The grafting density could be precisely tuned during surface functionalization. The surface‐anchored polymer brushes were cleaved by the addition of small molecule amines. New polymer brushes can be regrafted from the surface following refunctionalization of exposed sites. The maneuverability allows tuning of the types and densities of the polymer brushes, pointing the way to the preparation of a new generation of well‐defined brush‐modified materials with mixed grafts, with potential applications in the design of smart materials and surfaces.

Cui, Feichen↗

DOE OSTI2024

Defect Properties, Anion Ordering, and Photochromic Mechanism in Yttrium Oxyhydride

Yttrium oxyhydride (YHO) undergoes a reversible photochromic transition when exposed to ultraviolet light. However, the mechanism for this transformation is not fully understood, and the structure and precise chemical composition of YHO remain under debate. Here, we use first-principles density functional theory calculations with a hybrid functional to study the structure, chemical stability, and point defect properties of YHO. As experiments have shown, we find that YHO prefers a cubic structure, with H and O anions present in equal concentrations and located on tetrahedral sites. Stoichiometric and ordered YHO is chemically stable, but it has a wide band gap of 5.01 eV, considerably larger than that measured in experiments (2.4–3.8 eV). On the other hand, Y4H10O has a smaller band gap of 2.97 eV and also has a region of chemical stability; thus, the actual material may include some fraction of this H-rich structure. The defect chemistry of YHO is dominated by anionic antisite species (H O and O H ), with hydrogen interstitials (H i ) and vacancies (V H ) also present in reasonably high concentrations. We show that antisite disorder lowers the band gap relative to the perfectly ordered structure, bringing the magnitude of the gap into closer agreement with experiment. Based on our calculations of defect migration and the positions of defect states relative to the band edges, we link the onset of photochromic behavior to the reaction H O – → V O 0 + H i – , which follows photoexcitation of a H O + defect. H i – can subsequently migrate away and be trapped by additional H O + defects, contributing to the persistence of the reaction, while the resultant oxygen vacancy, V O 0 , introduces an occupied defect state that leads to optical absorption at visible wavelengths. Our results can explain reported discrepancies between experimental and computational results for YHO, and they allow us to propose specific atomic-scale processes that can lead to photochromism. In conclusion, understanding these mechanisms is key for unlocking YHO’s application in devices ranging from smart windows and optoelectronics to electrochemical synapses for neural networks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Backbone-Photodegradable Polymers by Incorporating Acylsilane Monomers via Ring-Opening Metathesis Polymerization

Materials capable of degradation upon exposure to light hold promise in a diverse range of applications including biomedical devices and smart coatings. Despite the rapid access to macromolecules with diverse compositions and architectures enabled by ring-opening metathesis polymerization (ROMP), a general strategy to introduce facile photodegradability into these polymers is lacking. Here, we report copolymers synthesized via ROMP that can be degraded by cleaving the backbone in both solution and solid states under irradiation with a 52 W, 390 nm Kessil LED to generate heterotelechelic low-molecular-weight fragments. To the best of our knowledge, this work represents the first instance of the incorporation of acylsilanes into a polymer backbone. Mechanistic investigation of the degradation process supports the intermediacy of an α-siloxy carbene, formed via a 1,2-photo Brook rearrangement, which undergoes insertion into water followed by cleavage of the resulting hemiacetal.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Leveraging graph clustering techniques for cyber‐physical system analysis to enhance disturbance characterisation

Abstract Cyber‐physical systems have behaviour that crosses domain boundaries during events such as planned operational changes and malicious disturbances. Traditionally, the cyber and physical systems are monitored separately and use very different toolsets and analysis paradigms. The security and privacy of these cyber‐physical systems requires improved understanding of the combined cyber‐physical system behaviour and methods for holistic analysis. Therefore, the authors propose leveraging clustering techniques on cyber‐physical data from smart grid systems to analyse differences and similarities in behaviour during cyber‐, physical‐, and cyber‐physical disturbances. Since clustering methods are commonly used in data science to examine statistical similarities in order to sort large datasets, these algorithms can assist in identifying useful relationships in cyber‐physical systems. Through this analysis, deeper insights can be shared with decision‐makers on what cyber and physical components are strongly or weakly linked, what cyber‐physical pathways are most traversed, and the criticality of certain cyber‐physical nodes or edges. This paper presents several types of clustering methods for cyber‐physical graphs of smart grid systems and their application in assessing different types of disturbances for informing cyber‐physical situational awareness. The collection of these clustering techniques provide a foundational basis for cyber‐physical graph interdependency analysis.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Search for High-Pressure Silicon Phases: Reaching the Extreme Conditions with High-Intensity Laser Irradiation

Controlling electronic and optical properties of semiconducting materials could substantially expand their functionality and enable new pathways for the formation of ‘smart’ materials for emerging innovative applications. An emerging new path for the synthesis of exotic silicon (Si) polymorphs is irradiation of bulk diamond-cubic Si by ultrashort laser pulses at relativistic intensity above 1019 W/cm2. Exotic polymorphs are formed due to interaction with MeV-energy electrons generated in laser-produced high-temperature plasma state. The unusual Si structures are found in the form of 5–10 nm nanoparticles confined deep in the bulk of 500-μm-thick Si samples. Raman spectroscopy, electron microscopy and X-ray diffraction studies provide an unequivocal evidence of exotic Si phase formation. A key advantage of such relativistic irradiation lies thereby in the fact that large quantities of such exotic Si is synthesised embedded within the bulk diamond-cubic Si and that further the formed Si polymorphs are stable at ambient temperature and pressure. They are thus available for further studies for electronic applications in selective band gap engineering.

Rapp, Ludovic↗

DOE OSTI2024

Blockchain-based decentralized computing

An exemplary blockchain-based decentralized computing system and method are disclosed for industrial analytics applications. The exemplary system and method leverage blockchain technology to deliver and execute privacy-preserving decentralized predictive analytics, machine learning, and optimization operations for various industrial applications using a set of self-contained analytics block smart contracts that can be readily utilized and in analytics applications to deploy across multiple sites.

Ramanan, Paritosh P.↗

DOE OSTI2024

Spatial modeling algorithms for reactions and transport in biological cells

Biological cells rely on precise spatiotemporal coordination of biochemical reactions to control their functions. Such cell signaling networks have been a common focus for mathematical models, but they remain challenging to simulate, particularly in realistic cell geometries. Here we present Spatial Modeling Algorithms for Reactions and Transport (SMART), a software package that takes in high-level user specifications about cell signaling networks and then assembles and solves the associated mathematical systems. SMART uses state-of-the-art finite element analysis, via the FEniCS Project software, to efficiently and accurately resolve cell signaling events over discretized cellular and subcellular geometries. We demonstrate its application to several different biological systems, including yes-associated protein (YAP)/PDZ-binding motif (TAZ) mechanotransduction, calcium signaling in neurons and cardiomyocytes, and ATP generation in mitochondria. Throughout, we utilize experimentally derived realistic cellular geometries represented by well-conditioned tetrahedral meshes. These scenarios demonstrate the applicability, flexibility, accuracy and efficiency of SMART across a range of temporal and spatial scales.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Artificial Intelligence Techniques in Smart Grid: A Survey

The smart grid is enabling the collection of massive amounts of high-dimensional and multi-type data about the electric power grid operations, by integrating advanced metering infrastructure, control technologies, and communication technologies. However, the traditional modeling, optimization, and control technologies have many limitations in processing the data; thus, the applications of artificial intelligence (AI) techniques in the smart grid are becoming more apparent. This survey presents a structured review of the existing research into some common AI techniques applied to load forecasting, power grid stability assessment, faults detection, and security problems in the smart grid and power systems. It also provides further research challenges for applying AI technologies to realize truly smart grid systems. Finally, this survey presents opportunities of applying AI to smart grid problems. The paper concludes that the applications of AI techniques can enhance and improve the reliability and resilience of smart grid systems.

energy systems↗

DOE OSTI2026

Development of Wireless Power Technology for Use in Electrochromic Window Retrofit Applications

Electrochromic (EC) windows, often referred to as smart windows, have the ability to adjust their tint in response to electrical signals, thereby controlling the amount of sunlight and heat entering a building. This dynamic modulation can lead to significant energy savings by reducing the reliance on artificial lighting and minimizing the load on heating, ventilation, and air conditioning (HVAC) systems. However, the widespread adoption of electrochromic window technology, especially in existing buildings, faces challenges, particularly concerning the installation cost associated with the need for electrical wiring to power and control the EC glass (tinting). In this project, GuRu Wireless demonstrated that it’s mmWave-based wireless power energy transfer technology can provide the necessary power for operation of electrochromic windows, wirelessly, and address the wiring challenges of electrochromic windows in retrofit applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Roadmap on energy harvesting materials

Ambient energy harvesting has great potential to contribute to sustainable development and address growing environmental challenges. Converting waste energy from energy-intensive processes and systems (e.g. combustion engines and furnaces) is crucial to reducing their environmental impact and achieving net-zero emissions. Compact energy harvesters will also be key to powering the exponentially growing smart devices ecosystem that is part of the Internet of Things, thus enabling futuristic applications that can improve our quality of life (e.g. smart homes, smart cities, smart manufacturing, and smart healthcare). To achieve these goals, innovative materials are needed to efficiently convert ambient energy into electricity through various physical mechanisms, such as the photovoltaic effect, thermoelectricity, piezoelectricity, triboelectricity, and radiofrequency wireless power transfer. By bringing together the perspectives of experts in various types of energy harvesting materials, this Roadmap provides extensive insights into recent advances and present challenges in the field. Additionally, the Roadmap analyses the key performance metrics of these technologies in relation to their ultimate energy conversion limits. Building on these insights, the Roadmap outlines promising directions for future research to fully harness the potential of energy harvesting materials for green energy anytime, anywhere.

14 SOLAR ENERGY↗

DOE OSTI2023

Advanced Machine Learning and Computational Methods: SMART (Science-informed Machine Learning for Accelerating Real-Time Decisions in Subsurface Applications) Phase 2

For presentation at the 2023 FECM/Carbon Management Review Meeting, Pittsburgh, PA, August 28-September 1, 2023.

Schuetter, Jared↗

DOE OSTI2022

Smart sensor for online situational awareness in power grids

Waveforms in power grids typically reveal a certain pattern with specific features and peculiarities driven by the system operating conditions, internal and external uncertainties, etc. This prompts an observation of different types of waveforms at the measurement points (substations). An innovative next-generation smart sensor technology includes a measurement unit embedded with sophisticated analytics for power grid online surveillance and situational awareness. The smart sensor brings additional levels of smartness into the existing phasor measurement units (PMUs) and intelligent electronic devices (IEDs). It unlocks the full potential of advanced signal processing and machine learning for online power grid monitoring in a distributed paradigm. Within the smart sensor are several interconnected units for signal acquisition, feature extraction, machine learning-based event detection, and a suite of multiple measurement algorithms where the best-fit algorithm is selected in real-time based on the detected operating condition. Embedding such analytics within the sensors and closer to where the data is generated, the distributed intelligence mechanism mitigates the potential risks to communication failures and latencies, as well as malicious cyber threats, which would otherwise compromise the trustworthiness of the end-use applications in distant control centers. The smart sensor achieves a promising classification accuracy on multiple classes of prevailing conditions in the power grid and accordingly improves the measurement quality across the power grid.

Dehghanian, Payman↗

DOE OSTI2023

Spatiotemporal Control over Polynucleotide Brush Growth on DNA Origami Nanostructures

Abstract DNA nanotechnology provides an approach to create precise, tunable, and biocompatible nanostructures for biomedical applications. However, the stability of these structures is severely compromised in biological milieu due to their fast degradation by nucleases. Recently, we showed how enzymatic polymerization could be harnessed to grow polynucleotide brushes of tunable length and location on the surface of DNA origami nanostructures, which greatly enhances their nuclease stability. Here, we report on strategies that allow for both spatial and temporal control over polymerization through activatable initiation, cleavage, and regeneration of polynucleotide brushes using restriction enzymes. The ability to site‐specifically decorate DNA origami nanostructures with polynucleotide brushes in a spatiotemporally controlled way provides access to “smart” functionalized DNA architectures with potential applications in drug delivery and supramolecular assembly.

Yang, Yunqi↗

DOE OSTI2023

Spatiotemporal Control over Polynucleotide Brush Growth on DNA Origami Nanostructures

DNA nanotechnology provides an approach to create precise, tunable, and biocompatible nanostructures for biomedical applications. However, the stability of these structures is severely compromised in biological milieu due to their fast degradation by nucleases. Recently, we showed how enzymatic polymerization could be harnessed to grow polynucleotide brushes of tunable length and location on the surface of DNA origami nanostructures, which greatly enhances their nuclease stability. Here, in this study, we report on strategies that allow for both spatial and temporal control over polymerization through activatable initiation, cleavage, and regeneration of polynucleotide brushes using restriction enzymes. The ability to site‐specifically decorate DNA origami nanostructures with polynucleotide brushes in a spatiotemporally controlled way provides access to “smart” functionalized DNA architectures with potential applications in drug delivery and supramolecular assembly.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Semantic Interoperability to Enable Smart, Grid-Interactive Efficient Buildings

Achieving a widespread transition to grid-interactive, efficient buildings (GEBs) depends critically on there being sufficient interoperability among connected building systems. While many critical elements already exist at the technical interoperability level (TCP/IP, BACnet, etc.), a lack of interoperability in the semantic level hinders streamlined integration of interdependent applications. Semantics refers to expressing information about “things” in a way that can be consistently understood by applications. Key components of formalized semantics include identifying what a “thing” is (its “type”), defining general information about that “thing” (its characteristics or properties), and defining the appropriate relationships of that “thing” to other “things” (its function or role in a larger system). Although this might seem initially trivial, the success of smart building applications is highly dependent on maintaining consistent self-descriptive notions of the “things”. Without semantic interoperability, it is technically difficult, labor-intensive, and cost-prohibitive to enable three key objectives of GEBs: optimizing performance, automatically identifying and diagnosing faults, and delivering grid services. Industry, academia, and standards bodies have invested effort in developing information models to facilitate semantic interoperability, however, they have not been widely adopted across the U.S. commercial building portfolio. This paper will present a pathway to drive semantic interoperability through a three-pronged approach to be led by the DOE Building Technologies Office in partnership with NIST and multiple national laboratories comprising: 1) industry engagement and coordination across existing efforts; 2) a semantic interoperability standard that empowers building owners to identify and require interoperable attributes when procuring equipment and applications; 3) tools to assist in implementation and a test framework to verify compliance of products with semantic interoperability specifications. This approach is designed to accelerate the timeline for adoption of semantic interoperability specifications. The intent is to reduce soft costs associated with implementing advanced controls, fault detection and diagnostics, and other smart building technologies and use cases as a necessary step in achieving an energy efficient smart grid future.

Bergmann, Harry↗

DOE OSTI2020

Semantic Interoperability to Enable Smart, Grid-Interactive Efficient Buildings

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2020

Semantic Interoperability to Enable Smart, Grid-Interactive Efficient Buildings

Achieving a widespread transition to grid-interactive, efficient buildings (GEBs) depends critically on there being sufficient interoperability among connected building systems. While many critical elements already exist at the technical interoperability level (TCP/IP, BACnet, etc.), a lack of interoperability in the semantic level hinders streamlined integration of interdependent applications. Semantics refers to expressing information about “things” in a way that can be consistently understood by applications. Key components of formalized semantics include identifying what a “thing” is (its “type”), defining general information about that “thing” (its characteristics or properties), and defining the appropriate relationships of that “thing” to other “things” (its function or role in a larger system). Although this might seem initially trivial, the success of smart building applications is highly dependent on maintaining consistent notions of the “things” being self-descriptive. Without semantic interoperability, it is technically difficult, labor-intensive, and cost-prohibitive to enable three key objectives of GEBs: optimizing performance, identifying faults, and delivering grid services. Industry, academia, and standards bodies have invested effort in developing information models to facilitate semantic interoperability, however, they have not been widely adopted across the U.S. commercial building portfolio. This paper will present a pathway to drive semantic interoperability through a three-pronged approach to be led by the DOE Building Technologies Office in partnership with NIST and multiple national laboratories comprising: 1) industry engagement and coordination across existing efforts; 2) a semantic interoperability standard that empowers building owners to identify and require interoperable attributes when procuring equipment and applications; 3) tools to assist in implementation and a test framework that can verify compliance of products with semantic interoperability specifications. This strategic approach is designed to accelerate the timeline for adoption of semantic interoperability standards. The intent is to reduce soft costs associated with implementing advanced controls, fault detection and diagnostics, and other smart building technologies as a necessary step in achieving an energy efficient smart grid future.

semantic interoperability, Semantic modeling, inte↗