8,980 research outputs found
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
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
An Independent Review of USGS Circular 1370: An Evaluation of the Science Needs to Inform Decisions on Outer Continental Shelf Energy Development in the Chukchi and Beaufort Seas, Alaska
Reviews the U.S. Geological Survey's findings and recommendations on Alaska's Arctic Ocean, including geology, ecology and subsistence, effect of climate change on, and impact of oil spills. Makes recommendations for data management and other issues
Computational design of syntheses leading to compound libraries or isotopically labelled targets
Although computer programs for retrosynthetic planning have shown improved and in some cases quite satisfactory performance in designing routes leading to specific, individual targets, no algorithms capable of planning syntheses of entire target libraries - important in modern drug discovery - have yet been reported. This study describes how network-search routines underlying existing retrosynthetic programs can be adapted and extended to multi-target design operating on one common search graph, benefitting from the use of common intermediates and reducing the overall synthetic cost. Implementation in the Chematica platform illustrates the usefulness of such algorithms in the syntheses of either (i) all members of a user-defined library, or (ii) the most synthetically accessible members of this library. In the latter case, algorithms are also readily adapted to the identification of the most facile syntheses of isotopically labelled targets. These examples are industrially relevant in the context of hitto-lead optimization and syntheses of isotopomers of various bioactive molecules
Development of a Student Lab Experiment: 1H NMR Characterization and Synthesis of Substituted 2,2’-Bipyridines
This paper describes an undergraduate research project focused on the creation of a laboratory experiment that crosses the fields of green, biomimetic, inorganic, organic, and organometallic chemistry. Research involved investigation of the synthesis and NMR characterization of a series of Water oxidation catalysts for providing a rich learning experience for students. A goal of this project was to consider the implementation of a greener student laboratory where learning outcomes across multiple years of undergraduate laboratories could be proposed. The experimental progress and results to date will be presented
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