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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Customizable Nonplanar Printing of Lithium‐Ion Batteries

Abstract Lithium‐ion batteries (LIBs) are widely used in consumer electronics due to their rechargeability and high energy density. Commercial LIBs are fabricated in fixed geometries such as cylinder, coin, and pouch. However, for specialized applications such as wearable electronics and on‐device power systems, customizable LIBs with arbitrary geometry on three‐dimensional (3D) structures need to be developed. For this purpose, aerosol printing is uniquely suitable due to its flexible working distance, allowing deposition on nonplanar substrates with multiscale surface topologies. Aerosol printing of LiFePO 4 cathodes and Li 4 Ti 5 O 12 anodes for LIBs is presented. Electrodes with an arbitrary geometry, tailorable thickness and on nonplanar substrates can be realized. The highest areal capacity achieved is ≈7.1 mAh cm −2 , which is at least twice that of conventional electrodes. Furthermore, to package the printed electrodes, 3D enclosures are fabricated via fused deposition modeling of polyvinylidene fluoride. The printed electrodes packaged in 3D enclosures exhibit 78.4% capacity retention after 30 cycles. With the two additive manufacturing processes, customizable LIBs on targeted objects can be realized. A nonplanar LIB conformably covering the edge of a block with specific capacity of 135 mAh g −1 is demonstrated.

Yu, Xiaowei↗
DOE OSTI2022

Size-Dependent Photon Avalanching in Tm 3+ Doped LiYF 4 Nano, Micro, and Bulk Crystals

Photon avalanche (PA) is a highly nonlinear mode of upconversion that is characterized by 100–1000-fold increase in luminescence intensity upon minute increments of pumping power. The practical realization of numerous possible nano-bio-technology applications utilizing the PA phenomenon will require information on its susceptibility to the material volume and surface. In this report these parameters are investigated via experimental and theoretical PA. The two-color, highly nonlinear PA emission at 475 and 800 nm is clearly observed in bulk single crystal, individual microcrystals, and ensembles of colloidal core and core–shell nanoparticles of LiYF 4 host doped with either 3 or 8% of thulium ions. The properties of PA emission, such as PA nonlinearity, PA gain, PA intensity, and luminescence kinetics in these materials show dependence on crystal volume and surface quenching. Theoretical simulations provide understanding of key physical processes that influence PA performance. Moreover, photon avalanche single beam super-resolution imaging is realized for the first time in 3% Tm 3+ doped LiYF 4 core–shell nanoparticles. The obtained insights and predictions form a solid background for further development and applications of new optimized PA materials.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Digital and Gradient Refractive Index Planar Optics by Nanoimprinting Mesoporous Silicon

We report the realization of digital and gradient index flat-optics and planar waveguides using the ‘nanoimprinting refractive index’ (NIRI) technique applied to mesoporous silicon. This technique combines the distinct optical and mechanical metamaterial qualities of mesoporous silicon, including its widely tunable effective refractive index and ability to undergo plastic deformation with a near zero Poisson ratio. Nanoimprinting with premastered and reusable stamps containing analog or digital features enables the continuous or discontinuous patterning of refractive index with high contrast Δn ≥ 0.8 and subwavelength resolution. Using NIRI we experimentally demonstrate a wavefront shaping flat microlens array operating in the visible (405–635 nm) and mesoporous silicon and silica waveguides operating near 1310 nm. This study demonstrates the viability of patterning arbitrary refractive index distributions, n(x,y), on the surface of a chip while circumventing the challenges and limitations of top-down lithographic techniques – thus opening a low-cost and scalable approach for the realization of advanced planar optical technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Surface‐Enforced Alignment of Reprogrammable Liquid Crystalline Elastomers

Abstract Liquid crystalline elastomers (LCEs) are stimuli‐responsive materials capable of undergoing large deformations. The thermomechanical response of LCEs is attributable to the coupling of polymer network properties and disruption of order between liquid crystalline mesogens. Complex deformations have been realized in LCEs by either programming the nematic director via surface‐enforced alignment or localized mechanical deformation in materials incorporating dynamic covalent chemistries. Here, the preparation of LCEs via thiol‐Michael addition reaction is reported that are amenable to surface‐enforced alignment. Afforded by the thiol‐Michael addition reaction, dynamic covalent bonds are uniquely incorporated in chemistries subject to surface‐enforce alignment. Accordingly, LCEs prepared with complex director profiles are able to be programmed and reprogrammed by (re)activating the dynamic covalent chemistry to realize distinctive shape transformations.

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

New Chemical Dopant and Counterion Mechanism for Organic Electrochemical Transistors and Organic Mixed Ionic–Electronic Conductors

Abstract Organic mixed ionic–electronic conductors (OMIECs) have varied performance requirements across a diverse application space. Chemically doping the OMIEC can be a simple, low‐cost approach for adapting performance metrics. However, complex challenges, such as identifying new dopant materials and elucidating design rules, inhibit its realization. Here, these challenges are approached by introducing a new n‐dopant, tetrabutylammonium hydroxide (TBA‐OH), and identifying a new design consideration underpinning its success. TBA‐OH behaves as both a chemical n‐dopant and morphology additive in donor acceptor co‐polymer naphthodithiophene diimide‐based polymer, which serves as an electron transporting material in organic electrochemical transistors (OECTs). The combined effects enhance OECT transconductance, charge carrier mobility, and volumetric capacitance, representative of the key metrics underpinning all OMIEC applications. Additionally, when the TBA + counterion adopts an “edge‐on” location relative to the polymer backbone, Coulombic interaction between the counterion and polaron is reduced, and polaron delocalization increases. This is the first time such mechanisms are identified in doped‐OECTs and doped‐OMIECs. The work herein therefore takes the first steps toward developing the design guidelines needed to realize chemical doping as a generic strategy for tailoring performance metrics in OECTs and OMIECs.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Phase Diagrams and Piezoelectric Properties of Wurtzite Al1-x-yScxGdyN Heterostructural Alloys

Ternary nitride alloys based on wurtzite AlN are a promising platform to realize functional materials, particularly ferroelectrics and optical emitters, that can smoothly integrate with conventional microelectronics. Here, a strategic design is presented to enable multifunctional materials by substituting multiple elements into AlN to create quaternary nitride alloys. By combining computational predictions and combinatorial thin film synthesis, the phase diagram of these quaternary Al-Sc-Gd-N alloys (or pseudo-ternary heterostructural AlN-ScN-GdN alloys) is successfully predicted as a function of effective temperature, and we experimentally grow Al1-x-xScxGdyN thin films for the first time. It is revealed that Al1-x-xScxGdyN crystallizes in a wurtzite-derived structure for X + y <~ 0.35, consistent with the calculated phase diagram. The computational investigation explores whether co-substitution induces cooperative effects on these alloys' piezoelectric and ferroelectric properties, finding that it is beneficial for reducing the polarization switching barrier. We calculate that Al1-x-xScxGdyN thin films should display ferroelectric switching. This is supported by our experimental measurements of a high optical bandgap, enhanced piezoelectric coefficient, and a change in the calculated polarization switching mechanism, and we achieve preliminary ferroelectric switching that experimentally realizes the prediction. Overall, our work sets the foundation toward quaternary wurtzite-nitride-based multifunctional materials, including piezoelectrics, ferroelectrics, and possibly even multiferroics.

36 MATERIALS SCIENCE↗
DOE OSTI2024

High Mobility, High Carrier Density SnSe 2 Field‐Effect Transistors with Ultralow Subthreshold Swing and Gate‐Controlled Photoconductance Switching

2D and layered semiconductors are considered as promising electronic materials, particularly for applications that require high carrier mobility and efficient field-effect switching combined with mechanical flexibility. To date, however, the highest mobility has been realized primarily at low carrier concentration. Here, it is shown that few-layer/multilayer SnSe 2 gated by a solution top gate combines very high room-temperature electron mobility (up to 800 cm 2 V −1 s −1 ), along with large on-off current ratios (>10 5 ) and a subthreshold swing below the thermodynamic limit (50 mV per decade) in field-effect devices, at exceptionally large sheet carrier concentrations of ≈10 13 cm −2 . Observed mobility enhancements upon partial depletion of the channel point to near-surface defects or impurities as the mobility-limiting scattering centers. Under illumination, the resulting gap states give rise to gate-controlled switching between positive and negative photoconductance. The results qualify SnSe 2 as a promising layered semiconductor for flexible and wearable electronics, as well as for the realization of advanced approaches to photodetection.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Understanding the Role of Cesium on Chemical Complexity in Methylammonium-Free Metal Halide Perovskites

Mixed cesium- and formamidinium-based metal halide perovskites (MHPs) are emerging as ideal photovoltaic materials due to their promising performance and improved stability. While theoretical predictions suggest that a larger composition ratio of Cs (≈30%) aids the formation of a pure photoactive α-phase, high photovoltaic performances can only be realized in MHPs with moderate Cs ratios. In fact, elemental mixing in a solution can result in chemical complexities with non-equilibrium phases, causing chemical inhomogeneities localized in the MHPs that are not traceable with global device-level measurements. Thus, the chemical origin of the complexities and understanding of their effect on stability and functionality remain elusive. Herein, through spatially resolved analyses, the fate of local chemical structures, particularly the evolution pathway of non-equilibrium phases and the resulting local inhomogeneities in MHPs is comprehensively explored. It is illustrated that Cs-rich MHPs have substantial local inhomogeneities at the initial crystallization step, which do not fully convert to the α-phase and thereby compromise the optoelectronic performance of the materials. These fundamental observations allow the authors to draw a complete chemical landscape of MHPs including nanoscale chemical mechanisms, providing indispensable insights into the realization of a functional materials platform.

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

Carbon-Nanotube-Bridging Strategy for Integrating Single Fe Atoms and NiCo Nanoparticles in a Bifunctional Oxygen Electrocatalyst toward High-Efficiency and Long-Life Rechargeable Zinc–Air Batteries

The development of highly efficient and robust bifunctional electrocatalysts for oxygen reduction (ORR) and evolution reactions (OER) is the key issue for realizing high-performance and long-life rechargeable zinc–air batteries (ZABs). However, it is still a great challenge to integrate independent ORR and OER sites in a catalyst with high activity. Here, a carbon nanotube-bridging strategy is proposed to synthesize such a bifunctional oxygen electrocatalyst enriched with highly active single-atom Fe sites for the ORR and high-performance nanosized NiCo hydroxides for the OER. Consequently, the developed catalyst shows a small overpotential difference of 0.686 V. When used as an oxygen electrode catalyst, the corresponding ZAB exhibits a large power density of 219.5 mW cm ₋2 , a small charge–discharge voltage gap of 0.72 V at 10 mA cm ₋2 , and outstanding discharge–charge durability without attenuation after more than 700 cycles. This work proposes a new idea to realize multifunctional catalysts and drives the practical application of ZABs.

25 ENERGY STORAGE↗
DOE OSTI2023

Thermochromic Halide Perovskite Windows with Ideal Transition Temperatures

Abstract Urban centers across the globe are responsible for a significant fraction of energy consumption and CO 2 emission. As urban centers continue to grow, the popularity of glass as cladding material in urban buildings is an alarming trend. Dynamic windows reduce heating and cooling loads in buildings by passive heating in cold seasons and mitigating solar heat gain in hot seasons. Here, reduced energy consumption in highly glazed buildings in a mesoscopic building energy model is demonstrated when thermochromic windows are employed. Savings are realized across eight disparate climate zones of the United States. The model is used to determine ideal critical transition temperatures of 20–27.5 °C for thermochromic windows based on metal halide perovskite materials. Ideal transition temperatures are realized experimentally in composite metal halide perovskite films composed of perovskite crystals and an adjacent reservoir phase. The transition temperature is controlled by cointercalating methanol, instead of water, with methylammonium iodide and tailoring the hydrogen‐bonding chemistry of the reservoir phase. Thermochromic windows based on metal halide perovskites represent a clear opportunity to mitigate the effects of energy‐hungry buildings.

14 SOLAR ENERGY↗
DOE OSTI2025

Screening and Development of Sacrificial Cathode Additives for Lithium‐Ion Batteries

Abstract This work presents a computational screening approach to identify Li‐rich transition‐metal oxide sacrificial cathode additives and provides experimental validation of antifluorite‐structured Li 6 MnO 4 as a potential candidate. Initial attempts to synthesize this compound result in low purity (≤40% by weight) owing to close thermodynamic competition with Li 2 O and MnO at low temperature. However, it is shown that a much higher purity of 85% by weight can be achieved by combining Li excess with rapid cooling from high temperature, which effectively stabilizes the Li 6 MnO 4 phase. The synthesized product delivers a high irreversible Li release capacity that exceeds 700 mAh g −1 by utilizing combined Mn oxidation (Mn 2+/3+ and Mn 3+/4+ ) and O oxidation. These results demonstrate that Li 6 MnO 4 may therefore be useful as a potential sacrificial cathode additive in Li‐ion batteries and motivate further investigation of other structurally‐related compounds. While attempts were made to synthesize two additional compounds among computationally screened candidates, it was not successful to experimentally realize the two candidates. The difficulty of experimental realization of the newly predicted materials remains a challenge and it is suggested that more efforts need to be devoted to developing computational techniques to precisely predict synthesizability and propose potential synthetic routes of the predicted materials.

Kim, Haegyeom↗
DOE OSTI2020

A Roadmap for Reaching the Potential of Brain-Derived Computing

Neuromorphic computing is a critical future technology for the computing industry, but it has yet to achieve its promise and has struggled to establish a cohesive research community. A large part of the challenge is that full realization of the potential of brain inspiration requires advances in both device hardware, computing architectures, and algorithms. This simultaneous development across technology scales is unprecedented in the computing field. This article presents a strategy, framed by market and policy pressures, for moving past these current technological and cultural hurdles to realize its full impact across technology. Achieving the full potential of brain-derived algorithms as well as post-complementary metal-oxide-semiconductor (CMOS) scaling neuromorphic hardware requires appropriately balancing the near-term opportunities of deep learning applications with the long-term potential of less understood opportunities in neural computing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Stabilizing *CO 2 Intermediates at the Acidic Interface using Molecularly Dispersed Cobalt Phthalocyanine as Catalysts for CO 2 Reduction

Abstract CO 2 electroreduction (CO 2 R) operating in acidic media circumvents the problems of carbonate formation and CO 2 crossover in neutral/alkaline electrolyzers. Alkali cations have been universally recognized as indispensable components for acidic CO 2 R, while they cause the inevitable issue of salt precipitation. It is therefore desirable to realize alkali‐cation‐free CO 2 R in pure acid. However, without alkali cations, stabilizing *CO 2 intermediates by catalyst itself at the acidic interface poses as a challenge. Herein, we first demonstrate that a carbon nanotube‐supported molecularly dispersed cobalt phthalocyanine (CoPc@CNT) catalyst provides the Co single‐atom active site with energetically localizeddstates to strengthen the adsorbate‐surface interactions, which stabilizes *CO 2 intermediates at the acidic interface (pH=1). As a result, we realize CO 2 conversion to CO in pure acid with a faradaic efficiency of 60 % at pH=2 in flow cell. Furthermore, CO 2 is successfully converted in cation exchanged membrane‐based electrode assembly with a faradaic efficiency of 73 %. For CoPc@CNT, acidic conditions also promote the intrinsic activity of CO 2 R compared to alkaline conditions, since the potential‐limiting step, *CO 2 to *COOH, is pH‐dependent. This work provides a new understanding for the stabilization of reaction intermediates and facilitates the designs of catalysts and devices for acidic CO 2 R.

Chemistry↗
DOE OSTI2025

Quantum Anomalies in Condensed Matter

Quantum materials provide a fertile ground in which to test and realize unusual phenomena such as quantum anomalies predicted by quantum field theory. There are three important symmetries that are broken when classical field theory is moved into the quantum regime, the scale anomaly, the axial (chiral) anomaly, and the parity anomaly. Several potential device applications may be realized by the discovery of quantum anomalies in condensed matter, enabled by the new physics they embody, including ultra‐sensitive dark matter detectors, far infrared optical modulators, micro‐bolometric detectors, low‐dissipation ballistic transporters, terahertz‐based qubits, terahertz polarization state controls, passive magnetic field sensors, stable topological superconductors that host Majorana fermions, and qubits topologically protected against decoherence. In this perspective article, the definition of these quantum anomalies is laid out, how little is known in the context of condensed matter, and how quantum anomalies are predicted to manifest as anomalous electronic, thermal, and magnetic behavior in experiments on topological quantum materials, including Weyl and Dirac semimetals. Furthermore, the importance that mechanical strain and defects will play in modifying signatures of quantum anomalies is discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Magnetic Solitons and Thickness‐Dependent Magnetization Reversal in Interconnected Helical Nanowire Arrays

By expanding magnetic nanostructures into the third dimension, it is possible to introduce new interactions and realize new forms of magnetic textures and emergent phenomena. Consequently, this unlocks new opportunities for applications in data storage, unconventional computing and sensing by utilizing 3D devices with enhanced functionalities. Connected magnetic nanowires offer a unique platform for applications such as neuromorphic computing due to their tunability and the presence of multiple transport pathways. However to realize this promise, it is necessary to further our understanding of how to locally control the magnetization in 3D, nanowire-based geometries. In this work we show the formation of magnetic domain walls, vortices, anti-vortices, and linked vortex-anti-vortex pairs in interconnected helical nanowire arrays. We show how wire diameter and 3D geometric design can control the states that form and reveal the magnetization reversal mechanism. Hence, we demonstrate this to be a highly tunable system, where the magnetization can be readily reconfigured by an external magnetic field.

3D Nanomagnetism↗
DOE OSTI2021

Evaluating Probability of Containment Effectiveness at a GCS Sites using integrated assessment modeling approach with Bayesian decision Networks

Improved scientific and engineering understanding of the behavior of geologic CO2 storage together with established regulatory framework and incentive structures raise the prospects for accelerated, large-scale deployment of this greenhouse gas emissions reduction approach. Incentive structures call for the establishment of appropriate verification and accounting approaches to support claims of the integrity of a geologic storage complex and to justify taking credit for long-term storage. In this study, we present a framework for assessing the probability of containment effectiveness over the lifetime of a geologic carbon storage site (e.g., after 70 years of injection and post-injection site performance) using forward stochastic model realizations based on site characterization data and using a monitoring-informed Bayesian network based on hypothetical detectability from surface seismic surveys over the site injection and post-injection phases. The National Risk Assessment Partnership’s open-source Integrated Assessment Model (NRAP-Open-IAM) was utilized to develop an ensemble of 10,000 a priori stochastic forecasts of CO2 containment. Those simulations were used to train the Bayesian network model to estimate the prior probabilities of the CO2 leakage mass into overlying, monitorable aquifers considering the uncertainties in the reservoir properties, permeability of potentially leaky wells and the overlying aquifers. The conditional probabilities in the Bayesian network were either learned from the NRAP-Open-IAM simulations or derived from the predefined detection thresholds for the monitoring method. Observations obtained from monitoring, over time during the site operation phases were then used to generate updated posterior probabilities of containment (and any loss from containment) in the Bayesian network by propagating the prior probabilities through the conditional probabilities. We demonstrate how to construct and use the Bayesian network for verifying the long-term storage complex effectiveness informed by monitoring based on the NRAP-Open-IAM simulations previously developed for the FutureGen 2.0 site. This approach may have relevance for stake holders to demonstrate secure geologic storage, provide a defensible, probabilistic approach to claim credit for geologic storage, and to estimate the likelihood that any fraction of the claimed credit may need to be refunded to the creditor based on available monitoring information.

Bayesian network, Risk assessment, Monitoring, car↗
DOE OSTI2022

A machine learning approach to water quality forecasts and sensor network expansion: Case study in the Wabash River Basin, United States

Abstract Midwestern cities require forecasts of surface nitrate loads to bring additional treatment processes online or activate alternative water supplies. Concurrently, networks of nitrate monitoring stations are being deployed in river basins, co‐locating water quality observations with established stream gauges. However, tools to evaluate the future value of expanded networks to improve water quality forecasts remains challenging. Here, we construct a synthetic data set of stream discharge and nitrate for the Wabash River Basin—one of the United States’ most nutrient polluted basins—using the established Agro‐IBIS and THMB models. Synthetic data enables rapid, unbiased and low‐cost assessment of potential sensor placements to support management objectives, such as near‐term forecasting. Using the synthetic data, we established baseline 1‐day forecasts for surface water nitrate at 12 cities in the basin using support vector machine regression (SVMR; RMSE 0.48–3.3 ppm). Next, we used the SVMRs to evaluate the improvement in forecast performance associated with deployment of additional nitrate sensors. We identified the optimal sensor placement to improve forecasts at each city, and the relative value of sensors at each candidate location. Finally, we assessed the co‐benefit realized by other cities when a sensor is deployed to optimize a forecast at one city, finding significant positive externalities in all cases. Ultimately, our study explores the potential for machine learning to make near‐term predictions and critically evaluate the improvement realized by expanding a monitoring network. While we use nitrate pollution in the Wabash River Basin as a case study, this approach could be readily applied to any problem where the future value of sensors and network design are being evaluated.

54 ENVIRONMENTAL SCIENCES↗