From isomorphism to polymorphism: connecting interzeolite transformations to structural and graph similarity

Zeolites are nanoporous crystalline materials with abundant industrial applications. Despite sustained research, only 235 different zeolite frameworks have been realized out of millions of hypothetical ones predicted by computational enumeration. Structure-property relationships in zeolite synthesis are very complex and only marginally understood. Here, we apply structure and graph-based unsupervised machine learning to gain insight on zeolite frameworks and how they relate to experimentally observed polymorphism and phase transformations. We begin by describing zeolite structures using the Smooth Overlap of Atomic Positions method, which clusters crystals with similar cages and density in a way consistent with traditional hand-selected composite building units. To also account for topological differences, zeolite crystals are represented as multigraphs and compared by isomorphism tests. We find that fourteen different pairs and one trio of known frameworks are graph isomorphic. Based on experimental interzeolite conversions and occurrence of competing phases, we propose that the availability of kinetic-controlled transformations between metastable zeolite frameworks is related to their similarity in the graph space. When this description is applied to enumerated structures, over 3,400 hypothetical structures are found to be isomorphic to known frameworks, and thus might be realized from their experimental counterparts. Using a continuous similarity metric, the space of known zeolites shows additional overlaps with experimentally observed phase transformations. Hence, graph-based similarity approaches suggest a venue for realizing novel zeolites from existing ones by providing a relationship between pairwise structure similarity and experimental transformations.Comment: 11 pages, 6 figure

The Materials Science Procedural Text Corpus: Annotating Materials Synthesis Procedures with Shallow Semantic Structures

Materials science literature contains millions of materials synthesis procedures described in unstructured natural language text. Large-scale analysis of these synthesis procedures would facilitate deeper scientific understanding of materials synthesis and enable automated synthesis planning. Such analysis requires extracting structured representations of synthesis procedures from the raw text as a first step. To facilitate the training and evaluation of synthesis extraction models, we introduce a dataset of 230 synthesis procedures annotated by domain experts with labeled graphs that express the semantics of the synthesis sentences. The nodes in this graph are synthesis operations and their typed arguments, and labeled edges specify relations between the nodes. We describe this new resource in detail and highlight some specific challenges to annotating scientific text with shallow semantic structure. We make the corpus available to the community to promote further research and development of scientific information extraction systems.Comment: Accepted as a long paper at the Linguistic Annotation Workshop (LAW) at ACL 201

Inorganic Materials Synthesis Planning with Literature-Trained Neural Networks

Leveraging new data sources is a key step in accelerating the pace of materials design and discovery. To complement the strides in synthesis planning driven by historical, experimental, and computed data, we present an automated method for connecting scientific literature to synthesis insights. Starting from natural language text, we apply word embeddings from language models, which are fed into a named entity recognition model, upon which a conditional variational autoencoder is trained to generate syntheses for arbitrary materials. We show the potential of this technique by predicting precursors for two perovskite materials, using only training data published over a decade prior to their first reported syntheses. We demonstrate that the model learns representations of materials corresponding to synthesis-related properties, and that the model's behavior complements existing thermodynamic knowledge. Finally, we apply the model to perform synthesizability screening for proposed novel perovskite compounds.Comment: Added new funding support to the acknowledgments section in this versio

Manufacturing-focused emissions reductions in footwear production

What is the burden upon your feet? With sales of running and jogging shoes in the world averaging a nontrivial 25 billion shoes per year, or 34 million per day, the impact of the footwear industry represents a significant portion of the apparel sector's environmental burden. A single shoe can contain 65 discrete parts that require 360 processing steps for assembly. While brand name companies dictate product design and material specifications, the actual manufacturing of footwear is typically contracted to manufacturers based in emerging economies. Using life cycle assessment methodology in accordance with the ISO 14040/14044 standards, this effort quantifies the life cycle greenhouse gas emissions, often referred to as a carbon footprint, of a pair of running shoes. Furthermore, mitigation strategies are proposed focusing on high leverage aspects of the life cycle. Using this approach, it is estimated that the carbon footprint of a typical pair of running shoes made of synthetic materials is 14 ± 2.7 kg CO[subscript 2]-equivalent. The vast majority of this impact is incurred during the materials processing and manufacturing stages, which make up around 29% and 68% of the total impact, respectively. Other similar studies in the apparel industry have reported carbon footprints of running shoes ranging between 18 and 41 kg CO[subscript 2]-equivalent/pair (PUMA, 2008; Timberland, 2009). For consumer products not requiring electricity during use, the intensity of emissions in the manufacturing phase is atypical; most commonly, materials make up the biggest percentage of impact. This distinction highlights the importance of identifying mitigation strategies within the manufacturing process, and the need to evaluate the emissions reduction efficacy of each potential strategy. By suggesting a few of the causes of manufacturing dominance in the global warming potential assessment of this product, this study hypothesizes the characteristics of a product that could lead to high manufacturing impact. Some of these characteristics include the source of energy in manufacturing and the form of manufacturing, in other words the complexity of processes used and the area over which these process are performed (particularly when a product involves numerous parts and light materials). Thereby, the work provides an example when relying solely on the bill of materials information for product greenhouse gas emissions assessment may underestimate life cycle burden and ignore potentially high impact mitigation strategies

Composite cathodes for lithium rechargeable batteries

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Materials Science and Engineering, 2007.Includes bibliographical references.The utility of incorporating continuous, nanoscale vanadium oxide phases within preferred domains of self-organizing copolymers was investigated towards the fabrication of composite, nanoarchitectured electrode materials for solid-state rechargeable batteries. In situ growth of cathodic phases within ion-conducting copolymer domains was explored as a means to control morphology and to increase the surface-area-to-volume ratio, thereby increasing the specific electrode area for faradaic reactions and decreasing ion diffusion distances within the electrode-active material. Copolymers of microphase-separating rubbery block and graft copolymers, previously developed as solid electrolytes, provide a matrix for directing the synthesis of an inorganic battery-active phase. The copolymers include poly[(oxyethylene)9 methacrylate]-block-poly(butyl methacrylate) (POEM-b-PBMA) with a domain periodicity of -35 nm made by atom transfer radical polymerization, and poly[(oxyethylene)9 methacrylate]-graft-poly(dimethyl siloxane) (POEM-g-PDMS) with a domain periodicity of-17 nm made by free radical polymerization. The resulting microphase-separated polymer is a structure of alternating hydrophilic (Li-ion conducting) and hydrophobic regions.(cont.) Sol-gel chemistry involving a vanadium alkoxide precursor enabled the in situ growth of cathode-active vanadium oxide within the continuous ion-conducting POEM domains of the microphase-separated copolymers. Resulting films, termed POEM-b-PBMA/VOx and POEM-g-PDMS/VOx, were freestanding and mechanically flexible. Small angle x-ray scattering and transmission electron microscopy revealed the nanoscale morphology of the composite and confirmed the spatially-selective incorporation of up to 34 wt% VO, in POEM-b-PBMA and 31 wt% in POEM-g-PDMS. Electronically conductive components, necessary for wiring of the lithium-active vanadium oxide domains to the external circuit, were added through a variety of methods. Dispersions of acid-treated and cryo-ground carbon black within POEM-b-PBMA/VOx enabled the cycling of this material as a cathode. Reversible capacities of-~ 40 mAh/g were measured for batteries fitted with a polymer electrolyte doped with LiCF3SO3 and a lithium foil anode. Electrolyte thickness studies indicated battery performance was limited by the ionic conductivity of the solid electrolyte.(cont.) Using liquid electrolyte resulted in improved capacity (at higher currents) over conventional composite cathodes made from sol-gel derived vanadium oxide without the polymer matrix. The vanadium oxide nanoarchitecture was preserved upon removal of the polymer by heat treatment. The resulting templated vanadium oxide, when repotted with carbon black and binder, exhibited improved capacity at high current over non-templated vanadium oxide cathodes.by Elsa A. Olivetti.Ph.D

Cumbre AIM4C: Innovación para integrar e incorporar la agricultura en la acción por el clima

El sistema agroalimentario tiene un impacto significativo en el cambio climático al ser responsable de más del 30% de las emisiones globales de gases de efecto invernadero. Este sistema también se ve afectado por fenómenos climáticos extremos y cambios en las condiciones de cultivo, lo que amenaza la seguridad alimentaria, los medios de vida y la estabilidad ecológica, especialmente para mujeres, jóvenes y grupos vulnerables. En la Cumbre de Innovación Agrícola para el Clima (AIM4C) en Washington, el Instituto Interamericano de Cooperación para la Agricultura (IICA) organizó una sesión sobre "Innovación para integrar y promover la agricultura en las NDC". En esta sesión, se discutieron estrategias para acelerar la innovación agrícola en términos de mitigación y adaptación al cambio climático. Se destacó la necesidad de políticas adecuadas que fomenten la ampliación de innovaciones prometedoras en el sector agrícola, lo cual requiere una modernización de los sistemas políticos e institucionales. Para implementar con éxito estas innovaciones, se deben abordar tres desafíos institucionales: fortalecer la coordinación, ampliar la financiación climática y mejorar el monitoreo y análisis de datos. La Iniciativa Integral para el Cambio Climático (CACCI) ha sido efectiva en apoyar la implementación de acciones climáticas a través de la agricultura y en fortalecer la capacidad de los actores involucrados. Estas acciones deben combinarse en un enfoque multifacético para abordar los desafíos climáticos a nivel nacional e internacional

Economics of End-of-Life Materials Recovery: A Study of Small Appliances and Computer Devices in Portugal

The challenges brought on by the increasing complexity of electronic products, and the criticality of the materials these devices contain, present an opportunity for maximizing the economic and societal benefits derived from recovery and recycling. Small appliances and computer devices (SACD), including mobile phones, contain significant amounts of precious metals including gold and platinum, the present value of which should serve as a key economic driver for many recycling decisions. However, a detailed analysis is required to estimate the economic value that is unrealized by incomplete recovery of these and other materials, and to ascertain how such value could be reinvested to improve recovery processes. We present a dynamic product flow analysis for SACD throughout Portugal, a European Union member, including annual data detailing product sales and industrial-scale preprocessing data for recovery of specific materials from devices. We employ preprocessing facility and metals pricing data to identify losses, and develop an economic framework around the value of recycling including uncertainty. We show that significant economic losses occur during preprocessing (over $70 M USD unrecovered in computers and mobile phones, 2006–2014) due to operations that fail to target high value materials, and characterize preprocessing operations according to material recovery and total costs.Portuguese Foundation for International Cooperation in Science, Technology and Higher EducationMIT Portugal Progra

Advancing Alternative Analysis: Integration of Decision Science.

Decision analysis-a systematic approach to solving complex problems-offers tools and frameworks to support decision making that are increasingly being applied to environmental challenges. Alternatives analysis is a method used in regulation and product design to identify, compare, and evaluate the safety and viability of potential substitutes for hazardous chemicals.Assess whether decision science may assist the alternatives analysis decision maker in comparing alternatives across a range of metrics.A workshop was convened that included representatives from government, academia, business, and civil society and included experts in toxicology, decision science, alternatives assessment, engineering, and law and policy. Participants were divided into two groups and prompted with targeted questions. Throughout the workshop, the groups periodically came together in plenary sessions to reflect on other groups' findings.We conclude the further incorporation of decision science into alternatives analysis would advance the ability of companies and regulators to select alternatives to harmful ingredients, and would also advance the science of decision analysis.We advance four recommendations: (1) engaging the systematic development and evaluation of decision approaches and tools; (2) using case studies to advance the integration of decision analysis into alternatives analysis; (3) supporting transdisciplinary research; and (4) supporting education and outreach efforts

Machine-Learning Based Selection and Synthesis of Candidate Metal-Insulator Transition Metal Oxides

The discovery of materials that exhibit a metal-insulator transition (MIT) is key to the development of multiple types of novel efficient microelectronic and optoelectronic devices. However, identifying MIT materials is challenging due to a combination of high computational cost of electronic structure calculations needed to understand their mechanism, the mechanisms' complexity, and the labor-intensive experimental validation process. To that end, we use a machine learning classification model to rapidly screen a high-throughput crystal structure database to identify candidate compounds exhibiting thermally-driven MITs. We focus on three candidate oxides, Ca$_2$Fe$_3$O$_8$, CaCo$_2$O$_4$, and CaMn$_2$O$_4$, and identify their MIT mechanism using high-fidelity density functional theory calculations. Then, we provide a probabilistic estimate of which synthesis reactions may lead to their realization. Our approach couples physics-informed machine learning, density functional theory calculations, and machine learning-suggested synthesis to reduce the time to discovery and synthesis of new technologically relevant materials