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Metal-insulator transition (MIT) compounds are materials that may exhibit insulating or metallic behavior, depending on the physical conditions, and are of immense fundamental interest owing to their potential applications in emerging microelectronics. There is a dearth of thermally-driven MIT materials, however, which makes delineating these compounds from those that are exclusively insulating or metallic challenging. Here we report a material database comprising temperature-controlled MITs (and metals and insulators with similar chemical composition and stoichiometries to the MIT compounds) from high quality experimental literature, built through a combination of materials-domain knowledge and natural language processing. We featurize the dataset using compositional, structural, and energetic descriptors, including two MIT relevant energy scales, an estimated Hubbard interaction and the charge transfer energy, as well as the structure-bond-stress metric referred to as the global-instability index (GII). We then perform supervised classification, constructing three electronic-state classifiers: metal vs non-metal (M), insulator vs non-insulator (I), and MIT vs non-MIT (T). We identify two important descriptors that separate metals, insulators, and MIT materials in a 2D feature space: the average deviation of the covalent radius and the range of the Mendeleev number. We further elaborate on other important features (GII and Ewald energy), and examine how they affect classification of binary vanadium and titanium oxides. We discuss the relationship of these atomic features to the physical interactions underlying MITs in the rare-earth nickelate family. Last, we implement an online version of the classifiers, enabling quick probabilistic class predictions by uploading a crystallographic structure file.

Establishing the composition-structure-property relationships for amorphous materials is critical for many important natural and engineering processes, including the dissolution of highly complex volcanic glasses. In this investigation, we performed force field molecular dynamics (MD) simulations to generate detailed structural representations for ten natural CaO-MgO-Al2O3-SiO2-TiO2-FeO-Fe2O3-Na2O-K2O glasses with compositions ranging from rhyolitic to basaltic. Based on the resulting atomic structural representations at 300 K, we have calculated the partial radial distribution functions, nearest interatomic distances and coordination number, which are consistent with the literature data on silicate-based glasses. Based on these structural attributes and classical bond valence models, we have introduced a novel structural descriptor, i.e., average metal-oxygen (M-O) bond strength parameter, which has captured the log dissolution rates of the ten glasses at both acidic and basic conditions (based on literature data) with R2 values of ~0.80-0.92 based on linear regression. This structural descriptor is seen to outperform several other structural descriptors also derived from MD simulation results, including the average metal oxide dissociation energy, the average self-diffusion coefficient of all the atoms at their melting points, and the energy barrier of self-diffusion. Furthermore, we showed that the MD-derived descriptors generally exhibit better predictive performance than the degree of depolymerization parameter commonly used to describe glass and mineral reactivity. The results suggest that the structural descriptors derived from MD simulations, especially the average M-O bond strength parameter, are promising structural descriptors for connecting composition with dissolution rates of highly complex natural glasses., 49 pages, 13 figures

Zeolites are versatile catalysts and molecular sieves with large topological diversity, but managing phase competition in zeolite synthesis is an empirical, labor-intensive task. Here, we controlled phase selectivity in templated zeolite synthesis from first principles by combining high-throughput atomistic simulations, literature mining, human-computer interaction, synthesis, and characterization. Proposed binding metrics distilled from over 586,000 zeolite-molecule simulations reproduced the extracted literature and rationalize framework competition in the design of organic structure-directing agents. Energetic, geometric, and electrostatic descriptors of template molecules were found to regulate synthetic accessibility windows and aluminum distributions in pure-phase zeolites. Furthermore, these parameters allowed realizing an intergrowth zeolite through a single bi-selective template. The computation-first approach enabled controlling both zeolite synthesis and structure composition using a priori theoretical descriptors., National Science Foundation (Awards 1922311, 1922372 and 1922090), Office of Naval Research (Contract N00014-20-1-2280)

Climate change will increase the frequency and severity of supply chain disruptions and large-scale economic crises, also prompting environmentally protective local policies. Here we use econometric time series analysis, inventory-driven price formation, dynamic material flow analysis, and life cycle assessment to model each copper supply chain actor’s response to China’s solid waste import ban and the COVID-19 pandemic. We demonstrate that the economic changes associated with China’s solid waste import ban increase primary refining within China, offsetting the environmental benefits of decreased copper scrap refining and generating a cumulative increase in CO2-equivalent emissions of up to 13 Mt by 2040. Increasing China’s refined copper imports reverses this trend, decreasing CO2e emissions in China (up to 180 Mt by 2040) and globally (up to 20 Mt). We test sensitivity to supply chain disruptions using GDP, mining, and refining shocks associated with the COVID-19 pandemic, showing the results translate onto disruption effects., Advanced copper supply chain modeling shows China’s new waste trade policy may increase pollution, while limiting other low-value imports reverses this trend. Here the authors show that recycling is vulnerable to supply chain shocks, requiring investment during recoveries to promote a circular economy.

A methodology for calibrating pH meters in highly alkaline solutions such as those relevant to cementitious systems is presented. This methodology uses an extended form of the Debye-Huckel equation to generate a calibration curve of pH vs. the measured electrochemical potential (mV) based on a series of aqueous alkali hydroxide solutions of known concentrations. This methodology is compared with the ‘built-in’ process of calibration based upon pH 4, 7, and 10 standard solutions. The built-in calibration process underestimates the real pH values by up to 0.3 log units, which is attributed to the alkali error. A spreadsheet for determining the calibration curve and its application to pH meter readings is provided as Supporting Information. The implications of improperly calibrated pH meters on interpreting solution chemistry in cementitious systems are discussed.

This research incorporates waste boiler ash into masonry construction materials using alkali-activation. The boiler ash, derived from three different Indian pulp and paper mills, has many undesirable characteristics for alkali-activation, including varying shape, large particle sizes ranging from 5 to 600 μm, loss on ignition between 8 and 35%, and less than 4% alumina. When combined with supplementary materials in the form of clay and lime, high compressive strengths are observed in the bricks made with all three ashes, demonstrating the robustness of the proposed mix design. A brick formulation with a solids phase weight ratio of ash(70):clay(20):lime(10), liquid to solid ratio of 0.45, and 2 M NaOH produces bricks with compressive strengths between 11 and 15 MPa after 28 days curing at 30 °C. Furthermore, early strength development is observed, as more than 55% of the 28 day strength is achieved after one day curing. An economic and environmental analysis indicates that these bricks can be produced for similar costs as the clay fired brick with reduced environmental impact, making them a viable alternative in the market.

Summary Sustained growth in lithium-ion battery (LIB) demand within the transportation sector (and the electricity sector) motivates detailed investigations of whether future raw materials supply will reconcile with resulting material requirements for these batteries. We track the metal content associated with compounds used in LIBs. We find that most of the key constituents, including manganese, nickel, and natural graphite, have sufficient supply to meet the anticipated increase in demand for LIBs. There may be challenges in rapidly scaling the use of materials associated with lithium and cobalt in the short term. Due to long battery lifetimes and multiple end uses, recycling is unlikely to provide significant short-term supply. There are risks associated with the geopolitical concentrations of these elements, particularly for cobalt. The lessons revealed in this work can be relevant to other industries in which the rapid growth of a materials-dependent technology disrupts the global supply of those materials.

Increased interest in high entropy alloys (HEA)s has led to significant activity in the development of new equimolar multicomponent metal systems. The present viewpoint article suggests applying a lens of practicality related to alloy economics and resource usage issues. A framework for HEA materials selection is presented to assist the metallurgical community as it searches for HEAs with feasible implementation possibilities, by identifying unsuitable alloying elements based on price or metrics of supply availability. For some metrics, such as price volatility, the elemental diversification in HEAs could prove beneficial, while for others, such as recyclability, elemental breadth introduces significant challenges. Keywords: High-entropy alloys; Multicomponent; Modeling; Analytical methods, National Science Foundation (Grant CBET-1605050)

Predicting and directing polymorphic transformations is a critical challenge in zeolite synthesis. Although interzeolite transformations enable selective crystallization, their design lacks predictions to connect framework similarity and experimental observations. Here, computational and theoretical tools are combined to data-mine, analyze and explain interzeolite relations. It is observed that building units are weak predictors of topology interconversion and insufficient to explain intergrowth. By introducing a supercell-invariant metric that compares crystal structures using graph theory, we show that topotactic and reconstructive (diffusionless) transformations occur only between graph-similar pairs. Furthermore, all known instances of intergrowth occur between either structurally-similar or graph-similar frameworks. Backed with exhaustive literature results, we identify promising pairs for realizing novel diffusionless transformations and intergrowth. Hundreds of low-distance pairs are identified among known zeolites, and thousands of hypothetical frameworks are connected to known zeolites counterparts. The theory opens a venue to understand and control zeolite polymorphism., Pre-peer review manuscript; 8 pages, 3 figures

Biomass ash results from the combustion of agricultural residues, which, in many developing countries, are a primary source of power generation for small and medium size industries. This study focuses on the performance of a binder synthesized from an Indian biomass ash, Indo-Gangetic clay, hydrated lime, and aqueous 1M NaOH solution. To measure the extent of leaching and its impact on physicochemical properties, the biomass ash binder in powder form (

Slags with varied amorphous and crystalline content, typical of iron and steel production, are generally underutilized. One promising reuse pathway for these wastes is chemical activation, producing alternatives to conventional building materials with lower embodied energy. The formation of a hardened binder is dependent on the slag mineralogy and, specifically, the reactivity of relevant phases. Reactivity can be understood by monitoring elemental dissolution rates through inductively coupled plasma (ICP-OES) analysis. Post-dissolution ICP analysis of activating solution and spectroscopic analysis of remaining solids was performed on several highly crystalline slags and on relevant synthetic minerals to track changes in chemical and phase composition. Amorphous and ionic phases have been observed as more reactive than other crystalline phases. This work aims to inform future studies on waste blending in alkali-activated systems, a promising avenue for valorization of industrial wastes with varied physicochemical properties. To this end, dissolution tests with varied initial Si, Al, and Ca concentrations in activating solution were also performed.

Exciting metallurgical breakthroughs of the last decades alongside the development and wide-ranging availability of new and more capable experimental and theoretical tools for metals research demonstrate that we are witnessing the dawn of a new age in metals design. Historically, the discovery of new metallic materials has enabled the vast majority of the key engineering advances in human history. Current engineering challenges create an urgent need for new metallic materials to further our technological advances in multiple industries that are key to our existence. Yet, present data on metals processing clearly demonstrate the significant environmental impact of the metallurgical industry on our planet’s future. There are numerous reports in which this impact and corresponding processing solutions are discussed. On the other hand, design of new metallic materials with improved property combinations can help address key environmental challenges in various ways. To this end, the goal of this review is to discuss the most urgent sustainability challenges that can be addressed with alloy design, to help orchestrate the increasing interest in metallurgical research to focus on these most critical challenges.

While the incineration of biomass residues is gaining traction as a globally available source of renewable energy, the resulting ash is often landfilled, resulting in the disposal of what could otherwise be used in value-added products. This research focuses on the beneficial use of predominantly rice husk and sugarcane bagasse-based mixed biomass ashes, obtained from two paper mills in northern India. A cementitious binder was formulated from biomass ash, clay, and hydrated lime (70:20:10 by mass, respectively) using 2M NaOH solution at a liquid-to-solid mass ratio of 0.40. Compressive strength of the biomass ash binder increased linearly with compaction pressure, indicating the role of packing density. Between the two mixed biomass ashes used in this study, the one with higher amorphous content resulted in a binder with higher strength and denser reaction product. Multi-faceted characterization of the biomass ash binder indicated the presence of aluminum-substituted calcium silicate hydrate, mainly derived from the pozzolanic reaction. Keywords: Biomass ash; Clay; Characterization; Pozzolanicity; Alkali-activation; Amorphous content, National Science Foundation (Grant DMR-1419807)

© 2017 American Chemical Society. In the past several years, Materials Genome Initiative (MGI) efforts have produced myriad examples of computationally designed materials in the fields of energy storage, catalysis, thermoelectrics, and hydrogen storage as well as large data resources that are used to screen for potentially transformative compounds. The bottleneck in high-Throughput materials design has thus shifted to materials synthesis, which motivates our development of a methodology to automatically compile materials synthesis parameters across tens of thousands of scholarly publications using natural language processing techniques. To demonstrate our framework's capabilities, we examine the synthesis conditions for various metal oxides across more than 12 thousand manuscripts. We then apply machine learning methods to predict the critical parameters needed to synthesize titania nanotubes via hydrothermal methods and verify this result against known mechanisms. Finally, we demonstrate the capacity for transfer learning by using machine learning models to predict synthesis outcomes on materials systems not included in the training set and thereby outperform heuristic strategies.

Predictive materials design has rapidly accelerated in recent years with the advent of large-scale resources, such as materials structure and property databases generated by ab initio computations. In the absence of analogous ab initio frameworks for materials synthesis, high-throughput and machine learning techniques have recently been harnessed to generate synthesis strategies for select materials of interest. Still, a community-accessible, autonomously-compiled synthesis planning resource which spans across materials systems has not yet been developed. In this work, we present a collection of aggregated synthesis parameters computed using the text contained within over 640,000 journal articles using state-of-the-art natural language processing and machine learning techniques. We provide a dataset of synthesis parameters, compiled autonomously across 30 different oxide systems, in a format optimized for planning novel syntheses of materials.

Systematic variation in the electrical conductivity of poly(3,4-ethylenedioxythiophene) (PEDOT) was achieved by oxidative chemical vapor deposition (oCVD). For oCVD, both the oxidant, Fe(III)Cl3, and 3,4-ethylenedioxythiophene (EDOT) monomer are introduced in the vapor phase. A heated crucible allows for sublimation of the oxidant directly into the reactor chamber operating at 150 mTorr. Spontaneous reaction of the oxidant with the monomer introduced though a feedback-controlled mass flow system results in the rapid (>200 nm thick film in 30 min) formation of π-conjugated PEDOT thin films directly onto a temperature-controlled substrate. As the substrate temperature is increased from 15 to 110 °C, increasing conjugation length, doping level, and electrical conductivity of the PEDOT chains are observed by UV−vis absorption spectroscopy (UV−vis), Fourier transform infrared spectroscopy (FTIR), and Raman spectroscopy. Concomitantly, the measured electrical conductivity of the PEDOT films increases systematic...

Films consisting of a vanadium pentoxide (i.e., V2O5) phase formed within a rubbery block copolymer were developed for their potential use as nanocomposite cathodes in lithium rechargeable batteries. Nanocomposite films were prepared by sol−gel synthesis from vanadyl triisopropoxide precursor in poly(oligooxyethylene methacrylate)-block-poly(butyl methacrylate), POEM-b-PBMA. The in situ growth of amorphous V2O5 was confirmed by wide-angle X-ray scattering (WAXS), X-ray photoelectron spectroscopy (XPS), and small-angle X-ray scattering (SAXS). Scanning transmission electron microscopy (STEM) and differential scanning calorimetry (DSC) demonstrated the selective incorporation of vanadium oxide within the ion-conducting POEM domains, while the oxide morphology was revealed by TEM to be a filamentous network. Cyclic voltammetry and impedance spectroscopy confirmed the preservation of the redox properties of the vanadium oxide and the ion-conductive properties of the polymer in hybrid films. Co-assembled nanoc...

This investigation revealed that the thermodynamic reactions that occur during Al remelting may lead to material losses for specific elements and circumstances. Mg losses as a result of oxidation are thermodynamically favorable to occur, but are limited by the exposure of Mg particulates to the oxygen atmosphere. Volatilization of Mn may also contribute to material losses, which is also limited by the materials exposure to the oxygen atmosphere. The relatively short melt processing times and the protective dross layer may largely limit the oxidation of Mg and volatilization of Mn. Material losses from the formation of second phase precipitates were shown to be exclusively a concern for the formation of second phase particles with densities less than Al. The low density of Al severely limited the potential compounds that could contribute to material losses. A study on the formation of pure Si second phase particles demonstrated that the particles would need to be approximately 40 µm to reach the dross under normal processing conditions. Particles of other compositions are expected to require much larger melting periods to reach the dross because the low density of Si allows it to serve as the lower bound of the time requirement. Dross chemistry was shown to influence the material yield. Batch planners should consider which fluxes are implemented in the modeled process to accurately predict batch plans. Aluminum recycling batch planners should also be prepared to update their batch plans as the popularity of chemically reactive fluxes and dross reprocessing for material recovery increases. Better management methods for compositional uncertainty resulting from thermodynamic effects will allow creation of batch plans for Al alloy products that increase incorporation of secondary metals, thereby reducing energy consumption in Al production while simultaneously providing economic benefits.

Films consisting of a vanadium pentoxide ! i.e., V2O5" phase formed within a rubbery block copolymer were developed for their potential use as nanocomposite cathodes in lithium rechargeable batteries. Films were prepared by sol-gel synthesis from vanadyl triisopropoxide precursor in poly! oligooxyethylene methacrylate" -block-poly! butyl methacrylate" , incorporating LiCF3SO3 and carbon black as conductivity additives. The morphology of the films was examined using electron microscopy, and their electrochemical performance was assessed by galvanostatic cycling. An all-solid-state battery comprising a polymer-based cathode and a block copolymer electrolyte was cycled repeatedly. The capacity was measured to be 40 mAh/g and found to be limited by the conductivity of the polymer electrolyte. A comparison between a nanocomposite cathode and a control cathode with the same carbon:vanadium oxide ratio demonstrated higher rate capability for the nanocomposite sample when paired with a liquid electrolyte. This study demonstrates the potential utility of block copolymers in the fabrication of high-surface-area cathodes for lithium batteries.

Control over doping level and work function is achieved for poly(3,4-ethylenedioxythiophene) (PEDOT) films deposited by oxidative chemical vapor deposition (oCVD). Surface analysis reveals the equivalence of the surface and bulk compositions for the oCVD films. The oCVD PEDOT polymer chains doped solely with Cl− ions. By increasing the substrate temperature used for deposition, the doping level was monotonically increased from 17to33at.%, resulting in a corresponding ability to tune the work function from 5.1to5.4eV. The controllability of doping level and work function of oCVD PEDOT offers great potential advantages for organic devices.

Graft copolymer electrolytes (GCEs) of poly[(oxyethylene)9 methacrylate]-g-poly(dimethyl siloxane) (POEM-g-PDMS) (70:30) have been synthesized by simple free radical polymerization using a macromonomer route. Differentialscanning calorimetry, transmission electron microscopy, and small angle neutron scattering confirmed the material to be microphase-separated with a domain periodicity of ∼25 nm. Over the temperature range 290 200 cycles) at a discharge rate of 2/3 C and could be cycled (charged and discharged) at subambient temperature (0°C).