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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 OSTI2022

Programming Function via Soft Materials (PFvSM) (Final Report)

The PFvSM cluster at the University of Illinois greatly deepened the science of soft materials and expanded the means for embedding within them unprecedented functionalities. We pioneered a mesoscopic approach to materials design that combined leading competencies in fundamental experimental and theoretical soft matter science and fabrication that powerfully establishes equilibrium and nonequilibrium assembly of novel and complex building blocks as a preeminent contributor to progress in materials chemistry. Our cluster’s vision was an integrated program of work centered on soft matter science with the ultimate goal of impacting important energy technologies. As elementary units we employed function-encoded colloids, nanoparticles, large mesh fibrillar gels, deterministically fabricated networks and hybrid objects. These materials were employed as building blocks for diverse model systems that allowed fundamental soft matter principles of wide relevance to be established. Their assembly into materials with useful functional behavior provided new approaches to challenging problems in basic energy science including energy harvesting, transport and storage. To achieve these goals the cluster brought together a team of recognized world-leaders in materials synthesis and processing, in-situ characterization, theory and modeling, and materials design, integration and fabrication

36 MATERIALS SCIENCE↗
DOE OSTI2018

FY2017 annual report: Roll-to-Roll Advanced Materials Manufacturing DOE Laboratory Consortium Project

The following report provides a description of the program structure and technical accomplishments made during FY 2017 to overcome challenges for expanding use of R2R technologies and processing for clean energy applications. Technologies are under development that enable enhanced manufacturing of battery electrodes, fuel cells and water separation membranes that take advantage of advancements in new functional materials. Data mining, visualization, modeling and simulation for the materials, technologies and processes being developed allow for improvements in R2R manufacturing applications. This report documents the research conducted by four DOE national laboratories as a consortium in collaboration with industry partnerships. The research is directly applicable to AMM strategies that apply the National Science and Technology Council’s Materials Genome Initiative (NSTC 2011) approach to enhance the performance of battery, fuel cell and water membrane materials. This effort supports building the foundation of technologies, processes and a U.S. manufacturing base that will enable an order of magnitude in shorter process development cycles with the pathway for initial commercialization within months instead of years.

36 MATERIALS SCIENCE↗
DOE OSTI2019

High performance bulk thermoelectric materials and flexible transparent electrodes. Final Technical Report

This is the final report of the grant for the period from January 15, 2013 to November 14, 2018. During the 6 years, we have carried out a number of research projects and have published 97 peer-reviewed journal papers in Nature Nanotechnology, Nature Communications, Energy & Environmental Science, PNAS, NanoLetters, Nano Energy, Advanced Functional Materials, Advanced Electronic Materials, Chemistry of Materials, etc. Among them, 8 are highly cited and have generated a significant impact to the fields of thermoelectrics, flexible transparent electronics, water splitting for hydrogen generation, enhanced oil recovery, etc. More than 20 invention disclosures have been filed, which are being processed by the US patent and trade office.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Hamiltonians and order parameters for crystals of orientable molecules

Many modern functional materials exhibit microscopic degrees of freedom that are difficult to describe mathematically or do not conform to conventional models in solid state physics. In this paper, we consider crystals containing orientable molecular species, which encompass the class of promising photovoltaic materials CH 3 NH 3 PbX 3 . Abstracting these materials as crystals of orientable rigid rotors, we develop an effective Hamiltonian that expresses the crystal potential energy in terms of collective orientations of interacting rigid rotors. The approach is motivated by the cluster expansion framework from alloy theory and is appropriate for describing both chiral and achiral molecules. This framework utilizes a quaternion parametrization of molecular orientation and makes full use of the symmetry both of the rotors and of the crystal in order to constrain the functional form of the final Hamiltonian expression. The resulting Hamiltonian is compact, systematically improvable, and is suitable for Monte Carlo or molecular dynamics simulation. We apply this formalism to CH 3 NH 3 PbI 3 and report symmetry-adapted basis functions that can be used to construct order parameters or Hamiltonians that describe orientational correlation of methylammonium ions in hybrid organic-inorganic halide perovskite materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Design of Heterogeneous Chalcogenide Nanostructures with Pressure-Tunable Gaps and without Electronic Trap States

Heterogeneous nanostructures, such as quantum dots (QDs) embedded in solid matrices or core–shell nanoparticles, are promising platforms for a wide variety of applications, including phosphors with increased quantum yield, photocatalysis, and solar energy conversion. However, characterizing and controlling their interfacial morphology and defects, which greatly influence their electronic properties, have proven difficult in numerous cases. Here we carried out atomistic calculations on chalcogenide nanostructured materials, i.e., PbSe QDs in CdSe matrices and CdSe embedded in PbSe, and we established how interfacial and core structures affect their electronic properties. In particular, we showed that defects present at interfaces of PbSe nanoparticles and CdSe matrices give rise to detrimental intragap states, degrading the performance of photovoltaic devices. Instead, the electronic gaps of the inverted system (CdSe dots in PbSe) are clean, indicating that this material has superior electronic properties for solar applications. In addition, our calculations predicted that the core structure of CdSe and in turn its band gap may be tuned by applying pressure to the PbSe matrix, providing a means to engineering the properties of new functional materials.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
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 OSTI2025

Uncovering multiscale structure-property correlations via active learning in scanning tunneling microscopy

Atomic arrangements and local sub-structures fundamentally influence emergent material functionalities. These structures are conventionally probed using spatially resolved studies and the property correlations are deciphered by a researcher based on sequential explorations, thereby limiting the efficiency and scope. Here we demonstrate a multi-scale Bayesian deep-learning based framework that automatically correlates material structure with its electronic properties using scanning tunneling microscopy (STM) measurements in real-time. Its predictions are used to autonomously direct exploration toward regions of the sample that optimize a given material property. This method is deployed on a low-temperature ultra-high vacuum STM to understand the structure-property relationship in a europium-based semimetal, EuZn 2 As 2 , a promising candidate relevant to magnetism-driven topological phenomena. The framework employs a sparse-sampling approach to efficiently construct the scalar-property space using minimal measurements, about 1–10% of the data required in standard hyperspectral methods. Moreover, we formulate the problem hierarchically across length scales, implementing autonomous workflow to locate mesoscopic and atomic structures that correspond to a target material property. This framework offers the choice to design scalar-property from the spectroscopic data to steer sample exploration. Our findings reveal correlations of the electronic properties unique to surface terminations, local defect density, and point defects.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Theoretical insight into thermodynamics of particle-based crystallization

Crystallization process often does not follow the monomer-by-monomer addition pathway, as described by classical nucleation theory. Instead, initial step may involve the formation of larger building blocks, such as crystalline or amorphous nanoparticles, droplets, clusters, complexes or oligomers, which subsequently undergo assembly into a crystal. These multistep crystallization processes are ubiquitous in mineral formation and biomineralization. In materials synthesis utilizing non-classical crystallization pathways is particularly attractive as the restriction on which crystalline faces can grow is lifted in a multistep crystallization process adding to the versatility of materials architectures that can be obtained. Predicting the outcomes of non-classical crystallization through the understanding of the control parameters influencing crystallization pathways is an important and challenging task essential for utilizing the full potential of non-classical crystallization in the design of functional materials. Here, the current status of the development of a predictive theoretical framework for modeling non-classical crystallization is reviewed.

Sushko, Maria L.↗
DOE OSTI2020

Predicting synthesizable multi-functional edge reconstructions in two-dimensional transition metal dichalcogenides

Abstract Two-dimensional (2D) transition metal dichalcogenides (TMDCs) have attracted tremendous interest as functional materials due to their exceptionally diverse and tunable properties, especially in their edges. In addition to the conventional armchair and zigzag edges common to hexagonal 2D materials, more complex edge reconstructions can be realized through careful control over the synthesis conditions. However, the whole family of synthesizable, reconstructed edges remains poorly studied. Here, we develop a computational approach integrating ensemble-generation, force-relaxation, and electronic-structure calculations to systematically and efficiently discover additional reconstructed edges and screen their functional properties. Using MoS 2 as a model system, we screened hundreds of edge-reconstruction to discover over 160 reconstructed edges to be more stable than the conventional ones. More excitingly, we discovered nine new synthesizable reconstructred edges with record thermodynamic stability, in addition to successfully reproducing three recently synthesized edges. We also find our predicted reconstructed edges to have multi-functional properties—they show near optimal hydrogen evolution activity over the conventional edges, ideal for catalyzing hydrogen-evolution reaction (HER) and also exhibit half-metallicity with a broad variation in magnetic moments, making them uniquely suitable for nanospintronic applications. Our work reveals the existence of a wide family of synthesizable, reconstructed edges in 2D TMDCs and opens a new materials-by-design paradigm of ‘intrinsic’ edge engineering multifunctionality in 2D materials.

Hu, Guoxiang (ORCID:0000000329428564)↗
DOE OSTI2019

Machine Learning for Computational Heterogeneous Catalysis

Abstract Big data and artificial intelligence has revolutionized science in almost every field – from economics to physics. In the area of materials science and computational heterogeneous catalysis, this revolution has led to the development of scientific data repositories, as well as data mining and machine learning tools to investigate the vast materials space. The goal of using these tools is to establish a deeper understanding of the relations between materials properties and activity, selectivity and stability – the important figures of merit in catalysis. Based on these insights, catalyst design principles can be established, which hopefully lead us to discover highly efficient catalysts to solve pressing issues for a sustainable future and the synthesis of highly functional materials, chemicals and pharmaceuticals. The inherent complexity of catalytic reactions quests for machine learning methods to efficiently navigate through the high‐dimensional hyper‐surfaces in structure optimization problems to determine relevant chemical structures and transition states. In this review, we show how cutting edge data infrastructures and machine learning methods are being used to address problems in computational heterogeneous catalysis.

Schlexer Lamoureux, Philomena↗
DOE OSTI2025

Multiplexing core & sheath extrusion system development for additive manufacturing for inner-bead multi-material capability

Single-feed polymer extruders are widely used in large-format additive manufacturing (AM) systems; however, the increasing demand for multi-material functionality within a single part has driven significant innovation in this field. One approach involves robotic pick-and-place operations, while another explores mechanical switching of feed lines during extrusion. Although robotic pick-and-drop systems offer flexibility, they introduce longer layer times during material changes, which can negatively affect the structural integrity of the part. On the other hand, mechanical feed switching causes delays in material transitions, as the existing material must be flushed before the new material emerges from the nozzle. This poses particular challenges for smaller or more intricate parts. In this study we are developing a unique multiplexing extrusion system with core & sheath nozzle that combines two extruders via co-extrusion. This allows for a unique inside and outside inner-bead (i.e., within the same bead) multi-material capability. We believe that this technology will allow for combining neat and filled materials, ductile and stronger materials, and many other combinations to address the problems aforementioned above and disrupt the AM technology creating new opportunities and opening application areas.

Tekinalp, Halil [ORNL]↗
DOE OSTI2018

Guanidinium-Based Ionic Covalent Organic Framework for Rapid and Selective Removal of Toxic Cr(VI) Oxoanions from Water

Ionic covalent organic frameworks make up an emerging class of functional materials in which the included ionic interfaces induce strong and attractive interactions with ionic species of the opposite charge. Here, the strong and selective binding forces between the confined diiminoguanidinium groups in the framework and tetrahedral oxoanions have led to unparalleled effectiveness in the removal of the toxic chromium(VI) pollutant from aqueous solutions. Lastly, the new functional framework can take up from 90 to 200 mg/g of chromium(VI), depending on the solution pH, and is capable of decreasing the chromium(VI) concentration in water from 1 ppm to 10 ppb within minutes (an order of magnitude below the current U.S. Environmental Protection Agency maximum contaminant level of 100 ppb), demonstrating superior properties among known ion exchange materials and natural sorbents.

36 MATERIALS SCIENCE↗
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 OSTI2017

Finding a Needle in the Haystack: Identification of Functionally Important Minority Phases in an Operating Battery

The in-depth understanding of the minority phases’ roles in functional materials, e.g., batteries, is critical for optimizing the system performance and the operational efficiency. Although the visualization of battery electrode under operating conditions has been demonstrated, the development of advanced data-mining approaches is still needed in order to identify minority phases and to understand their functionalities. The present study uses nanoscale X-ray spectromicroscopy to study a functional LiCoO 2 /Li battery pouch cell. The data-mining approaches developed herein were used to search through over 10 million X-ray absorption spectra that cover more than 100 active cathode particles. Two particles with unanticipated chemical fingerprints were identified and further analyzed, providing direct evidence and valuable insight into the undesired side reactions involving the cation dissolution and precipitation as well as the local overlithiation-caused subparticle domain deactivation. As a result, the data-mining approach described in this work is widely applicable to many other structurally complex and chemically heterogeneous systems, in which the secondary/minority phases could critically affect the overall performance of the system, well beyond battery research.

25 ENERGY STORAGE↗
DOE OSTI2024

Copper and bismuth-based sorbent characterization in simulated iodine off-gas streams

The effective capture of volatile radioiodine, a fission product present in used nuclear fuel (UNF), is of paramount importance for development of used fuel reprocessing schemes to prevent release of radioiodine during unit operations and to meet regulatory standards for air emissions. A well-studied method for iodine capture in off-gas streams is the use of silver-functionalized zeolite phases (AgZ), which exploit chemisorption of I to Ag. Advances into other Ag-functionalized materials, including aerogels and metal organic frameworks (MOFs), are underway [1]. Additional metals with the capability to chemisorb iodine, including Cu, Bi, and Sn, [1] are being evaluated as alternatives to Ag for potential applicability to iodine management in off-gas systems. The design of novel functionalized sorbents with Cu and Bi, including composites with metal particles embedded in PAN substrates [2] and composites with metal sulfides embedded in PAN [3], is an ongoing area of study for improved iodine capture. Previously reported work on novel PAN-based metal sorbents has provided the synthesis, characterization, and iodine capture efficiency of this new class of sorbent. Specifically, the metal sulfide PAN composites are found to be easy to produce and reproduce, as well as having a high iodine loading potential under static conditions [3]. Due to the favorable testing previously performed with metal sulfide PAN composites, further testing into the performance of these composites under gas streams containing I2(g) in combination with NO2(g) and H2O(g) is needed. Humid streams of NO2(g) may arise from dissolver off-gas streams, when used fuel is dissolved in HNO3(aq) [4]. NO2(g) has been found to reduce AgZ sorption capacity for I because of oxidation of Ag, the chemisorbing agent, to Ag2O [5]. It follows that performance evaluation of novel sorbents under highly oxidizing conditions such as NO2(g) streams is critical. Therefore, the objective of this study is to determine the effect of flowing NO2(g) and H2O(g) streams on iodine sorption capacity and sorbent performance. This work utilizes custom-built gas handling capabilities for sorbent exposure along with solid-state characterization techniques to assess the physical and chemical properties of sorbents before and after exposure.

copper, bismuth, iodine capture, iodine sorbent, p↗
DOE OSTI2012

Effect of sputtered lanthanum hexaboride film thickness on field emission from metallic knife edge cathodes

We report experiments and analysis of field emission from metallic knife-edge cathodes, which are sputter-coated with thin films of lanthanum hexaboride (LaB{sub 6}), a low-work function material. The emission current is found to depend sensitively on the thickness of the LaB{sub 6} layer. We find that films thinner than 10 nm greatly enhance the emitted current. However, cathodes coated with a thicker layer of LaB{sub 6} are observed to emit less current than the uncoated metallic cathode. This result is unexpected due to the higher work function of the bare metal cathode. We show, based on numerical calculation of the electrostatic potential throughout the structure, that the external (LaB{sub 6}/vacuum) barrier is reduced with respect to uncoated samples for both thin and thick coatings. However, this behavior is not exhibited at the internal (metal/LaB{sub 6}) barrier. In thinly coated samples, electrons tunnel efficiently through both the internal and external barrier, resulting in current enhancement with respect to the uncoated case. In contrast, the thick internal barrier in thickly coated samples suppresses current below the value for uncoated samples in spite of the lowered external barrier. We argue that this coating thickness variation stems from a relatively low (no higher than 10{sup 18} cm{sup -3}) free carrier density in the sputtered polycrystalline LaB{sub 6}.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Direct observation and analysis of yolk-shell materials using low-voltage high-resolution scanning electron microscopy: Nanometal-particles encapsulated in metal-oxide, carbon, and polymer

Nanometal particles show characteristic features in chemical and physical properties depending on their sizes and shapes. For keeping and further enhancing their features, the particles should be protected from coalescence or degradation. One approach is to encapsulate the nanometal particles inside pores with chemically inert or functional materials, such as carbon, polymer, and metal oxides, which contain mesopores to allow permeation of only chemicals not the nanometal particles. Recently developed low-voltage high-resolution scanning electron microscopy was applied to the study of structural, chemical, and electron state of both nanometal particles and encapsulating materials in yolk-shell materials of Au@C, Ru/Pt@C, Au@TiO{sub 2}, and Pt@Polymer. Progresses in the following categories were shown for the yolk-shell materials: (i) resolution of topographic image contrast by secondary electrons, of atomic-number contrast by back-scattered electrons, and of elemental mapping by X-ray energy dispersive spectroscopy; (ii) sample preparation for observing internal structures; and (iii) X-ray spectroscopy such as soft X-ray emission spectroscopy. Transmission electron microscopy was also used for characterization of Au@C.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Tuning Ultrafast Photoinduced Strain in Ferroelectric-Based Devices

Ferroelectric materials exhibit coupled degrees of freedom and possess a switchable electric polarization coupled to strain, making them good piezoelectrics and enabling numerous devices including nonvolatile memories, actuators, and sensors. Moreover, novel photovoltaic effects are encountered through the interplay of electric polarization with the material optical properties. Consequently, light-induced deformation in ferroelectrics, or photostriction, combining photovoltaic and converse piezoelectric effects, is under investigation in the quest for multifunctional materials. Using time-resolved X-ray diffraction, the first control of ultrafast photoinduced strain is demonstrated through in situ tuning of the polarization state in ferroelectric-based devices. Both the magnitude and the sign of the photoinduced strain strongly depend on the transient photoinduced change of the internal electric field in the ferroelectric layer, and can be actively engineered to achieve two distinct remanent photostrictive responses. These results provide fundamental insight into light–matter interaction in ferroelectrics and exciting new avenues for materials functionality engineering.

36 MATERIALS SCIENCE↗