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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Flicker: A review of temporal light modulation stimulus, responses, and measures

Flicker has been an important lighting system consideration for over a century. More precise terms are temporal light modulation (TLM) as the stimulus, and responses to TLM as the unwanted visual, cognitive, or physiological consequences. As lighting technology evolved, different forms of TLM emerged, and so did responses to them. Today, some LED systems – encompassing the LED, driver, and control – can result in TLM causing severe unwanted effects, while other LED systems produce no unwanted effects at all. LED systems can deliver a much wider range of luminous waveforms than conventional lighting systems, some exhibiting very high modulation depths. More than any light source before, they can elicit perceptions of the phantom array. Direct flicker effects at modulation frequencies less than about 80 Hz and the stroboscopic effect at frequencies greater than 80 Hz are fairly well understood, but the phantom array effect needs more exploration and characterisation. This review focuses on the technology and research history that led to current metrics for quantifying TLM and human responses to TLM. Notably, visually impaired individuals may exhibit alterations in their response to TLM, but such a discussion is beyond the intent of this review. Thus, the focus is on individuals with normal visual function.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Agile Research and Technology Transitions (ARTT)

The Energy and Environment Directorate (EED) supports an extensive portfolio of strategic Laboratory Directed Research and Development (LDRD) research through its SEED, strategic, Agile and Initiative programs. Of paramount importance is the relevance of these investments to the long-term objectives of our various Department of Energy (DOE) programmatic sponsors. This LDRD project seeks to maximize impact to our sponsors by providing an agile funding approach to develop/enhance DOE relevant technologies in an accelerated and responsive manner to emerging and adjacent technical challenges. Staff will propose small development activities to be carried out under the overall Agile Research and Technology Transitions project.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Micro-fabricated mirrors with finesse exceeding one million

The Fabry–Perot resonator is one of the most widely used optical devices, enabling scientific and technological breakthroughs in diverse fields including cavity quantum electrodynamics, optical clocks, precision length metrology, and spectroscopy. Though resonator designs vary widely, all high-end applications benefit from mirrors with the lowest loss and highest finesse possible. Fabrication of the highest-finesse mirrors relies on centuries-old mechanical polishing techniques, which offer losses at the parts-per-million (ppm) level. However, no existing fabrication techniques are able to produce high-finesse resonators with the large range of mirror geometries needed for scalable quantum devices and next-generation compact atomic clocks. In this paper, we introduce a scalable approach to fabricate mirrors with ultrahigh finesse ( ≥ <#comment/> 10 6 ) and user-defined radius of curvature spanning of four orders of magnitude ( 10 − <#comment/> 4 − <#comment/> 10 0 m ). We employ photoresist reflow and reactive ion etching to shape and transfer mirror templates onto a substrate while maintaining sub-Angstrom roughness. This substrate is coated with a dielectric stack and used to create arrays of compact Fabry–Perot resonators with finesse values as high as 1.3 million and measured excess loss < <#comment/> 1 p p m . Optical ringdown measurements of 43 devices across five substrates reveal that the fabricated cavity mirrors—with both small and large radii of curvature—produce an average coating-limited finesse of 1.05 million. This versatile approach opens the door to scalable fabrication of high-finesse miniaturized Fabry–Perot cavities needed for emerging quantum optics and frequency metrology technologies.

42 ENGINEERING↗
DOE OSTI2020

Visualizing Energy Transfer at Buried Interfaces in Layered Materials Using Picosecond X-Rays

Understanding the fundamentals of nanoscale heat propagation is crucial for next-generation electronics. For instance, weak van der Waals bonds of layered materials are known to limit their thermal boundary conductance (TBC), presenting a heat dissipation bottleneck. In this paper we present a new non-destructive method to probe heat transport in nanoscale crystalline materials using time-resolved x-ray measurements of photo-induced thermal strain. This technique directly monitors time-dependent temperature changes in the crystal and the subsequent relaxation across buried interfaces by measuring changes in the c-axis lattice spacing after optical excitation. We investigate films of five different layered transition metal dichalcogenides MoX 2 [X= S, Se, Te] and WX 2 [X= S, Se] as well as graphite and a W-doped alloy of MoTe 2 , on c-plane sapphire substrates, finding TBC values in the range 10-30 MWm -2 K -1 at room temperature. In conjunction with molecular dynamics simulations, we show that the high thermal resistances are a consequence of weak interfacial van der Waals bonding and low phonon irradiance. This work paves the way for an improved understanding of thermal bottlenecks in emerging three-dimensional heterogeneously integrated technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Decreasing the Overpotential of Aprotic Li-CO 2 Batteries with the In-Plane Alloy Structure in Ultrathin 2D Ru-Based Nanosheets

We report the aprotic Li-CO 2 battery is emerging as a promising energy storage technology with the capability of CO 2 fixation and conversion. However, its practical applications are still impeded by the large overpotential. Herein, the general synthesis of a series of ultrathin 2D Ru-M (M = Co, Ni, and Cu) nanosheets by a facile one-pot solvothermal method is reported. As a proof-of-concept application, the representative RuCo nanosheets are used as the cathode catalysts for Li-CO 2 batteries, which demonstrate a low charge voltage of 3.74 V, a small overpotential of 0.94 V, and hence a high energy efficiency of 75%. Ex/in situ studies and density functional theory calculations reveal that the excellent catalytic performance of RuCo nanosheets originates from the enhanced adsorption toward Li and CO 2 during discharge as well as the elevated electron interaction with Li 2 CO 3 during charge by the in-plane RuCo alloy structure. This work indicates the feasibility of boosting the electrochemical performance of Li-CO 2 batteries by in-plane metal alloy sites of ultrathin 2D alloy nanomaterials.

25 ENERGY STORAGE↗
DOE OSTI2023

A Superconducting Micro-Magnetometer for Quantum Vortex in Superconducting Nanoflakes

Superconducting quantum interferometer device (SQUID) plays a key role in understanding electromagnetic properties and emergent phenomena in quantum materials. The technological appeal of SQUID is that its detection accuracy for the electromagnetic signal can precisely reach the quantum level of a single magnetic flux. However, conventional SQUID techniques normally can only be applied to a bulky sample and do not have the capability to probe the magnetic properties of micro-scale samples with small magnetic signals. Here, in this paper, it is demonstrated that, based on a specially designed superconducting nano-hole array, the contactless detection of magnetic properties and quantized vortices in micro-sized superconducting nanoflakes is realized. An anomalous hysteresis loop and a suppression of Little–Parks oscillation are observed in the detected magnetoresistance signal, which originates from the disordered distribution of the pinned vortices in Bi 2 Sr 2 CaCu 2 O 8+δ . Therefore, the density of pinning centers of the quantized vortices on such micro-sized superconducting samples can be quantitatively evaluated, which is technically inaccessible for conventional SQUID detection. The superconducting micro-magnetometer provides a new approach to exploring mesoscopic electromagnetic phenomena of quantum materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Recent Advances in 3D Printed Sensors: Materials, Design, and Manufacturing

Sensors are of great importance in different aspects of research and industry. Future sensors will require high-efficient and low-cost manufacturing, as well as high-performance functionality in areas, such as mechanical sensing, biomedical, and optical applications. Recent advances in 3D printing open a new paradigm for sensors fabrication as a precision, customizable, and seamless process. Here, in this article, the state-of-the-art 3D printing methods in sensors manufacturing is reviewed and the performance of the 3D printed sensing materials and devices is summarized. Special attention is paid to emerging multimaterial printing and 4D printing technologies, which will benefit the fabrication of a new generation of structures with multifunctionalities. The content on 3D printed sensors covers piezoelectric sensors, medical, and optical sensing devices. The performance of 3D printed sensors in comparison with the sensors made by traditional manufacturing is also covered. Finally, section 4 provides the viewpoints on the future development of 3D printed sensors.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Direct Insertion Polymerization of Ionic Monomers: Rapid Production of Anion Exchange Membranes

Abstract The limited number of methods to directly polymerize ionic monomers currently hinders rapid diversification and production of ionic polymeric materials, namely anion exchange membranes (AEMs) which are essential components in emerging alkaline fuel cell and electrolyzer technologies. Herein, we report a direct coordination‐insertion polymerization of cationic monomers, providing the first direct synthesis of aliphatic polymers with high ion incorporations and allowing facile access to a broad range of materials. We demonstrate the utility of this method by rapidly generating a library of solution processable ionic polymers for use as AEMs. We investigate these materials to study the influence of cation identity on hydroxide conductivity and stability. We found that AEMs with piperidinium cations exhibited the highest performance, with high alkaline stability, hydroxide conductivity of 87 mS cm −1 at 80 °C, and a peak power density of 730 mW cm −2 when integrated into a fuel cell device.

Hsu, Jesse H.↗
DOE OSTI2023

Direct Insertion Polymerization of Ionic Monomers: Rapid Production of Anion Exchange Membranes

The limited number of methods to directly polymerize ionic monomers currently hinders rapid diversification and production of ionic polymeric materials, namely anion exchange membranes (AEMs) which are essential components in emerging alkaline fuel cell and electrolyzer technologies. Herein, we report a direct coordination-insertion polymerization of cationic monomers, providing the first direct synthesis of aliphatic polymers with high ion incorporations and allowing facile access to a broad range of materials. We demonstrate the utility of this method by rapidly generating a library of solution processable ionic polymers for use as AEMs. We investigate these materials to study the influence of cation identity on hydroxide conductivity and stability. Furthermore, we found that AEMs with piperidinium cations exhibited the highest performance, with high alkaline stability, hydroxide conductivity of 87 mS cm –1 at 80 °C, and a peak power density of 730 mW cm –2 when integrated into a fuel cell device.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Multilayered Network Models for Security: Enhancing System Security Engineering with Orchestration

Security engineering approaches can often focus on a particular domain—physical security, cyber security, or personnel security, for example. Yet, security systems engineering consistently faces challenges requiring socio-technical solutions to address evolving and dynamic complexity. While some drivers of this complexity stem from complex risk environments, innovative adversaries, and disruptive technologies, other drivers are endogenous and emerge from the interactions across security engineering approaches. In response, INCOSE's Systems Security Working Group identified the need to better coordinate “disparate security solutions [that] operate independently” as one of eleven key concepts in their IS21 FuSE Security Roadmap. From this perspective, this need for “security orchestration” aligns with the perspective that security is a property that emerges from interactions within complex systems. Current efforts at Sandia National Laboratories are developing a systems security engineering approach that describes high consequence facility (HCF) security as a multidomain set of interacting layers. The result is a multilayered network (MLN)-based approach that captures the interactions between infrastructure, physical components, digital components, and humans in nuclear security systems. This article will summarize the MLN-based approach to HCF security and describe two preliminary results demonstrating potential benefits from incorporating interactions across disparate security solutions. Here, leveraging the logical structure of networks, this MLN model-based approach provides an example of how security orchestration provides enhanced systems security engineering solutions.

42 ENGINEERING↗
DOE OSTI2022

Chapter 1.18 - The Promise of Perovskite Solar Cells

Perovskite solar cells (PSCs) based on a new class of semiconductors - organic and inorganic hybrid halide perovskites - have emerged as a disruptive photovoltaic (PV) technology that is potentially cost-effective, scalable, and highly efficient, with an expectation for future deployment at terawatt scale. This new PV technology has drawn significant R&D attention from academics and industries as an alternate to compete with traditional PV technologies to help mitigate challenges associated with global energy demand. The synthesis of the hybrid halide perovskites was reported in the 1970s. The structural knowledge, solution processing and optoelectronic characteristics of this hybrid material family were further studied in the 1990s. It is until 2009-2012 when the use of methylammonium lead triiodide (MAPbI3) was first demonstrated in PV cells worldwide researchers have started to show a general interest in using hybrid halide perovskites for PV and other optoelectronic applications.

perovskite↗
DOE OSTI2022

Ni/SiO 2 catalysts for polyolefin deconstruction via the divergent hydrogenolysis mechanism

Noble metal-based hydrogenolysis is emerging as a key chemical deconstruction technology of polyolefins into valuable products. Still, the catalyst cost and availability are significant barriers to handling the large volume of plastics. Cheap earth-abundant metals have been deemed inactive for polyolefin hydrogenolysis. Herein, we report that Ni/SiO 2 is active in deconstructing low-density polyethylene to n-alkanes (C 6 -C 35 ) at mild conditions (300 °C, 30barH 2 ) with maximum liquid yields of 65 wt%. In this study, we expose a new mechanism of long-alkane hydrogenolysis that encompasses chain location-dependent single and multiple C-C bond cracking events and rationalizes product selectivity and molecular weight dependence. Ni/SiO 2 catalysts are reusable and can handle multiple plastics producing feedstock-dependent products (i.e., n-alkanes, iso-alkanes, cyclics, aromatics, etc.). The findings broaden the scope of viable catalysts polyolefin hydrogenolysis and unleash the potential to manage the volume of plastic waste.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Impact of system parameters and geospatial variables on the reliability of residential systems with PV and energy storage

A reliable power supply is the foundation of modern society, enabling technologies used to function within a society. Residential systems are places where the end users directly consume power, enabling technologies to sustain life. With the emergence of behind-the-meter resources, the end-users have some control over power supply reliability. The intermittency and variability of these resources impact residential system reliability. In this work, we study the reliability performance of a grid-supplemented residential system with behind-the-meter Distributed Energy Resources(DER) subject to various system parameters and geospatial variables. We propose a multistate reliability model for the behind-the-meter microinverter-based Photo Voltaic (PV) system and integrated inverter-based energy storage (ES) system. A sequential Monte Carlo method is then presented to evaluate the reliability indices for the residential system with behind-the-meter DERs as the main supply and the grid as the backup. The sequential Monte Carlo method is used to analyze the reliability performance of the residential model at the top 100 populous counties of the United States, where actual load and solar irradiance data at the counties is used. In the analysis, the sensitivity of indices to system parameters such as DER size and the sensitivity of the indices to climate zone and gross horizontal irradiation (GHI), which affects the load conditions and the PV output of the residential system, is performed. The analysis results show that the system parameters and the geospatial variables significantly impact the residential system’s reliability. The insights from this analysis will be of immense value to the distribution system planners to provide zone-specific guidelines for DER system sizing and toward the evolution of utility business models. Finally, the methodology developed can be used to extend the analysis to other locations.

14 SOLAR ENERGY↗
DOE OSTI2026

Cobalt Dissolution from Metal Oxides and Battery Cathode Materials with Acetic Acid-Based Deep Eutectic Solvents

Recovery of critical metals with alternative solvents beyond those in traditional pyrometallurgy and hydrometallurgy is needed in consideration of environmental challenges and the growing demand for metals in energy technologies. Deep eutectic solvents (DESs) have emerged as sustainable alternatives for solvometallurgy in metal separation and recovery. In this study, DESs based on hydrogen bond acceptors (HBAs) including choline chloride (ChCl), acetylcholine chloride (AChCl), and betaine (Bet) were investigated for their effectiveness when paired with acetic acid (AA) as the hydrogen bond donor (HBD) for the dissolution of cobalt from cobalt oxide (CoO), lithium cobalt oxide (LiCoO 2 ), and lithium nickel manganese cobalt oxide (LNMC). Based on the spectroscopic analysis of the metal dissolution and coordination, Bet:AA was found to provide the highest solubility for CoO (0.33 M) in the form of an octahedral complex. On the other hand, ChCl:AA solvent was more effective at dissolving LiCoO 2 with 0.04 M Co 2+ corresponding to 17% dissolution efficiency and LNMC with 0.06 M Co 2+ corresponding to 72% dissolution efficiency at 50 °C, compared to Bet:AA (9% for LiCoO 2 and 31% for LNMC). Although the solubilities of LiCoO 2 and LNMC have not significantly improved in ChCl:AA, this difference in effectiveness between the solvents clearly reveals the role of the HBA in solubilization. The coordination synergy between the chloride and the –OH moiety facilitates the breakdown of the LiCoO 2 driven by the alteration of the solvent polarity. Cobalt in these solutions was found dominantly as a tetrahedral [CoCl 4 ] 2– complex. A chemical separation of cobalt oxalate from a mixed-metal oxide system based on Co, Fe, and Ni was also demonstrated, confirming the potential of these solvents for practical metal recovery.

Cobalt separation↗
DOE OSTI2025

First-Principles Simulations Correlating X-ray Absorption Spectroscopy Features to Point Defects in h -BN

Hexagonal boron nitride (h-BN) is a promising material for a range of emerging applications in electronics, quantum information technology, and energy storage. Soft X-ray absorption spectroscopy (XAS) is powerful to reveal atomic details of BN, especially in the presence of defects. However, correlating XAS spectral features with specific defect types remains elusive. In this Letter, we report B K-edge XAS measurements of sputter-deposited turbostratic h-BN films and use a combination of first-principles spectroscopic simulations and analysis of detailed electronic structure and local charge transfer characteristics to elucidate their unique spectroscopic features. Our results show that the two main defect-related peaks, between the main π* resonances of h-BN and B2O3, as typically observed in BN films deposited by energetic condensation or bombarded with energetic ions, are associated with electronic states of H-passivated B atoms bonded to one and two oxygen impurity atoms, respectively. These conclusions hold significant implications for applications relying on defect-mediated properties of h-BN.

chemical structure↗
DOE OSTI2023

Contrasting Capability of Single Atom Palladium for Thermocatalytic versus Electrocatalytic Nitrate Reduction Reaction

The occurrence of high concentrations of nitrate in various water resources is a significant environmental and human health threat, demanding effective removal technologies. Single atom alloys (SAAs) have emerged as a promising bimetallic material architecture in various thermocatalytic and electrocatalytic schemes including nitrate reduction reaction (NRR). This study suggests that there exists a stark contrast between thermocatalytic (T-NRR) and electrocatalytic (E-NRR) pathways that resulted in dramatic differences in SAA performances. Among Pd/Cu nanoalloys with varying Pd–Cu ratios from 1:100 to 100:1, Pd/Cu (1:100) SAA exhibited the greatest activity (TOF Pd = 2 min –1 ) and highest N 2 selectivity (94%) for E-NRR, while the same SAA performed poorly for T-NRR as compared to other nanoalloy counterparts. DFT calculations demonstrate that the improved performance and N 2 selectivity of Pd/Cu (1:100) in E-NRR compared to T-NRR originate from the higher stability of NO 3 * in electrocatalysis and a lower N 2 formation barrier than NH due to localized pH effects and the ability to extract protons from water. Here, this study establishes the performance and mechanistic differences of SAA and nanoalloys for T-NRR versus E-NRR.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Machine Learning-Guided Identification of PET Hydrolases from Natural Diversity

The enzymatic depolymerization of poly(ethylene terephthalate) (PET) is emerging as a leading chemical recycling technology for waste polyester. As part of this endeavor, new candidate enzymes identified from natural diversity can serve as useful starting points for enzyme evolution and engineering. In this study, we improved upon HMM searches by applying an iterative machine learning strategy to identify 400 putative PET-degrading enzymes (PET hydrolases) from naturally occurring homologs. Using high-throughput (HTP) experimental techniques, we successfully expressed and purified >200 enzyme candidates and assayed them for PET hydrolysis activity as a function of pH, temperature, and substrate crystallinity. From this library, we discovered 91 previously unknown PET hydrolases, 35 of which retain activity at pH 4.5 on crystalline material, which are conditions relevant to developing more efficient commercial processes. Notably, four enzymes showed equal to or higher activity than LCC-ICCG, a benchmark PET hydrolase, at this challenging condition in our screening assay, and 11 of which have pH optima <7. Using these data, we identified regions of PETases statistically correlated to activity at lower pH. We additionally investigated the effect of condition-specific activity data on trained machine learning predictors and found a precision (putative hit rate) improvement of up to 30% compared to a Hidden Markov Model alone. Our findings show that by pointing enzyme discovery toward conditions of interest with multiple rounds of experimental and machine learning, we can discover large sets of active enzymes and explore factors associated with activity at those conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Data-driven predictions of complex organic mixture permeation in polymer membranes

Membrane-based organic solvent separations are rapidly emerging as a promising class of technologies for enhancing the energy efficiency of existing separation and purification systems. Polymeric membranes have shown promise in the fractionation or splitting of complex mixtures of organic molecules such as crude oil. Determining the separation performance of a polymer membrane when challenged with a complex mixture has thus far occurred in an ad hoc manner, and methods to predict the performance based on mixture composition and polymer chemistry are unavailable. Here, we combine physics-informed machine learning algorithms (ML) and mass transport simulations to create an integrated predictive model for the separation of complex mixtures containing up to 400 components via any arbitrary linear polymer membrane. We experimentally demonstrate the effectiveness of the model by predicting the separation of two crude oils within 6-7% of the measurements. Integration of ML predictors of diffusion and sorption properties of molecules with transport simulators enables for the rapid screening of polymer membranes prior to physical experimentation for the separation of complex liquid mixtures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗