Extraction of Critical Electronic Materials from Steelmaking Wastes
Not provided.
Metallurgy & Metallurgical Engineering↗
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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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Enabling high-porosity porous silicon as an electronic material
Not Available
Sun, Xiao (ORCID:0000000257700943)↗
Ion Tunable Electronic Materials Systems for Neuromorphic Computing.
Abstract not provided.
Talin, Albert↗
Presentation submission for Electronic Materials Conference
Explore the source record for details and available documents.
Peterson, Amelia Harriet↗
On the Prospect of Chemically Transferable Coarse-Grained Electronic Models for Soft Materials
Electronic coarse-graining (ECG) methods predict quantum-mechanical electronic properties directly from coarse-grained (CG) molecular configurations, enabling electronic predictions at mesoscale length scales. Here, we present a diagnostic assessment of the feasibility of chemically transferable ECG models across a broad polymer-relevant chemical space using all-atom, united-atom, and Martini-scale representations. While high-resolution ECG models achieve near-quantitative accuracy, we show that chemically transferable ECG at the Martini resolution fails because the CG force field does not sample the same configurational distribution of local molecular structure as that underlying the DFT-parameterized ECG model. We demonstrate that our proposed Element-Count-Label (ECL) representation, which augments Martini beads with explicit stoichiometric data, significantly improves chemical generalization across diverse polymer chemistries. However, we find that even with improved chemical resolution, the model cannot recover electronic property distributions that are absent from the configurational space sampled by the CG force field. These results demonstrate that chemically transferable ECG requires future Martini-like force fields to explicitly preserve quantum chemistry–compatible local molecular structure in addition to thermodynamic and structural fidelity.
Kidder, Katherine M [Department of Chemistry; Univ↗
Frontal polymerization of thermosets to enable vacuum-formed structural electronics
Material design and accessible manufacturing are often at odds with each other, calling for creative solutions to adapt high-performance materials to available processes. This challenge is represented well by in-mold electronics, an innovative approach to the manufacture of 3D circuitry and electronic components that offers game-changing advantages. In-mold electronics relies on vacuum forming processes, which are historically limited to thermoplastics. Extending these methods to include thermosets would enable manufacturing of robust components with desirable properties. Here, we provide a solution to make thermoset materials amenable to vacuum forming. Specifically, an ambient polymerization is used to transition a liquid monomeric solution to an elastomeric gel. These free-standing gels can then be vacuum formed, and the reaction can be completed via frontal polymerization. Thermoset materials produced with this method have properties that provide benefits over traditionally employed thermoplastic substrates and enable 3D device integration into environmentally demanding architectural, automotive, and extraterrestrial structures.
Fowler, Hayden Elise [Sandia National Laboratories↗
Collective Energy Transport of Excitons in Two-dimensional Materials
Electronic thermal transport and thermoelectric measurements are pursued in this project to obtain unique insights into the unusual collective energy transport behaviors in two-dimensional (2D) heterostructures. Electronic thermal transport and thermoelectric measurements are essential techniques for characterizing bulk superconductors by probing the heat-carrying quasi-particles. Thermoelectric and electronic thermal transport measurements are expanded in this work beyond bulk systems to probe interactions among electrons, holes, and phonons in 2D heterostructures. In one experiment, a microbridge platform is advanced to demonstrate field-effect resistive-thermometry measurements of the electronic thermal conductivity of graphene heterostructures. Together with first principles theoretical calculations and analytical models, the experimental results suggest that tunable electron coupling with flexural phonons provides a knob to control quantum matters in graphene heterostructures with broken reflection symmetry. In another experiment, the Seebeck coefficient (S) is measured to probe interlayer interactions in electron-hole bilayers that are predicted to give rise to the emergence of a variety of correlated states. As a measure of the entropy, the measured S reveals the signature of electric injection of interlayer excitons in transition metal dichalcogenide (TMD) structures.
36 MATERIALS SCIENCE↗
High-Resolution Imaging of Unstained Polymer Materials
Electron microscopy has played an important role in polymer characterization. Traditionally, electron diffraction is used to study crystalline polymers while transmission electron microscopy is used to study microphase separation in stained block copolymers and other multiphase systems. We describe developments that eliminate the barrier between these two approaches - it is now possible to image polymer crystals with atomic resolution. The focus of this Review is on high-resolution imaging (30 Å and smaller) of unstained polymers. Recent advances in hardware allow for capturing numerous (as many as 105) low-dose images from an unperturbed specimen; beam damage is a significant barrier to high-resolution electron microscopy of polymers. Machine-learning-based software is then used to sort and average the images to retrieve pristine structural information from a collection of noisy images. Acknowledging the heterogeneity in polymer samples prior to averaging is essential. Molecular conformations in a wide range of amphiphilic block copolymers, polymerized ionic liquids, and conjugated polymers can be gleaned from two-dimensional projections (2D), three-dimensional (3D) tomograms, and four-dimensional (4D) scanning transmission electron microscopy (STEM) data sets where 2D diffraction patterns are taken as a function of position. Some methods such as phase contrast STEM have been used to image closely related materials such as metal-organic frameworks but not polymers. With improvements in hardware and software, such methods may soon be applied to polymers. Our goal is to provide a comprehensive understanding of the strategies toward the high-resolution imaging of radiation sensitive polymer materials at different length scales.
36 MATERIALS SCIENCE↗
Predicting Elastic Properties of Materials from Electronic Charge Density Using 3D Deep Convolutional Neural Networks
Materials representation plays a key role in machine learning-based prediction of materials properties and new materials discovery. Currently both graph and three-dimensional (3D) voxel representation methods are based on the heterogeneous elements of the crystal structures. Here, we propose to use electronic charge density (ECD) as a generic unified 3D descriptor for materials property prediction with the advantage of possessing close relation with the physical and chemical properties of materials. We developed an ECD-based 3D convolutional neural networks (CNNs) for predicting the elastic properties of materials, in which CNNs can learn effective hierarchical features with multiple convolving and pooling operations. Extensive benchmark experiments over 2170 $Fm\bar3m$ face-centered-cubic materials show that our ECD-based CNNs can achieve good performance for elasticity prediction. Especially, our CNN models based on the fusion of elemental Materials-Agnostic Platform for Informatics and Exploration features and ECD descriptors achieved the best fivefold cross-validation performance. More importantly, we showed that our ECD-based CNN models can achieve significantly better extrapolation performance when evaluated over nonredundant data sets, where there are few neighbor-training samples around test samples. As an additional validation, we evaluated the predictive performance of our models on 329 materials of space group $Fm\bar3m$ by comparing to density functional theory calculated values, which shows a better prediction power of our model for bulk modulus than shear modulus. Because of the unified representation power of ECD, it is expected that our ECD-based CNN approach can also be applied to predict other physical and chemical properties of crystalline materials.
36 MATERIALS SCIENCE↗
Precision Agriculture using Networks of Degradable Analytical Sensors (PANDAS) (Final Technical Report)
Precision agriculture, where sensing of soil, environment and crop conditions are used to precisely synchronize inputs (such as water and fertilizer) to crop needs enhances input use efficiency. This can improve yields and farm profitability while mitigating environmental losses, improving soil carbon content and substantially decreasing energy use for food, feed and fuel crops. Unfortunately, farmers are not yet able to harness the full potential of these management technologies as there is a lack of available management information, and there is therefore a need for sensors that are able to economically measure spatio-temporal variability in soil and crop properties of extremely heterogeneous farm fields precisely at high resolution and at low cost. Real-time, in-situ monitoring of agricultural soil conditions is today carried out using devices that limit the total number of nodes that can be used economically to typically one per acre or less. Higher spatio-temporal resolution sensing would enable more precise agricultural input optimization, with significant benefits to the farmer and the environment. In order to address this issue, this project focused on developing additively manufactured, biodegradable, soil sensors with predicted costs of < $\$$1 per unit to monitor crop inputs (such as water and fertilizer) that predictably, harmlessly degrade away into the soil when no longer needed. These sensor nodes should be easy to place, accurately and continuously monitor soil and crop conditions for an entire season, be read remotely using existing farm equipment, require no ongoing maintenance, not impede farm operations and produce no persistent waste. This approach could enable a >100× increase in information density over current solutions for precision farming of row and other crops, and lead to significant reductions in input energy use and provide increased yield for biofuel crops. Over the course of this project the team at the University of Colorado Boulder, University of California Berkeley, and Colorado State University/Kansas State University investigated a wide range of printable biodegradable electronic materials and sensor designs for determining soil moisture and soil nitrate concentration. These efforts expanded the available materials set for printed soil degradable electronic materials, particularly for conductors, enabling high conductivity and stability. Printed soil moisture and nitrate sensors with suitable sensitivity and selectivity were developed and characterized. Low power and passive wireless electronic systems were integrated with the soil sensors, and testing was carried out with completed sensors to understand their functionality under agricultural conditions. Additionally, other sensor types enabled by the biodegradable materials set created during this project, such as soil microbial activity sensors, were also developed and demonstrated. Project outputs include 10 peer reviewed publications, 4 patent applications, 21 technical presentations, 3 PhD thesis, 10 media reports, 8 additional grants worth over $\$$6M, and the formation of 3 start-up companies.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Using radioactive material to evaluate decontamination of contaminated electronics
Electronic materials are used everywhere and can get easily contaminated by their use in the field/laboratory. The goal of this project was to use radioactive material to track the effectiveness of a cleaning procedure using an off-the-shelf cleaning gel. Radioactive potassium bromide (KBr) was used as a model contaminant in four contamination scenarios to gauge the effectiveness of a cleaning gel in the decontamination of contaminated raspberry pi’s. Finally, the investigated decontamination technique was found to be 75–97% effective in removing contamination from the tested electronic devices. 95% of the contaminated electronic devices retained their functionality post-decontamination.
38 - RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCL↗
Benzoimidazolium-derived dimeric and hydride n-dopants for organic electron-transport materials: impact of substitution on structures, electrochemistry, and reactivity
1,3-Dimethyl-2,3-dihydrobenzo[ d ]imidazoles, 1H , and 1,1',3,3'-tetramethyl-2,2',3,3'-tetrahydro-2,2'-bibenzo[ d ]imidazoles, 1 2 , are of interest as n-dopants for organic electron-transport materials. Salts of 2-(4-(dimethylamino)phenyl)-4,7-dimethoxy-, 2-cyclohexyl-4,7-dimethoxy-, and 2-(5-(dimethylamino)thiophen-2-yl)benzo[ d ]imidazolium ( 1g–i + , respectively) have been synthesized and reduced with NaBH 4 to 1gH , 1hH , and 1iH , and with Na:Hg to 1g 2 and 1h 2 . Their electrochemistry and reactivity were compared to those derived from 2-(4-(dimethylamino)phenyl)- ( 1b + ) and 2-cyclohexylbenzo[ d ]imidazolium ( 1e + ) salts. E ( 1 + / 1 • ) values for 2-aryl species are less reducing than for 2-alkyl analogues, i.e., the radicals are stabilized more by aryl groups than the cations, while 4,7-dimethoxy substitution leads to more reducing E ( 1 + / 1 • ) values, as well as cathodic shifts in E ( 1 2 •+ / 1 2 ) and E ( 1H •+ / 1H ) values. Both the use of 3,4-dimethoxy and 2-aryl substituents accelerates the reaction of the 1H species with PC 61 BM. Because 2-aryl groups stabilize radicals, 1b 2 and 1g 2 exhibit weaker bonds than 1e 2 and 1h 2 and thus react with 6,13-bis(triisopropylsilylethynyl)pentacene ( VII ) via a “cleavage-first” pathway, while 1e 2 and 1h 2 react only via “electron-transfer-first”. 1h 2 exhibits the most cathodic E ( 1 2 •+ / 1 2 ) value of the dimers considered here and, therefore, reacts more rapidly than any of the other dimers with VII via “electron-transfer-first”. Crystal structures show rather long central C–C bonds for 1b 2 (1.5899(11) and 1.6194(8) Å) and 1h 2 (1.6299(13) Å).
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Dynamic structural views in solar energy materials by femtosecond electron diffraction
Solar materials convert light into other forms of energy through excited state processes occurring on ultrafast time and atomic length scales. Understanding and controlling such nonequilibrium processes is essential for applications ranging from photovoltaics to photocatalysis. These processes are commonly studied by transient optical techniques, which resolve charge carrier dynamics. However, optical spectroscopy does not directly probe the atomic-scale motions that play a central role in the ultimate functionality of these materials. Filling this missing gap, ultrafast electron and x-ray scattering techniques enable monitoring of structural dynamics in materials with femtosecond time resolution. In this work, we focus on the use of ultrafast electron diffraction (UED) techniques to probe photoinduced energy conversion dynamics in solar energy materials. First, we discuss the use of UED as an ultrafast lattice thermometer allowing a direct probe of nonradiative relaxations such as hot carrier cooling and Auger recombination. Second, we present a time-resolved atomic pair distribution function analysis enabled by UED, which uncovers lattice deformations arising from excitation localization in materials. Finally, we provide an outlook looking toward new approaches for resolving in situ energy conversion dynamics and uncovering structure–property relationships in solar energy materials.
36 MATERIALS SCIENCE↗
Critical material content in modern conventional U.S. vehicle electronics
Critical materials (CM) are vital to modern technology. Components of modern vehicles can be recycled to recover and reuse the CMs to help ensure a supply of these materials. Electronic components from a 2015 GMC Sierra truck (21 components) and 2016 Toyota Camry sedan (10 components) were analyzed for CMs. The components were processed via size reduction, aqua regia leaching and dissolution, and final solutions were analyzed for metal content. It was found that most electronic components of both vehicles contain CM. The most concentrated CM in the components were Sn, Nb, and Tb. Nd and Co were found in several of the magnetic components. CM economic value was found to be low compared to the overall value of the components, and the CM content would not allow for a viable pathway for recycling. Remanufacturing of components may be a more economic option of reuse in the future.
2015 GMC Sierra↗
Rationalizing energy level alignment by characterizing Lewis acid/base and ionic interactions at printable semiconductor/ionic liquid interfaces
Charge transfer and energy conversion processes at semiconductor/electrolyte interfaces are controlled by local electric field distributions, which can be especially challenging to measure. Furthermore, we leverage the low vapor pressure and vacuum compatibility of ionic liquid electrolytes to undertake a layer-by-layer, ultra-high vacuum deposition of a prototypical ionic liquid EMIM + (1-ethyl-3-methylimidazolium) and TFSI – (bis(trifluoromethylsulfonyl)-imide) on the surfaces of different electronic materials. We consider a case-by-case study between a standard metal (Au) and four printed electronic materials, where interfaces are characterized by a combination of X-ray and ultraviolet photoemission spectroscopies (XPS/UPS). For template-stripped gold surfaces, we observe through XPS a preferential orientation of the TFSI anion at the gold surface, enabling large electric fields (~10 8 eV m –1 ) within the first two monolayers detected by a large surface vacuum level shift (0.7 eV) in UPS.
14 SOLAR ENERGY↗
A microscopic Kondo lattice model for the heavy fermion antiferromagnet CeIn 3
Electrons at the border of localization generate exotic states of matter across all classes of strongly correlated electron materials and many other quantum materials with emergent functionality. Heavy electron metals are a model example, in which magnetic interactions arise from the opposing limits of localized and itinerant electrons. This remarkable duality is intimately related to the emergence of a plethora of novel quantum matter states such as unconventional superconductivity, electronic-nematic states, hidden order and most recently topological states of matter such as topological Kondo insulators and Kondo semimetals and putative chiral superconductors. The outstanding challenge is that the archetypal Kondo lattice model that captures the underlying electronic dichotomy is notoriously difficult to solve for real materials. Here we show, using the prototypical strongly-correlated antiferromagnet CeIn 3 , that a multi-orbital periodic Anderson model embedded with input from ab initio bandstructure calculations can be reduced to a simple Kondo-Heisenberg model, which captures the magnetic interactions quantitatively. We validate this tractable Hamiltonian via high-resolution neutron spectroscopy that reproduces accurately the magnetic soft modes in CeIn 3 , which are believed to mediate unconventional superconductivity. Our study paves the way for a quantitative understanding of metallic quantum states such as unconventional superconductivity.
36 MATERIALS SCIENCE↗