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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Electrochemical Random-Access Memory: Progress, Perspectives, and Opportunities

Non-von Neumann computing using neuromorphic systems based on analogue synaptic and neuronal elements has emerged as a potential solution to tackle the growing need for more efficient data processing, but progress toward practical systems has been stymied due to a lack of materials and devices with the appropriate attributes. Recently, solid state electrochemical ion-insertion, also known as electrochemical random access memory (ECRAM) has emerged as a promising approach to realize the needed device characteristics. ECRAM is a three terminal device that operates by tuning electronic conductance in functional materials through solid-state electrochemical redox reactions. This mechanism can be considered as a gate-controlled bulk modulation of dopants and/or phases in the channel. Early work demonstrating that ECRAM can achieve nearly ideal analogue synaptic characteristics has sparked tremendous interest in this approach. More recently, the realization that electrochemical ion insertion can be used to tune the electronic properties of many types of materials including transition metal oxides, layered two-dimensional materials, organic and coordination polymers, and that the changes in conductance can span orders of magnitude has further attracted interest in ECRAM as the basis for analogue synaptic elements for inference accelerators as well as for dynamical devices that can emulate a wide range of neuronal characteristics for implementation in analogue spiking neural networks. At its core, ECRAM shares many fundamental aspects with rechargeable batteries, where ion insertion materials are used extensively for their ability to reversibly store charge and energy. Computing applications, however, present drastically different requirements: systems will require many millions of devices, scaled down to tens of nanometers, all while achieving reliable electronic-state tuning at scaled-up rates and endurances, and with minimal energy dissipation and noise. Further, in this review, we discuss the history, basic concepts, recent progress, as well as the challenges and opportunities for different types of ECRAM, broadly grouped by their primary mobile ionic charge carrier, including Li, protons, and oxygen vacancies.

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

Electrochemistry of the NaI-AlBr 3 Molten Salt System: A Redox-Active, Low-Temperature Molten Salt Electrolyte

NaI-AlBr 3 is a very appealing low melting temperature (<100 °C), salt system for use as an electrochemically-active electrolyte. This system was investigated for its electrochemical and physical properties with focus to energy storage considerations. A simple phase diagram was generated; at >100 °C, lower NaI concentrations had two partially miscible liquid phases, while higher NaI concentrations had solid particles. Considering the fully molten regime, electrical conductivities were evaluated over 5–25 mol% NaI and 110 °C–140 °C. Conductivities of 6.8–38.9 mS cm −1 were observed, increasing with temperature and NaI concentration. Effective diffusion coefficients of the I − /I 3 − redox species were found to decrease with both increasing NaI concentration and increasing applied potential. Regardless, oxidation current density at 3.6 V vs Na/Na + was observed to increase with increasing NaI concentration over 5–25 mol%. Finally, the critical interface between the molten salt electrolyte and electrode materials was found to significantly affect reaction kinetics. When carbon was used instead of tungsten, an adsorbed species, most likely I 2 , blocked surface sites and significantly decreased current densities at high potentials. This study shows the NaI-AlBr 3 system offers an attractive, low-temperature molten salt electrolyte that could be useful to many applied systems, though composition and electrode material must be considered.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Mechanical Properties of Polyisoprene-Based Elastomer Composites

Herein we have explored the origins of mechanical reinforcement in elastomers filled with polymer-grafted nanoparticles (NPs). The brush chains are constructed from the same monomers as the polymer melt, although they have different microstructures (i.e., different amounts of trans and cis isomers). The NPs display a variety of morphologies depending on variations in the graft density of the polymers, with these morphologies hardly changing when the matrix (and the grafts) is cross-linked using dicumyl peroxide (DCP). NMR measurements show that the cross-link densities depend only on the DCP content and are independent of NP morphologies. We find that the elastic moduli of these materials are strongly dependent on the NP morphology but that the maximum reinforcement occurs when the NPs percolate, in a manner where the cores are exposed enough to have strong enthalpic interactions; these interactions could either be due to direct core–core van der Waals attractions or due to bridging interactions driven by polymers adsorbed on adjacent NPs. The nonlinear mechanical response of these materials is less sensitive to changes in NP morphology and loading. These results emphasize the important role of the exposed NP surface in determining the moduli of cross-linked elastomers. This last aspect is apparently less relevant for the corresponding uncross-linked melts filled with NPs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Hydrogen and water interactions with CrMnFeCoNi alloy from density functional theory calculations

High entropy alloys (HEAs) are a promising class of materials with remarkable mechanical and catalytic properties. Among these, the quinary CrMnFeCoNi alloy (also called “Cantor alloy”) has attracted considerable attention given its thermodynamic stability and remarkable mechanical properties under different temperatures. Given that various degradation mechanisms involve multiple contaminants, such as hydrogen and water in hydrogen embrittlement and surface poisoning, respectively, understanding their interactions with the Cantor alloy is critical for its practical applications as structural, nuclear, or hydrogen storage material. In this work, we perform first-principles calculations based on Density Functional Theory (DFT) to investigate such interactions when considering various microstructures, including bulk materials and those containing certain defects, such as grain boundaries, stacking faults, and vacancies. We also employ Global Sensitivity Analysis to identify the importance of different factors in the stability of the impurities. We find that the accuracy of the H formation energy is significantly affected by spin polarization and chemical short-range order. The study also identifies a strong tendency for hydrogen interstitials to segregate to Σ5(210)/[001] symmetric tilt grain boundary, even when H concentrations are high, suggesting that a certain type of grain boundaries acts as H sinks within the alloy. Further, this result is reinforced by the low formation energy of vacancy-hydrogen complexes, which can contain multiple hydrogen atoms. Finally, the surface reactivity analysis reveals that the adsorption energy of oxygen and hydroxyl groups is highly sensitive to the specific metal atom involved in the binding, with a clear preference for chromium atoms, which could have implications for the alloy’s oxidation and corrosion behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Scale up, Field testing, and Optimization of Nontoxic, Durable, Economical Coatings for Control of Biofouling and Corrosion (Abstract Only)

The objective of this project is the technical maturation and demonstration of a durable, economical, and nontoxic coating, Superhydrophobic Lubricant Infused Composite (SLIC), that will prevent fouling organisms from growing on marine and hydrokinetic (MHK) structures and prevent invasive mussels from growing on hydropower structures. SLIC technology was developed and patented by PNNL. It combines multiple antifouling mechanisms to provide excellent antifouling performance, durability, and low hydrodynamic drag without using toxic materials. Advanced proof-of-concept testing and demonstrations completed during a Phase 1 TCF project attracted industry interest and partnerships for this Phase 2 effort focused on maturation of a commercial product. Specific tasks and tests will shift the development emphasis to optimizing formulations, validating antifouling performance to address specific application needs, explore compatibility with other paint systems, develop a product with useful shelf life (in can), and determine curing times and effective applications methodology. Phase 2 efforts will focus upon technology transfer and commercialization of the technology with the industrial team. Industrial partners now include a coatings development specialist (Lorama), hydrophobic material manufacturer and paint developer (Dry Surface Technologies), nontoxic biodegradable lubricants manufacturer (BioBlend), and aquatic applications specialists (Prometheus Innovations, River Connectivity Systems). Engagement with the MHK device developers, the PNNL Marine and Coastal Research Laboratory (MCRL) test site in Sequim WA, Bureau of Reclamation, and Taylor Shellfish throughout the project will provide topical expertise and field test sites that will deliver crucial real-world performance data. Through this Phase 2 effort, SLIC will transition from a Technical Readiness Level (TRL) 5 to TRL 6 and long-term performance data will be acquired through demonstrations. The field test data will allow optimization of SLIC formulation to enhance performance (e.g., durability) and packaging, which are key de-risking activities for technology transfer and ultimately to the production of a viable commercial product.

13 HYDRO ENERGY↗
DOE OSTI2020

A High-Energy NASICON-Type Cathode Material for Na-Ion Batteries

Over the last decade, Na-ion batteries have been extensively studied as low-cost alternatives to Li-ion batteries for large-scale grid storage applications; however, the development of high-energy positive electrodes remains a major challenge. Materials with a polyanionic framework, such as Na superionic conductor (NASICON)-structured cathodes with formula Na x M 2 (PO 4 ) 3 , have attracted considerable attention because of their stable 3D crystal structure and high operating potential. Herein, a novel NASICON-type compound, Na 4 MnCr(PO 4 ) 3 , is reported as a promising cathode material for Na-ion batteries that deliver a high specific capacity of 130 mAh g –1 during discharge utilizing high-voltage Mn 2+/3+ (3.5 V), Mn 3+/4+ (4.0 V), and Cr 3+/4+ (4.35 V) transition metal redox. In addition, Na 4 MnCr(PO 4 ) 3 exhibits a high rate capability (97 mAh g –1 at 5 C) and excellent all-temperature performance. In situ X-ray diffraction and synchrotron X-ray diffraction analyses reveal reversible structural evolution for both charge and discharge.

25 ENERGY STORAGE↗
DOE OSTI2024

Materials Science of the Interstitial Doping Process

Particle accelerators are an increasingly important tool for frontier science. Growing initial and operating costs are a significant barrier for upgrades and for new machines. While everything matters, the major cost contributor is the SRF cavities and their ancillary facilities (e.g., cryoplant). Accordingly, the accelerator science community devotes much R&D effort to improving their energy efficiency (increased Q o ) and gradient (E acc ). While improved gradient is at the forefront for certain machines (ILC), improved quality factor has broader impact, benefitting all SRF applications. An important opportunity for accelerator science and technology to move forward arose in the course of building the LCLS-II, the second generation Linac Coherent Light Source at SLAC. At more or less the same time, researchers at Fermilab discovered that introducing a small amount of nitrogen to the niobium surface could improve the mid-range quality factor as much as three-fold. A firm resolution of how nitrogen confers its benefit attracts much current research interest. The key elements of the “nitrogen doping” process were vacuum bake at 800 °C, brief exposure to mTorr of nitrogen at several hundred degrees followed by electropolish (EP) to remove several microns from the surface to eliminate unwanted nitrides: While the process as a whole was novel, the comprising unit operations are familiar to the accelerator community. It was judged reasonable to adopt it as a cost-reduction technology for LCLS-II. Researchers carried out a program of varying process parameters and measuring performance in single-cell cavities, leading to a consensus stable protocol for the project. The transition to vendor fabrication and multiple niobium sources has presented unforeseen challenges of performance variation evidently not connected to anything that could be incorporated in a purchase specification. Moving beyond the high temperature N-doping process above, researchers reported a simplified process consisting entirely of tens of hours anneal in a N atmosphere at low temperatures (~120°C – 160°C) after 800 °C UHV bake. These processes typically yield a few-nm doped layer while the high temperature process yields at least a few to many micron doped layer. Even more recently, oxygen has been used to dope instead of nitrogen which leaves a few-µm O-alloyed layer upon vacuum annealing for 300 °C for ~3 hours. The investigation of these materials is just beginning, but the process simplification they may offer is surely attractive. The very low quantity of material that appears to be significant in the “infusion” process indicates the need for very careful control of gas species available for diffusion into the surface during low temperature treatment, both for process control and research to characterize the underlying dynamics. Oxygen alloying offers the further opportunity to utilize the decomposition of the surface native oxide as the dopant source. It is necessary to understand and (thus) manage this process. We have been supported by the Department of Energy Offices of High Energy Physics and Nuclear Physics to pursue this goal.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Ligand‐Mediated Quantum Yield Enhancement in 1‐D Silver Organothiolate Metal–Organic Chalcogenolates

X-ray free electron laser (XFEL) microcrystallography and synchrotron single-crystal crystallography are used to evaluate the role of organic substituent position on the optoelectronic properties of metal–organic chalcogenolates (MOChas). MOChas are crystalline 1D and 2D semiconducting hybrid materials that have varying optoelectronic properties depending on composition, topology, and structure. While MOChas have attracted much interest, small crystal sizes impede routine crystal structure determination. A series of constitutional isomers where the aryl thiol is functionalized by either methoxy or methyl ester are solved by small molecule serial femtosecond X-ray crystallography (smSFX) and single crystal rotational crystallography. While all the methoxy examples have a low quantum yield (0-1%), the methyl ester in the ortho position yields a high quantum yield of 22%. Here, the proximity of the oxygen atoms to the silver inorganic core correlates to a considerable enhancement of quantum yield. Four crystal structures are solved at a resolution range of 0.8–1.0 Å revealing a collapse of the 2D topology for functional groups in the 2- and 3- positions, resulting in needle-like crystals. Further analysis using density functional theory (DFT) and many-body perturbation theory (MBPT) enables the exploration of complex excitonic phenomena within easily prepared material systems.

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

CO2 Sorption in Ionic Liquid Crystals

Ionic liquid crystals (ILCs) have an affinity for certain polarizable gases such as CO2, due to their similarity to ionic liquids. We investigated three ILCs in the [1-alkyl-3-methylimidazolium+] family: n=12,14 with [BF4-] and [PF6-]: liquid crystalline analogues to ionic liquids with moderate (e.g., 1-2 mol%) CO2 solubility at atmospheric conditions: [1-butyl-3-methylimidazolium+] with [BF4-] and [PF6-]. While ionic liquids show high CO2 solubility, regenerating the CO2 is a high-energy process. Liquid crystals show low CO2 solubility but have a much lower regeneration energy requirement. Will ionic liquid crystals uptake CO2? What are the energy requirements of regenerating CO2? Conclusions: 1. C12mim BF4- shows the highest sorption at 0.12 wt% CO2 in the isotropic phase vs. C14mim BF4- with 0.097 wt% in the smectic phase. We hypothesize that the increase in chain length affects the free volume of the smectic vs. isotropic phase of C14mim BF4-, increasing the latter. 2. The change in anion from BF4- to PF6- decreased the sorption to an insignificant level more analogous to a physical adsorption onto the material in all phases. We hypothesize that the change in anion to the larger, less charge dense PF6- decreased the attractive forces between CO2 and the anion. 3. 0.12 wt% of CO2 in C12mim BF4- is small but significant. This in combination with the room temperature release of CO2 after only requiring refrigeration temperatures to occlude the CO2, making ionic liquid crystals promising materials for future.

carbon dioxide sorption↗
DOE OSTI2021

Data-Driven Strategies for Accelerated Materials Design

The ongoing revolution of the natural sciences by the advent of machine learning and artificial intelligence sparked significant interest in the material science community in recent years. The intrinsically high dimensionality of the space of realizable materials makes traditional approaches ineffective for large-scale explorations. Modern data science and machine learning tools developed for increasingly complicated problems are an attractive alternative. An imminent climate catastrophe calls for a clean energy transformation by overhauling current technologies within only several years of possible action available. Tackling this crisis requires the development of new materials at an unprecedented pace and scale. For example, organic photovoltaics have the potential to replace existing silicon-based materials to a large extent and open up new fields of application. In recent years, organic light-emitting diodes have emerged as state-of-the-art technology for digital screens and portable devices and are enabling new applications with flexible displays. Reticular frameworks allow the atom-precise synthesis of nanomaterials and promise to revolutionize the field by the potential to realize multifunctional nanoparticles with applications from gas storage, gas separation, and electrochemical energy storage to nanomedicine. In the recent decade, significant advances in all these fields have been facilitated by the comprehensive application of simulation and machine learning for property prediction, property optimization, and chemical space exploration enabled by considerable advances in computing power and algorithmic efficiency. In this Account, we review the most recent contributions of our group in this thriving field of machine learning for material science. We start with a summary of the most important material classes our group has been involved in, focusing on small molecules as organic electronic materials and crystalline materials. Specifically, we highlight the data-driven approaches we employed to speed up discovery and derive material design strategies. Subsequently, our focus lies on the data-driven methodologies our group has developed and employed, elaborating on high-throughput virtual screening, inverse molecular design, Bayesian optimization, and supervised learning. We discuss the general ideas, their working principles, and their use cases with examples of successful implementations in data-driven material discovery and design efforts. Furthermore, we elaborate on potential pitfalls and remaining challenges of these methods. Finally, we provide a brief outlook for the field as we foresee increasing adaptation and implementation of large scale data-driven approaches in material discovery and design campaigns.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Machine-learning for designing nanoarchitectured materials by dealloying

Machine learning-augmented materials design is an emerging method for rapidly developing new materials. It is especially useful for designing new nanoarchitectured materials, whose design parameter space is often large and complex. Metal-agent dealloying, a materials design method for fabricating nanoporous or nanocomposite from a wide range of elements, has attracted significant interest. Here, a machine learning approach is introduced to explore metal-agent dealloying, leading to the prediction of 132 plausible ternary dealloying systems. A machine learning-augmented framework is tested, including predicting dealloying systems and characterizing combinatorial thin films via automated and autonomous machine learning-driven synchrotron techniques. This work demonstrates the potential to utilize machine learning-augmented methods for creating nanoarchitectured thin films.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Recycled Cardboard Containers as a Low Energy Source for Cellulose Nanofibrils and Their Use in Poly(l-lactide) Nanocomposites

Cellulose nanomaterials have attracted a great deal of interest as sustainable alternatives to nonrenewable or fossil fuel-derived materials, particularly in composite applications. Cellulose nanofibrils (CNF) are most often derived from wood sources through energy-intensive and costly mechanical fibrillation processes. Here, recycled cardboard, referred to as old corrugated cardboard (OCC), was investigated as an alternate CNF source. OCC is a recycled material that can be obtained at one-tenth the cost of the commonly used bleached softwood Kraft pulp and can be refined to similar levels with nearly one-half of the energy consumption. Additionally, the distinct composition and morphology of OCC-derived CNF provides a more favorable fiber–matrix interface and better reinforcement capabilities of the cellulose nanofibrils in polymer matrices, displaying an over 70% increase in tensile modulus at a loading of 40 wt % with no decrease in tensile strength. When paired with biobased poly(l-lactide) (PLLA), OCC-derived CNF is proven to be an attractive low-cost and low-energy reinforcing agent for sustainable, high performance nanocomposites.

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

Experimental Protocols for Studying Organic Non-aqueous Redox Flow Batteries

We report that Redox flow batteries (RFBs) are promising devices for grid-scale energy storage due to the decoupling of power and energy, which can be independently scaled by the electrode area and storage tank size, respectively. To date, only aqueous RFBs, such as the vanadium RFB, have been implemented commercially. Nevertheless, the limited energy densities and high-cost materials may preclude their wider market penetration. Organic non-aqueous redox-flow batteries (O-NRFBs), which utilize redox-active organic molecules (ROMs), have been offered as an attractive alternative. Many possible advantages include the use of earth-abundant elements (C, H, N, O, S, F), wherein the ROMs can be prepared from low-cost and sustainable materials. Additionally, a large variety of electroactive moieties are accessible as building blocks, providing a synthetic platform to tune the properties of ROMs through rational design. As a consequence, the development of novel ROMs has attracted researchers with diverse backgrounds, prompting remarkable innovations in the past decade. However, consistency in experimental protocols (e.g., electrochemical methods, cycling stability, experimental conditions) has not coincided with this uptick in research, leading to sometimes ambiguous and incomparable results. This is further convoluted by the complexity innate to battery development, such as cell design, detection, and characterization of reactions and active components. The O-NRFB application imposes stringent requirements on the physical or/and chemical processes involved in electrochemical cycling. Yet such considerations are often overlooked. Further, while quantum mechanical calculations provide a convenient tool for evaluating and selecting ROM candidates, this simulation is not always performed. Thus, in this Energy Focus, we detail a means to standardize experimental protocols for studies of O-NRFBs and suggest practices to facilitate fundamental understanding and development of ROMs.

25 ENERGY STORAGE↗
DOE OSTI2023

Optically Excited Lasing in a Cavity‐Based, High‐Current‐Density Quantum Dot Electroluminescent Device

Abstract Laser diodes based on solution‐processable materials can benefit numerous technologies including integrated electronics and photonics, telecommunications, and medical diagnostics. An attractive system for implementing these devices is colloidal semiconductor quantum dots (QDs). The progress towards a QD laser diode has been hampered by rapid nonradiative Auger decay of optical‐gain‐active multicarrier states, fast device degradation at high current densities required for laser action, and unfavorable competition between optical gain and optical losses in a multicomponent device stack. Here we resolve some of these challenges and demonstrate optically excited lasing from fully functional high‐current density electroluminescent (EL) devices with an integrated optical resonator. This advance has become possible due to excellent optical gain properties of continuously graded QDs and a refined device architecture, which allows for highly efficient light amplification in a thin, EL‐active QD layer.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Leveraging Exchange Kinetics for the Synthesis of Atomically Precise Porous Catalysts

Metal-organic frameworks (MOFs) have attracted significant attention as porous catalyst platforms due to the synthetic modularity of these materials and the diversity of lattice-confined catalytic active sites that are readily embedded within periodic crystalline frameworks. MOFs offer platforms to heterogenize molecular catalysts, stabilize novel coordination motifs, and leverage confinement effects in catalysis. Crystallinity allows diffraction-based methods to be employed in the characterization of these catalysts. Access to crystalline MOFs typically requires reversible construction of the metal-ligand (M-L) bonds that connect the SBUs, which provides a mechanism to anneal defects during crystallization. While the required M-L bond reversibility is often promoted by synthesis at elevated temperature, access to crystalline materials based on either transition metals with characteristic slow exchange kinetics or highly basic donor ligands remains a synthetic challenge. Here in this paper, we highlight synthetic strategies that leverage M-L exchange kinetics to access MOFs based on kinetically inert ions and extensions of these strategies to the assembly of atomically precise multimetallic materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Understanding the Active Site Structures and Achieving Catalytic Activity Tuning of Atomically Dispersed FeN 4 Sites for Oxygen Reduction Reaction

Atomically dispersed Fe–—N—C catalysts with high oxygen reduction reaction (ORR) activity have attracted great attention since the last decade. Due to comparable ORR activity and low material cost, they are promising platinum group metal (PGM)-free catalysts that can replace the commercialized Pt/C materials; furthermore, it can facilitate the efficiency of the fuel cell technologies and mitigate dependence on fossil fuels. Great advancements have been made to experimentally optimize the synthesis approach of the Fe–—N—C catalysts, enhance the ORR activity, and improve the catalyst stability. Similarly, recent theoretical studies also provide enriched understanding of the active site structures, properties, and reaction mechanisms. In this review, discussions are made upon utilizing combined experimental and computational spectroscopy to reveal the active site structures, employing mechanistic studies to investigate reaction thermodynamics and kinetics, as well as developing scaling relationships to assist the design and development of future PGM-free catalyst materials. Furthermore, recent advances in studying Fe–—N—C catalysts utilizing electrified surface models and explicit solvation models are also discussed. Not only can these aspects improve the accuracy of theoretical simulation and predictions but also deepen the understanding of the catalyst properties and reaction mechanisms under the effect of surface charges and solvent molecules.

Fe single-atom catalysts↗
DOE OSTI2019

Machine learning maximized Anderson localization of phonons in aperiodic superlattices

Nanostructuring materials to achieve ultra-low lattice thermal conductivity has proven to be extremely attractive for numerous applications such as thermoelectric energy conversion. Anderson localization of phonons due to aperiodicity can reduce thermal conductivity in superlattices, but the lower limit of thermal conductivity remains elusive due to the prohibitively large design space. In this work, we demonstrate that an intuition-based manual search for aperiodic superlattice structures (random multilayers or RMLs) with the lowest thermal conductivity yields only a local minimum, while a genetic algorithm (GA) based approach can efficiently identify the globally minimum thermal conductivity by only exploring a small fraction of the design space. Our results show that this minimum value occurs at an average RML period that is, surprisingly, smaller than the period corresponding to the minimum SL thermal conductivity. Interestingly, above this critical period, scattering of incoherent phonons at interfaces is less, whereas below this period, the room for randomization becomes less, thus putting more coherent phonons out of Anderson localization and causing increased thermal conductivity. Moreover, the lower limit of the thermal conductivity occurs at a moderate rather than maximum randomness of the layer thickness. Our machine learning approach demonstrates a general process of exploring an otherwise prohibitively large design space to gain non-intuitive physical insights.

42 ENGINEERING↗
DOE OSTI2024

Synchrotron small-angle X-ray scattering technique for battery electrode study

Structure dependent stability is a concern for the achievement of high energy density electrode with long cycling lifetime, especially for alloying-type and conversion-type anodes. Substantial alterations in volume upon discharge-discharge process leads to particle pulverization and continuous consumption of electrolyte. Moreover, the nucleation and growth mechanism of Li 2 O and Li 2 S, which determines the rate performance of Li-O 2 and Li-S batteries, are still understudy. Microstructure characterization techniques have been applied to disclose the structural changes of active material at different charge/discharge states. Synchrotron small-angle X-ray scattering (SAXS) attracts considerable attention because of the high flux, high time resolution and nondestructive characteristics. In addition, SAXS patterns provide statistics structural information of electrode at micrometer scale. The commonly used coin cell with punched holes simplifies the application of in situ/operando SAXS measurement. Here, this review discusses the research about the SAXS technique in the characterization of electrode in different batteries.

25 ENERGY STORAGE↗