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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 1,711 records · Page 95
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Polymers in Deep Eutectic Solvents

The project investigated the behavior of polymers in ionic liquids such as deep eutectic solvents using an array of techniques. These included the development of atomistic force fields, coarse graining these force fields to the united atom level, large scale molecular dynamics (MD) simulations using new thermostat algorithms, and machine learning (ML) methods for the phase behavior. The project demonstrated the feasibility and accuracy of first principles force fields for ionic liquids, deep-eutectic solvents, and urea-water mixtures. A novel hierarchical coarse graining method was then used to develop accurate and efficient united-atom models, using which microsecond simulations were performed for polymers in ionic liquids. These simulations were in quantitative agreement with experiment, thus resolving previous controversies. Methods were also developed to obtain the potential of mean force between complex ions in solution. Finally, supervised ML methods were developed for the phase behavior of polymers in ionic liquids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Can artificial intelligence and data-driven machine learning models match or even replace process-driven hydrologic models for streamflow simulation?: A case study of four watersheds with different hydro-climatic regions across the CONUS

With recent developments in computational techniques, Data-driven Machine Learning Models (DMLs) have shown great potential in simulating streamflow and capturing the rainfall-runoff relationship in given watersheds, which are traditionally fulfilled by Process-based Hydrologic Models (PHMs). There are debates on whether the DMLs can outperform and possibly replace the classical PHMs for streamflow simulation and river forecasting, but no clear conclusions have been made. This study aims to investigate whether the newer DMLs have any potential in further improving the simulation accuracy of classical PHMs, and vice versa. To do this, we compared a few popular PHMs and DMLs over four watersheds across the Continental US (CONUS) that are associated with different input, climate, and regional conditions. A total of five hydrologic models were chosen, including (1) two classical lumped models, i.e., the Sacramento Soil Moisture Accounting (SAC-SMA) and Xinanjiang (XAJ); (2) one modern distributed model, termed Coupled Routing and Excess Storage (CREST); (3) and two DMLs including an Artificial Neural Networks (ANN) and a deep learning model, termed Long Short Term Memory (LSTM). Our results demonstrated that the DMLs still significantly biased when using the baseline input scenario with the PHMs. However, the DMLs fed with delayed input scenarios had great potential and can reach high simulation accuracy. The DMLs, especially the ANN, outperformed other employed models under the rainfall-runoff relationship in which rainfall dominantly drives. Furthermore, the DMLs also showed better performance in the high-flow regime, while the PHMs had a better performance for the low-flow regime, implying both PHMs and DMLs have their own merits and are worthy of joint development. In general, our study indicated a great potential of using DMLs to simulate streamflow, but further studies are still needed to verify the transferability and scalability of DMLs in large-scale experiments, such as the Distributed Model Intercomparison Projects 1&2 conducted by National Weather Services but to compare modern DMLs and PHMs.

58 GEOSCIENCES↗
DOE OSTI2012

The Geomechanics of CO 2 Storage in Deep Sedimentary Formations

This study provides a review of the geomechanics and modeling of geomechanics associated with geologic carbon storage (GCS), focusing on storage in deep sedimentary formations, in particular saline aquifers. The paper first introduces the concept of storage in deep sedimentary formations, the geomechanical processes and issues related with such an operation, and the relevant geomechanical modeling tools. This is followed by a more detailed review of geomechanical aspects, including reservoir stress-strain and microseismicity, well integrity, caprock sealing performance, and the potential for fault reactivation and notable (felt) seismic events. Geomechanical observations at current GCS field deployments, mainly at the In Salah CO 2 storage project in Algeria, are also integrated into the review. The In Salah project, with its injection into a relatively thin, low-permeability sandstone is an excellent analogue to the saline aquifers that might be used for large scale GCS in parts of Northwest Europe, the U.S. Midwest, and China. Some of the lessons learned at In Salah related to geomechanics are discussed, including how monitoring of geomechanical responses is used for detecting subsurface geomechanical changes and tracking fluid movements, and how such monitoring and geomechanical analyses have led to preventative changes in the injection parameters. Recently, the importance of geomechanics has become more widely recognized among GCS stakeholders, especially with respect to the potential for triggering notable (felt) seismic events and how such events could impact the long-term integrity of a CO 2 repository (as well as how it could impact the public perception of GCS). As described in the paper, to date, no notable seismic event has been reported from any of the current CO 2 storage projects, although some unfelt microseismic activities have been detected by geophones. However, potential future commercial GCS operations from large power plants will require injection at a much larger scale. In conclusion, for such large-scale injections, a staged, learn-as-you-go approach is recommended, involving a gradual increase of injection rates combined with continuous monitoring of geomechanical changes, as well as siting beneath a multiple layered overburden for multiple flow barrier protection, should an unexpected deep fault reactivation occur.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Modification of defects and potential fluctuations in slow-cooled and quenched Cu 2 ZnSnSe 4 single crystals

Recent literature reports have shown the ability to manipulate Cu-Zn cation ordering for Cu 2 ZnSnSe 4 (CZTSe) via low temperature treatments. Theoretical arguments suggest that one of the major roadblocks to higher V OC —significant band tailing—could be improved with increased cation order; however, few direct measurements have been reported and significant device improvements have not yet been realized. This paper investigates electrical properties, defects, and devices from quenched and slow-cooled single crystals of CZTSe. The extent of disorder was characterized by Raman spectroscopy as well as x-ray diffraction, where the change in Cu-Zn order can be detected by a changing c/a ratio. Quenched samples show higher acceptor concentrations, lower hole mobilities, and a lower-energy photoluminescence (PL) peak than crystals cooled at slower rates, consistent with a reduction in the bandgap. In addition, samples quenched at the highest temperatures showed lower PL yield consistent with higher quantities of deep defects. Devices fabricated using slow-cooled CZTSe single crystals showed improved efficiencies, most notably with increased V OC ; however, low temperature intensity-dependent photoluminescence measurements continue to indicate the existence of potential fluctuations. We discuss the possibility that potential fluctuations in slow-cooled samples may be related to the inability to achieve a long range order of the Cu-Zn sub-lattice resulting in local regions of high and low levels of cation order, and consequent local variations in the bandgap. Finally, the presence of significant potential fluctuations, even after the slow-cooling step, suggests the difficulty in eliminating band-tailing in this system, and thus, additional approaches may be needed for significant reduction of the V OC deficit.

36 MATERIALS SCIENCE↗
NASA NTRS2016

NASA's Space Launch System: An Evolving Capability for Exploration

A foundational capability for international human deep-space exploration, NASA's Space Launch System (SLS) vehicle represents a new spaceflight infrastructure asset, creating opportunities for mission profiles and space systems that cannot currently be executed. While the primary purpose of SLS, which is making rapid progress towards initial launch readiness in two years, will be to support NASA's Journey to Mars, discussions are already well underway regarding other potential utilization of the vehicle's unique capabilities. In its initial Block 1 configuration, capable of launching 70 metric tons (t) to low Earth orbit (LEO), SLS will propel the Orion crew vehicle to cislunar space, while also delivering small CubeSat-class spacecraft to deep-space destinations. With the addition of a more powerful upper stage, the Block 1B configuration of SLS will be able to deliver 105 t to LEO and enable more ambitious human missions into the proving ground of space. This configuration offers opportunities for launching co-manifested payloads with the Orion crew vehicle, and a class of secondary payloads, larger than today's CubeSats. Further upgrades to the vehicle, including advanced boosters, will evolve its performance to 130 t in its Block 2 configuration. Both Block 1B and Block 2 also offer the capability to carry 8.4- or 10-m payload fairings, larger than any contemporary launch vehicle. With unmatched mass-lift capability, payload volume, and C3, SLS not only enables spacecraft or mission designs currently impossible with contemporary EELVs, it also offers enhancing benefits, such as reduced risk, operational costs and/or complexity, shorter transit time to destination or launching large systems either monolithically or in fewer components. This paper will discuss both the performance and capabilities of Space Launch System as it evolves, and the current state of SLS utilization planning.

Creech, Stephen D.↗
DOE OSTI2020

Optimal carbon storage reservoir management through deep reinforcement learning

Model-based optimization plays a central role in energy system design and management. The complexity and high-dimensionality of many process-level models, especially those used for geosystem energy exploration and utilization, often lead to formidable computational costs when the dimension of decision space is also large. This work adopts elements of recently advanced deep learning techniques to solve a sequential decision-making problem in applied geosystem management. Specifically, a deep reinforcement learning framework was formed for optimal multiperiod planning, in which a deep Q-learning network (DQN) agent was trained to maximize rewards by learning from high-dimensional inputs and from exploitation of its past experiences. To expedite computation, deep multitask learning was used to approximate high-dimensional, multistate transition functions. Both DQN and deep multitask learning are pattern based. As a demonstration, the framework was applied to optimal carbon sequestration reservoir planning using two different types of management strategies: monitoring only and brine extraction. Both strategies are designed to mitigate potential risks due to pressure buildup. Results show that the DQN agent can identify the optimal policies to maximize the reward for given risk and cost constraints. Finally, experiments also show that knowledge the agent gained from interacting with one environment is largely preserved when deploying the same agent in other similar environments.

15 GEOTHERMAL ENERGY↗
NASA NTRS2015

Aram Chaos: a Long Lived Subsurface Aqueous Environment with Strong Water Resources Potential for Human Missions on Mars

Aram Chaos, Mars is a crater 280 kilometers in diameter with elevations circa. minus 2 to minus 3 kilometers below datum that provides a compelling landing site for future human explorers as it features multiple scientific regions of interest (ROI) paired with a rich extensible Resource ROI that features poly-hydrated sulfates [1]. The geologic history of Aram Chaos suggests several past episodes of groundwater recharge and infilling by liquid water, ice, and other materials [1-3]. The creation of the fractured region with no known terrestrial equivalent may have been caused by melting of deep ice reservoirs that triggered the collapse of terrain followed by catastrophic water outflows over the region. Aram Chaos is of particular scientific interest because it is hypothesized that the chaotic terrain may be the source of water that contributed to the creation of nearby valleys such as Ares Vallis flowing toward Chryse Planitia. The liquid water was likely sourced as groundwater and therefore represents water derived from a protected subsurface environment making it a compelling astrobiological site [2]. The past history of water is also represented by high concentrations of hematite, Fe-oxyhydroxides, mono-hydrated and poly-hydrated sulfates [1, 2]. Poly-hydrated sulfates are likely to contain abundant water that evolves at temperatures below 500 degrees Centigrade thus conferring Aram Chaos a potentially high value for early in-situ resource utilization (ISRU) [4]. The geologic history also calls for future prospecting of deep ice deposits and possibly liquid water via deep drilling. The most recent stratigraphic units in the central part of Aram Chaos are not fractured, and are part of a dome-shaped formation that features bright, poorly-consolidated material that contains both hydrated sulfates and ferric oxides according to OMEGA (Observatoire pour la Minéralogie, l'Eau, les Glaces et l'Activité) data [5]. These surface material characteristics are preliminary indications of their potential use in civil engineering activities that involve regolith moving and hauling, while further study is needed to assess traverse-ability challenges. The widespread distribution of sulfates is also of interest as a resource for the use of sulfur as a binding compound in regolith-based concrete for constructions. The terrain depressions caused by the rock fracturing events may challenge surface mobility but also suggest the possibility of using such natural features for additional shielding from space radiation and as emplacement of nuclear surface power reactors for the same reason. The high concentration of hematite (up to 16 percent) in some of the smoother recent terrains of the central part of Aram Chaos [2] is a favorable attribute for metal extraction ISRU to create iron-based feedstock for in-situ fabrication of replacement parts or their repairs. Preliminary data on Aram Chaos indicate that it offers a combination of many critical criteria for human missions to the surface of Mars: equatorial region at low Mars Orbiter Laser Altimeter (MOLA), evidence of hydrated minerals over large areas and at high concentrations tied to historic evidence of liquid water over long periods.

Sibille, L.↗
DOE OSTI2019

An archaeal symbiont-host association from the deep terrestrial subsurface

DPANN archaea have reduced metabolic capacities and are diverse and abundant in deep aquifer ecosystems, but little is known about their interactions with other microorganisms that reside there. In this work, we offer evidence for an archaeal host-symbiont association from a deep aquifer system at the Colorado Plateau (Utah, USA). The symbiont, Candidatus Huberiarchaeum crystalense , and its host, Ca. Altiarchaeum hamiconexum , show a highly significant co-occurrence pattern over 65 metagenome samples collected over six years. The physical association of the two organisms was confirmed with genome-informed fluorescence in situ hybridization depicting small cocci of Ca. H. crystalense attached to Ca. A. hamiconexum cells. Based on genomic information, Ca. H. crystalense potentially scavenges vitamins, sugars, nucleotides, and reduced redox-equivalents from its host and thus has a similar metabolism as Nanoarchaeum equitans . These findings give insight into host-symbiont interactions among members of two uncultivated archaeal phyla that thrive in a deep subsurface aquifer.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2020

The Biological Potential of Present-day Mars

In the mid-1970s the twin Viking Landers conducted three biological experiments in two different locations on the surface of Mars. Results from these experiments did not provide conclusive evidence of biological activity, and instead they were consistent with abiotic chemical reactions in the regolith. The paradigm established by the Viking missions is that the near-surface environment on Mars is too cold, dry, and hostile for life as we know it. Our understanding of the limits of metabolic activity and growth in terrestrial organisms, together with ecological studies in terrestrial analog environments, some of which approximate the temperature and dryness conditions on Mars, seem to support this view. But data gathered by surface and orbital assets in the past two decades suggests that liquid water could still be an important agent of landscape evolution over timescales ranging from seasons to millions of years. In addition, the tantalizing discovery of both liquid water buried deep beneath the southern polar deposits and fluctuating levels of methane in the atmosphere make the existence of a subsurface biosphere both possible and realistic. These discoveries have sparked a renewed interest on the biological potential of present-day Mars, and the possibility of extant life. This chapter reviews the environmental aspects most relevant to the biological potential of present-day Mars, emphasizing the near-surface environment that will be sampled and investigated by future robotic missions.

Life↗
DOE OSTI2011

Electron and hole gas in modulation-doped GaAs/Al{sub 1-x}Ga{sub x}As radial heterojunctions

We perform self-consistent Schroedinger-Poisson calculations with exchange and correlation corrections to determine the electron and hole gas in a radial heterojunction formed in a GaAs/AlGaAs core-multi-shell nanowire, which is either n- or p-doped. We show that the electron and hole gases can be tuned to different localizations and symmetries inside the core as a function of the doping density/gate potential. Contrary to planar heterojunctions, conduction electrons do not form a uniform 2D electron gas (2DEG) localized at the GaAs/AlGaAs interface, but rather show a transition between an isotropic, cylindrical distribution deep in the GaAs core (low doping) and a set of six tunnel-coupled quasi-1D channels at the edges of the interface (high doping). Holes, on the other hand, are much more localized at the GaAs/AlGaAs interface. At low doping, they present an additional localization pattern with six separated 2DEGs strips. The field generated by a back-gate may easily deform the electron or hole gas, breaking the sixfold symmetry. Single 2DEGs at one interface or multiple quasi-1D channels are shown to form as a function of voltage intensity, polarity, and carrier type.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Accurate and rapid acoustic damage characterization in complex structures using sparse sensor networks and deep learning models

Damage diagnosis in critical components is essential for ensuring the safety and reliability of operations across industries, spanning manufacturing, aerospace, and energy. Traditional acoustic nondestructive testing methods primarily focus on detecting defects through the direct scattering of single-mode incident waves from the damage, which limit their applicability to simple structures and small inspection areas. Our earlier research demonstrated that machine learning algorithms combined with sparse sensor networks can identify critical defect signatures even from multiply scattered, multi-mode acoustic signals, indicating the potential for improved defect inspection in complex, real-world structures. In this work, we demonstrate the successful implementation of this approach in a fixed sensor configuration to rapidly and accurately detect simulated defects in a geometrically complex, real-world structure, a brake rotor hub. Three different types of defects were physically simulated on the surface of the hub, and the collected data were used to train an autoencoder-based deep learning model. Two models were tested, one using single measurements and the other using multiple measurements taking advantage of the spatial distribution of the sensor network. After training, the multi-measurement model achieved 100 % accuracy in identifying, classifying, and locating unseen, unique damages. This work illustrates the potential of the proposed method for a wide range of industrial applications.

36 MATERIALS SCIENCE↗
DOE OSTI2011

Anisotropies in the Optical ac and dc Conductivities in Lightly Doped La2−xSrxCuO4: The Role of Deep and Shallow Acceptor States

We investigate the origin of the optical ac and dc conductivity anisotropies observed in the low temperature orthorhombic phase of lightly doped, untwinned La{sub 2-x}Sr{sub x}NiO{sub 4} single crystals. We show that these anisotropies can be naturally ascribed to the emergence of two odd parity, rotational-symmetry-broken, localized impurity acceptor states, one deeper and one shallower, resulting from the trapping of doped holes by the Coulomb potential provided by the Sr ions. These two lowest-energy, p-wave-like states are split by orthorhombicity and are partially filled with holes. This leaves a unique imprint in the optical ac conductivity, which shows two distinct far-infrared continuum absorption energies corresponding to the photoionization of the deep and shallow acceptor states. Furthermore, we argue that the existence of two independent and orthogonal channels for hopping conductivity, directly associated with the two orthorhombic directions, also quantitatively explains the observed low temperature anisotropies in the dc conductivity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2019

Predicted Performance of an X-Ray Navigation System for Future Deep Space and Lunar Missions

In November 2017, the NASA Goddard Space Flight Center (GSFC) Station Explorer for X-ray Timing and Navigation Technology (SEXTANT) experiment successfully demonstrated the feasibility of X-ray Pulsar Navigation (XNAV) as part of the Neutron Star Interior Composition Explorer (NICER) mission, which is an X-ray Astrophysics Mission of Opportunity currently operating onboard the International Space Station (ISS). XNAV provides a GPS-like absolute autonomous navigation and timing capability available anywhere in the Solar System and beyond. While the most significant benefits of XNAV are expected to come in support of very deep-space missions, the absolute autonomous navigation and timing capability also has utility for inner Solar System missions where increased autonomy or backup navigation and timing services are required, e.g., address loss of communication scenarios.The NASA commitment to develop a Gateway to support exploration of the Moon and eventually Mars, as well as current and future robotic missions such as James Webb Space Telescope (JWST), New Horizons, and much more, certainly will tax the existing ground based infrastructure in terms of availability. There- fore, an extended look at the feasibility and potential performance of XNAV for comparable missions is warranted. In this paper, we briefly review the XNAV concept and present case studies of its utility and performance for a Gateway orbit, Sun-Earth libration orbit, and a deep space transit trajectory.

Getchius, Joel↗
DOE OSTI2011

Comparing large scale CCS deployment potential in the USA and China: a detailed analysis based on country-specific CO2 transport & storage cost curves

The United States and China are the two largest emitters of greenhouse gases in the world and their projected continued growth and reliance on fossil fuels, especially coal, make them strong candidates for CCS. Previous work has revealed that both nations have over 1600 large electric utility and other industrial point CO2 sources as well as very large CO2 storage resources on the order of 2,000 billion metric tons (Gt) of onshore storage capacity. In each case, the vast majority of this capacity is found in deep saline formations. In both the USA and China, candidate storage reservoirs are likely to be accessible by most sources with over 80% of these large industrial CO2 sources having a CO2 storage option within just 80 km. This suggests a strong potential for CCS deployment as a meaningful option to efforts to reduce CO2 emissions from these large, vibrant economies. However, while the USA and China possess many similarities with regards to the potential value that CCS might provide, including the range of costs at which CCS may be available to most large CO2 sources in each nation, there are a number of more subtle differences that may help us to understand the ways in which CCS deployment may differ between these two countries in order for the USA and China to work together - and in step with the rest of the world - to most efficiently reduce greenhouse gas emissions. This paper details the first ever analysis of CCS deployment costs in these two countries based on methodologically comparable CO2 source and sink inventories, economic analysis, geospatial source-sink matching and cost curve modeling. This type of analysis provides a valuable insight into the degree to which early and sustained opportunities for climate change mitigation via commercial-scale CCS are available to the two countries, and could facilitate greater collaboration in areas where those opportunities overlap.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

Announcing the Biomedical Data Translator: Initial Public Release

ABSTRACT The growing availability of biomedical data offers vast potential to improve human health, but the complexity and lack of integration of these datasets often limit their utility. To address this, the Biomedical Data Translator Consortium has developed an open‐source knowledge graph–based system—Translator—designed to integrate, harmonize, and make inferences over diverse biomedical data sources. We announce here Translator's initial public release and provide an overview of its architecture, standards, user interface, and core features. Translator employs a scalable, federated, knowledge graph framework for the integration of clinical, genomic, pharmacological, and other biomedical knowledge sources, enabling query retrieval, inference, and hypothesis generation. Translator's user interface is designed to support the exploration of knowledge relationships and the generation of insights, without requiring deep technical expertise and gradually revealing more detailed evidence, provenance, and confidence information, as needed by a given user. To demonstrate Translator's application and impact, we highlight features of the user interface in the context of three real‐world use cases: suggesting potential therapeutics for patients with rare disease; explaining the mechanism of action of a pipeline drug; and screening and validating drug candidates in a model organism. We discuss strengths and limitations of reasoning within a largely federated system and the need for rich concept modeling and deep provenance tracking. Finally, we outline future directions for enhancing Translator's functionality and expanding its data sources. Translator represents a significant step forward in making complex biomedical knowledge more accessible and actionable, aiming to accelerate translational research and improve patient care.

Research & Experimental Medicine↗
DOE OSTI2019

Self-organized Higgs criticality

The critical point for a Higgs sector can be a point of interest in the potential for a modulus field such as the radion of an extra dimensional construction, or the dilaton of spontaneously broken approximate conformal invariance. In part motivated by conjectures about the self-organized critical state in statistical physics, we construct a 5D model in which there is an infrared emergent Higgs instability due to violation of the Breitenlohner-Freedman bound deep in the interior of a near AdS geometry. This is holographically dual to a “running” scaling dimension transitioning from real to complex with decreasing scale. The complex scaling indicates an instability to be resolved by condensates which modify the interior geometry and backreact on the 5D radion potential. Studying the model at small gravitational backreaction, we find a rich possible vacuum structure and uncover evidence that resolution of the instability requires a non-trivial cosmology.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

High Performance Pd/4H-SiC Epitaxial Schottky Barrier Radiation Detectors for Harsh Environment Applications

Although many refractory metals have been investigated as the choice of contact metal in 4H-SiC devices, palladium (Pd) as a Schottky barrier contact for 4H-SiC radiation detectors for harsh environment applications has not been investigated adequately. Pd is a refractory metal with high material weight-to-thickness ratio and a work function as high as nickel, one of the conventional metal contacts for high performing 4H-SiC Schottky barrier detectors (SBDs). In this article, Pd/4H-SiC epitaxial SBDs have been demonstrated for the first time as a superior self-biased (0 V applied bias) radiation detector when compared to benchmark Ni/4H-SiC SBDs. The Pd/4H-SiC SBD radiation detectors showed a very high energy resolution of 1.9% and 0.49% under self- and optimized bias, respectively, for 5486 keV alpha particles. The SBDs demonstrated a built-in voltage (V bi ) of 2.03 V and a hole diffusion length (L d ) of 30.8 µm. Such high V bi and L d led to an excellent charge collection efficiency of 76% in the self-biased mode. Capacitance mode deep level transient spectroscopy (DLTS) results revealed that the “lifetime-killer” Z 1/2 trap centers were present in the 4H-SiC epilayer. Another deep level trap was located at 1.09 eV below the conduction band minimum and resembles the EH5 trap with a concentration of 1.98 × 10 11 cm –3 and capture cross-section 1.7 × 10 –17 cm –2 ; however, the detector performance was found to be limited by charge trapping in the Z 1/2 center. The results presented in this article revealed the unexplored potential of a wide bandgap semiconductor, SiC, as high-efficiency self-biased radiation detectors. Such high performance self-biased radiation detectors are poised to address the longstanding problem of designing self-powered sensor devices for harsh environment applications e.g., advanced nuclear reactors and deep space missions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗