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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 19 records

Experimental characterization and analysis of phase change material-based thermal energy storage system for refrigerated display case

Refrigerated display cases that are used to store and exhibit food products in supermarkets and retail spaces consume a significant portion of the buildings’ total electricity. Importantly, the refrigeration-related energy cost and demand charges are greatly affected by the time-of-use electricity pricing and demand rates, which are at their maximum during peak hours, typically when refrigeration energy consumption is also high. Using energy storage to shift the refrigeration load from peak to off-peak hours can greatly reduce the operational costs in the supermarket. This study demonstrates a phase change material-based thermal energy storage (TES) system, specifically designed in stackable units, that can be integrated with an open vertical refrigerated display case. We perform numerical and experimental characterization that includes finite-difference modeling for the TES, prototype fabrication, and laboratory evaluation, followed by a preliminary system-level analysis to predict the impact of TES on the refrigerated case performance, energy use, and energy cost. The results show that the dedicated latent TES for refrigerated cases can provide a specific energy of 50.4 Wh/kg and a specific power of 15.5 W/kg. The TES can be charged during 12 h of the off-peak period and discharged at various rates during 4 to 6 h of the peak period, thereby shifting the refrigeration load from the peak to the off-peak period. Consequently, annual cost savings up to 19% can be achieved, depending on the thermal load, the summer/winter peak electricity pricing, and the transition temperature of the phase change material used.

25 ENERGY STORAGE↗

Predictive model using artificial neural network to design phase change material-based ocean thermal energy harvesting systems for powering uncrewed underwater vehicles

Uncrewed Underwater Vehicles (UUVs) are a major beneficiary of the phase change material (PCM)-based ocean thermal energy harvesting technology for their mission needs. However, this technology relies on different parameters and energy conversion steps that could be critical to the general energy generation efficiency. Sea trials showed that the design performed lower than their laboratory design specifications. This underperformance results from different factors, mainly the UUV’s trajectory, travel time, underwater ocean currents, temperature fluctuations, and biofouling on the heat exchanger due to long term underwater operations. Therefore, there exists a need to continuously monitor the ambient energy harvesting system and predict system performance, for mission planning purposes. Two major parameters influencing the energy harvesting system include the final pressure inside the hydraulic energy storage vessel or accumulator, and the electrical load value. Here, this work focuses on the hydraulic to electric energy conversion system. Therefore, a combination of numerical model and experimental testing is used to develop a predictive model using artificial neural network using MATLAB. After validation with experimental testing, 1000 data samples obtained from the numerical model are used to train the ANN. Compared to the experimental results, the developed ANN model can predict in less than a second the designed benchtop system’s total efficiency with less than 15 percent maximum error range. This predictive model development represents a cost-effective way for optimization and a computational energy efficient mode aboard UUVs for mission planning for deployed UUVs using PCM-based ocean thermal energy harvesting technology.

30 DIRECT ENERGY CONVERSION↗

Towards low-carbon low-energy concrete alternatives: Life cycle assessment of carbonated cementitious material-based precast panels

Cement is responsible for 22 % of all global CO 2 emissions from industrial processes. Technological innovation for developing and deploying of alternative materials will be required to decarbonize the cement industry. Carbonated cementitious materials (CCMs) are building materials that rely on carbon mineralization for their strength. A process-based cradle-to-gate life cycle assessment (LCA) was conducted to evaluate the global warming potential (GWP), cumulative energy demand, and water consumption of a lab-scale CCM-based precast panel compared to a conventional precast concrete panel. Since the CCM process is currently a lab-scale early-stage process, the CCM panel showed higher environmental impacts compared to the conventional panel. However, scenario analyses include mature production process scenarios. In conclusion, a sensitivity analysis revealed that the GWP of CCM can be lowered to below that of the conventional panel using polymers, fillers, low-carbon electricity sources, and optimized carbonation parameters.

36 MATERIALS SCIENCE↗

Few-mode and anisotropic quantum transport in InSb nanoribbons using an all-van der Waals material-based gate

High-quality electrostatic gating is a fundamental ingredient for successful semiconducting device physics, and a key element of realizing clean quantum transport. Inspired by the widespread improvement of transport quality when two-dimensional van der Waals (vdW) materials are gated exclusively by other vdW materials, we have developed a method for gating non-vdW materials with an all-vdW gate stack, consisting of a hexagonal boron nitride dielectric layer and a few-layer graphite gate electrode. We demonstrate this gating approach on MOVPE-grown InSb nanoribbons (NRs), a novel variant of the InSb nanowire, with a flattened cross-section. In our all-vdW gated NR devices we observe conductance features that are reproducible and have low- to near-zero gate hysteresis. We also report quantized conductance, which persists to lower magnetic fields and longer channel lengths than typical InSb nanowire devices reported to date. Additionally, we observe level splitting that is highly anisotropic in an applied magnetic field, which we attribute to the ribbon cross-section. The performance of our devices is consistent with the reduced disorder expected from the all-vdW gating scheme, and marks the first report of ballistic, few-modes quantum transport in a non-vdW material with an all-vdW gate. Our results establish all-vdW gating as a promising approach for high-quality gating of non-vdW materials for quantum transport, which is in principle applicable generically, beyond InSb systems. In addition, the work showcases the specific potential of all-vdW gate/InSb NR devices for enabling clean quantum devices that may be relevant for spintronics and topological superconductivity studies.

InSb↗

Hydrogen Storage System Modeling: Public Access, Maintenance, and Enhancements

The overall vision of this project is to provide ownership and support for maintaining existing material-based hydrogen storage systems models. This includes making models accessible to the research community through a public web page and updating and enhancing storage systems models to support material developers in assessing their materials relative to DOE vehicle-level targets. Key elements for FY24: Continue to update and enhance existing models for broader application and user-friendliness. Develop tools to evaluate the performance of hydrogen storage materials developed under HyMARC activities or other fundamental hydrogen storage materials discovery research. Expand the application of current hydrogen storage models beyond light-duty vehicles to include medium-, heavy-duty, and mining vehicles and stationary application(s). Develop models for alternatives, such as LOHCs, to material-based systems (liquefied & gaseous H2) and compare for various mobile and stationary use cases.

ENERGY STORAGE,HYDROGEN↗

Scalable thin graphene oxide membranes enabled by polydopamine gutter layer

Two-dimensional (2D) nanosheets have been widely used to fabricate thin-film composite membranes for dye desalination. However, they often need to be thick to mitigate the defects resulting from their random stacking and rough support surface. Herein, bio-adhesive polydopamine (PDA) is used as a gutter layer to prepare graphene oxide (GO)-based membranes by improving the adhesion between the GO and porous support and providing a smooth surface to form thin, highly selective layers. For example, the PDA priming reduces the GO layer thickness by 57 %, from 447 to 190 nm, while achieving similar dye desalination properties. The effect of the dopamine concentration, exposure time, and GO layer thickness on the membrane structure and desalination performance are thoroughly investigated using various techniques, such as scanning electron microscopy (SEM), x-ray photoelectron spectroscopy (XPS), and x-ray diffraction (XRD). The PDA gutter layer is also applied for hollow fiber membranes, achieving water permeance of 79 L m -2 h −1 bar−1 and rejection of ∼99 % for Direct red 80. The membranes were challenged by simulated dye/salt mixtures to elucidate the complicated effect of the compositions on the desalination performance. Furthermore, this study unveils a new avenue to improve separation performance and large-scale manufacturability of 2D material-based membranes.

Dye desalination↗

Large scale polymer toughening of two-dimensional materials revealed by in situ TEM fracture tests and multiscale simulations

Two-dimensional (2D) materials offer significant potential for applications in energy-harvesting devices, batteries, sensors, and transistors. However, their intrinsic brittleness makes them prone to mechanical failure, limiting their practical use. In this work, we perform in situ transmission electron microscopy (TEM) fracture tests on monolayer MoSe2 and uncover an extrinsic toughening effect induced by an ultrathin adsorbed polystyrene adlayer. This adlayer substantially enhances the fracture resistance of the 2D flakes. Through a combination of molecular dynamics simulations and finite element analysis, we elucidate the molecular mechanism behind this toughening effect. Further, it arises from the active crack-bridging behavior of entangled polymer chains and the formation of a fracture process zone that stabilizes crack propagation and increases the energy required for crack extension. The proposed toughening mechanism offers a pathway to improving the mechanical reliability of 2D material-based devices by mitigating the risk of sudden failure.

2D materials↗

Probing Operando Electrochemical Strain Generation in α-NaFeO 2 Composite Cathodes during Cycling of Na-Ion Batteries

The transition metal oxide (TMO) cathodes in Na-ion batteries suffer from low-capacity retention. Chemo-mechanical instabilities lead to the deterioration of the electrochemical performance of TMO cathodes in Li-ion batteries. However, there is not much known about the chemo-mechanical instabilities in the TMO cathodes for Na-ion batteries. Understanding the governing forces behind the interplay between the electrochemical performance and mechanical stability in TMO cathodes is critical for the development of Na-ion batteries. Here, we synchronize the digital image correlation (DIC) technique with electrochemical analysis to capture the real-time deformation behavior of the α-NaFeO 2 cathodes during cycling. When the charge cutoff voltage is 3.6 V, the cathode experiences reversible deformations (except for the first cycle). There is negative strain (shrinkage) generation during Na extraction and positive strain (expansion) generation during the subsequent Na insertion. A detailed analysis of the potential-dependent strain rate evolution points out complicated phase transformations and nonequilibrium conditions in the α-NaFeO 2 cathodes during cycling. When the charge cutoff voltage was increased to 4.2 V, there was a rapid capacity loss and large plastic deformations in the α-NaFeO 2 cathodes. We provide an in-depth discussion about the possible mechanisms behind the chemo-mechanical instabilities in the α-NaFeO 2 . In conclusion, the correlation is critical to develop material-based strategies to mitigate instability mechanisms in TMO cathodes for Na-ion batteries.

Wable, Minal [University of Maryland Baltimore Cou↗

Observation of a Picosecond Light-Induced Spin Transition in Polymeric Nanorods

Spin transition (ST) materials are attractive for developing photoswitchable devices, but their slow material transformations limit device applications. Size reduction could enable faster switching, but the photoinduced dynamics at the nanoscale remains poorly understood. Here, we report a femtosecond optical pump multimodal X-ray probe study of polymeric nanorods. Simultaneously tracking the ST order parameter with X-ray emission spectroscopy and structure with X-ray diffraction, we observe photodoping of the low-spin–lattice within ~150 fs. Above a ~16% photodoping threshold, the transition to the high-spin phase occurs following an incubation period assigned to vibrational energy redistribution within the nanorods activating the molecular spin switching. Above ~60% photodoping, the incubation period disappears, and the transition completes within ~50 ps, preceded by the elastic nanorod expansion in response to the photodoping. These results support the feasibility of ST material-based GHz optical switching applications.

36 MATERIALS SCIENCE↗

Atomic Precision Processing of Two-Dimensional Materials for Next-Generation Microelectronics

The growth of the information era economy is driving the pursuit of advanced materials for microelectronics, spurred by exploration into “Beyond CMOS” and “More than Moore” paradigms. Atomically thin 2D materials, such as transition metal dichalcogenides (TMDCs), show great potential for next-generation microelectronics due to their properties and defect engineering capabilities. This perspective delves into atomic precision processing (APP) techniques like atomic layer deposition (ALD), epitaxy, atomic layer etching (ALE), and atomic precision advanced manufacturing (APAM) for the fabrication and modification of 2D materials, essential for future semiconductor devices. Additive APP methods like ALD and epitaxy provide precise control over composition, crystallinity, and thickness at the atomic scale, facilitating high-performance device integration. Subtractive APP techniques, such as ALE, focus on atomic-scale etching control for 2D material functionality and manufacturing. In APAM, modification techniques aim at atomic-scale defect control, offering tailored device functions and improved performance. Achieving optimal performance and energy efficiency in 2D material-based microelectronics requires a comprehensive approach encompassing fundamental understanding, process modeling, and high-throughput metrology. Finally, the outlook for APP in 2D materials is promising, with ongoing developments poised to impact manufacturing and fundamental materials science. Integration with advanced metrology and codesign frameworks will accelerate the realization of next-generation microelectronics enabled by 2D materials.

36 MATERIALS SCIENCE↗

All 2D Material Printed Diodes and Circuits on Paper for Sustainable Electronics

Sustainable electronics aim to reduce environmental impact by using ecofriendly materials, energy-efficient manufacturing, and recyclable components. However, existing approaches rely on complex, resource-intensive methods, rare metals, or nanomaterials with limited stability as well as plastic substrates, raising sustainability issues. Solution-processed two-dimensional (2D) materials offer a promising alternative: water-based and biocompatible conductive, semiconductive, and insulating 2D material inks can be produced with scalable techniques and are suitable for the fabrication of fully printed devices on low-cost and biodegradable paper substrates. However, 2D material only and fully printed diodes on paper have not yet been reported. Here, we demonstrate fully inkjet-printed 2D material-based diodes on paper using metal-insulator-semiconductor and metal-insulator-metal-semiconductor architectures. Water-based graphene and MoS2 inks, prepared by liquid-phase exfoliation, are used for the metallic and insulating films, while electrochemical exfoliation is used to produce the semiconducting MoS2 ink. The highest forward-to-reverse current ratio obtained is 330 (at ±2 V), while the forward current density is 1 mA/cm2 (at 1 V), making the diode performance comparable to the best solution-processed diodes reported so far. However, in contrast to previous works, fabrication occurs entirely at room temperature and ambient pressure, without using high-pressure sputtering, thermal evaporation, and any precious metal ink. The devices maintain stable performance under bending up to strain of 4% over 10,000 cycles. Finally, the diodes are successfully integrated with other 2D-material based electrical components to realize fully printed RC circuits, differentiators, integrators, and AC-to-DC converters onto paper, hence demonstrating the suitability of our approach for sustainable and disposable integrated circuits.

2D materials↗

Nonlinear encoding in diffractive information processing using linear optical materials

Nonlinear encoding of optical information can be achieved using various forms of data representation. Here, we analyze the performances of different nonlinear information encoding strategies that can be employed in diffractive optical processors based on linear materials and shed light on their utility and performance gaps compared to the state-of-the-art digital deep neural networks. For a comprehensive evaluation, we used different datasets to compare the statistical inference performance of simpler-to-implement nonlinear encoding strategies that involve, e.g., phase encoding, against data repetition-based nonlinear encoding strategies. We show that data repetition within a diffractive volume (e.g., through an optical cavity or cascaded introduction of the input data) causes the loss of the universal linear transformation capability of a diffractive optical processor. Therefore, data repetition-based diffractive blocks cannot provide optical analogs to fully connected or convolutional layers commonly employed in digital neural networks. However, they can still be effectively trained for specific inference tasks and achieve enhanced accuracy, benefiting from the nonlinear encoding of the input information. Our results also reveal that phase encoding of input information without data repetition provides a simpler nonlinear encoding strategy with comparable statistical inference accuracy to data repetition-based diffractive processors. Our analyses and conclusions would be of broad interest to explore the push-pull relationship between linear material-based diffractive optical systems and nonlinear encoding strategies in visual information processors.

42 ENGINEERING↗

Tuning the low-energy band structure in twisted bilayer WSe2

Tuning the electronic structures of two-dimensional (2D) material-based heterostructures is of crucial importance for their use in functional next-generation electronics. Here, through angle-resolved photoemission spectroscopy with nanoscale spatial resolution (nano-ARPES), we systematically track the evolution of the near-Fermi-level electronic structure of bilayer WSe2 over a large range of twist angle. While the momentum positioning of the valence-band maxima (VBM) is independent of twist angle, we find that the energetic separation between the hole bands at the K point of the Brillouin zone and the higher binding-energy hole band at Γ can be varied in excess of 100 meV. We explore the mechanisms underpinning this evolution and discuss the implications for tuning both the size of the band gaps, and the efficiency of the spin-dependent electron-phonon coupling channels in homobilayer transition-metal dichalcogenide devices.

Vu, T-H-Y↗

Halide Perovskite Solar Photovoltaics

Technological progress in photovoltaic (PV) technologies provides hope that a comprehensive and desperately needed decarbonization of the energy sector is possible. Commercially successful PV technologies based predominantly on silicon wafer technology are reliable and cost-effective, but remain capital- and carbon-intensive. In this context, emerging PV technologies, such as metal-halide perovskites (MHPs), could further catalyze the energy transition by providing technological opportunities for even lower-cost, mass-producible, high-efficiency solar cells with a significantly reduced "carbon footprint." This themed issue of MRS Bulletin on "Halide perovskite solar photovoltaics summarizes the current state of the art, challenges, and opportunities of perovskite photovoltaics with contributions and perspectives from six expert teams worldwide. The topics covered provide a status update on perovskite PV, remaining hurdles to their deployment, and challenges to realizing the potential of this technology to impact climate goals. Articles in this collection address scalability of perovskite PV and prospects for industrial manufacturing; perovskite PV as an add-on technology on top of commercial silicon PV; environmental and sustainability considerations; and durability and reliability considerations. Further considerations include prospects of automation, coupled to artificial intelligence and machine learning, for accelerating material-based solutions to these outstanding challenges including the possibilities of discovering new absorber and device component materials to enable success and ultimately deployment of these next-generation PVs.

metal-halide perovskites↗

High Capacity Step-Shaped Hydrogen Adsorption in Robust, Pore-Gating Zeolitic Imidazolate Frameworks (Final Technical Report)

The use of porous adsorbents for the densification of H 2 under relatively mild pressures and temperatures has been long pursued through various avenues of synthetic organic frameworks, namely metal–organic frameworks. However, the overwhelming majority of these materials are macroscopically rigid, exhibiting adsorption–desorption profiles that require appreciable energetic input for their full payload capacity to be stored and subsequently delivered. This reduced “deliverable” capacity is a core inefficiency in the use of porous adsorbents for H 2 densification. Our core mission is to determine a material-based strategy that fundamentally alters the adsorption¬–desorption profile in a manner that obviates these deleterious energetic requirements. Towards this, we have focused on metal–organic frameworks that exhibit “cooperative flexibility”, wherein the material undergoes reversible macroscopic phase changes in response to changes to external temperature and/or adsorbate pressure (i.e., concentration). Where these reversible switches occur between states of disparate enough accessible porosity, cooperatively flexible frameworks can exhibit “step-shaped” adsorption–desorption profiles that enable use of the delivery gaseous payload without the aforementioned additional energy requirements. However, before our work, such the observation of this phenomenon with very weakly adsorbing H 2 had not been observed with the necessary profile and P/T conditions desired for H 2 storage and delivery. During this project we have leveraged a deep understanding of the phase change in family of cooperatively flexible metal–organic frameworks to systematically alter their adsorption–desorption profiles to achieve step-shaped adsorption and desorption of H 2 in a precise P/T regime that enables a high deliverable capacity. Specifically, the thermodynamics of the adsorption/desorption induced phase changes in the baseline framework CdIF-13 (sod–Cd(benzimidazolate) 2 ) were tuned using the mixed-linker, or multivariate, approach to framework derivatization. Follow this, we have pursued a similar approach to tuning the adsorption–desorption profile of a second framework family, MIL-53(Al), which contains only Al(III) and theoretically exhibits a much higher deliverable capacity. In total, our work demonstrates that by first understanding the structural consequences of phase changes in these materials, their behavior can be systematically altered through ligand substitutions, tuning the pressure and temperature conditions at which H 2 is adsorbed and desorbed. Thus, enabling high deliverable capacities of H 2 with minimized energetic requirements.

08 HYDROGEN↗

Analyzing Potential Failures and Effects in a Pilot-Scale Biomass Preprocessing Facility for Improved Reliability

This study demonstrates a failure identification methodology applied to a preprocessing facility generating conversion-ready feedstocks from biomass meeting conversion process critical quality attribute (CQA) specifications. Failure Modes and Effects Analysis (FMEA) was used as an industrially relevant risk analysis approach to evaluate a logging residue preprocessing system to prepare feedstock for pyrolysis conversion. Risk evaluations considered both system-level and operation unit-level assessments considering process efficiency, product quality, cost, sustainability, and safety. Key outputs included estimations of semi-quantitative risk scores for each failure, identification of the failure impacts, identification of failure causes associated with material attributes and process parameters, ranking success rates of failure detection methods, and speculation of potential mitigation strategies for decreasing failure risk scores. Results showed that deviations from moisture specifications had cascading consequences for other CQAs along with process safety implications. Failures linked to fixed carbon specifications carried the highest risk scores for product quality and process efficiency impacts. As increased throughput can be inversely related to meeting product quality specifications; achieving throughput and other material-based CQAs simultaneously will likely require system optimization or prioritization based on system economics. Ultimately, this work successfully demonstrates FMEA as a risk analysis approach for other bioenergy process systems.

09 BIOMASS FUELS↗

The Extended Embedded Self-Shielding Method in SCALE 6.3/Polaris

The SCALE transport lattice code, Polaris, has been previously developed to generate few-group homogenized cross sections for whole-core nodal diffusion simulators in which the embedded self-shielding method (ESSM) is used for resonance self-shielding calculations to process cross sections. Although the ESSM capability has been very successful in light-water reactor analysis, it may require enhancements in computational efficiency; treatment of spatially dependent resonance self-shielding effects; and handling of interrelated resonance effects among fuel, cladding, and control rod materials. Therefore, this study focuses on improving computational efficiency by using a Dancoff-based Wigner–Seitz approximation combined with a material-based resonance categorization, through which a spatially dependent ESSM capability is developed to accurately estimate self-shielded cross sections inside the fuel. Benchmark results show that the new capability significantly enhances computational efficiency and accuracy for spatially dependent local zones within the fuel and through depletion.

ESSM↗