Marie and BERT-A Knowledge Graph Embedding Based Question Answering System for Chemistry.

This paper presents a novel knowledge graph question answering (KGQA) system for chemistry, which is implemented on hybrid knowledge graph embeddings, aiming to provide fact-oriented information retrieval for chemistry-related research and industrial applications. Unlike other existing designs, the system operates on multiple embedding spaces, which use various embedding methods and queries the embedding spaces in parallel. With the answers returned from multiple embedding spaces, the system leverages a score alignment model to adjust the answer scores and rerank the answers.

Blockchain Technology in the Chemical Industry.

This article presents a review of the application of blockchain and blockchain-based smart contracts in the chemical and related industries. We introduce the basic concepts of blockchain and smart contracts and explain how some of their features are enabled. We review several typical or novel applications of blockchain and smart contract technologies and their enabling concepts and underlying technologies.

On the Viability of Video Imaging in Leak Rate Quantification: A Theoretical Error Analysis.

Optical gas imaging through multispectral cameras is a promising technique for mitigation of methane emissions through localization and quantification of emissions sources. While more advanced cameras developed in recent years have led to lower uncertainties in measuring gas concentrations, a systematic analysis of the uncertainties associated with leak rate estimation have been overlooked. We present a systematic categorization of the involved uncertainties with a focus on a theoretical analysis of projection uncertainties that are inherent to this technique.

Question Answering System for Chemistry.

This paper describes the implementation and evaluation of a proof-of-concept Question Answering (QA) system for accessing chemical data from knowledge graphs (KGs) which offer data from chemical kinetics to the chemical and physical properties of species. We trained the question classification and named the entity recognition models that specialize in interpreting chemistry questions. The system has a novel design which applies a topic model to identify the question-to-ontology affiliation to handle ontologies with different structures.

Mobile Measurement System for the Rapid and Cost-Effective Surveillance of Methane and Volatile Organic Compound Emissions from Oil and Gas Production Sites.

In this study, a ground-based mobile measurement system was developed to provide rapid and cost-effective emission surveillance of both methane (CH) and volatile organic compounds (VOCs) from oil and gas (O&G) production sites. After testing in several controlled release experiments, the system was deployed in a field campaign in the Eagle Ford basin, TX. We found fat-tail distributions for both methane and total VOC (C4-C12) emissions (e.

Multiscale Cross-Domain Thermochemical Knowledge-Graph.

In this paper, we develop a set of software agents which improve a knowledge-graph containing thermodynamic data of chemical species by means of quantum chemical calculations and error-canceling balanced reactions. The knowledge-graph represents species-associated information by making use of the principles of linked data, as employed in the Semantic Web, where concepts correspond to vertices and relationships between the concepts correspond to edges of the graph. We implement this representation by means of ontologies, which formalize the definition of concepts and their relationships, as a critical step to achieve interoperability between heterogeneous data formats and software.

Knowledge Graph Approach to Combustion Chemistry and Interoperability.

In this paper, we demonstrate through examples how the concept of a Semantic Web based knowledge graph can be used to integrate combustion modeling into cross-disciplinary applications and in particular how inconsistency issues in chemical mechanisms can be addressed. We discuss the advantages of linked data that form the essence of a knowledge graph and how we implement this in a number of interconnected ontologies, specifically in the context of combustion chemistry. Central to this is OntoKin, an ontology we have developed for capturing both the content and the semantics of chemical kinetic reaction mechanisms.

A small, lightweight multipollutant sensor system for ground-mobile and aerial emission sampling from open area sources.

Characterizing highly dynamic, transient, and vertically lofted emissions from open area sources poses unique measurement challenges. This study developed and applied a multipollutant sensor and time-integrated sampler system for use on mobile applications such as vehicles, tethered balloons (aerostats) and unmanned aerial vehicles (UAVs) to determine emission factors. The system is particularly applicable to open area sources, such as forest fires, due to its light weight (3.

A Mobile Sensing Approach for Regional Surveillance of Fugitive Methane Emissions in Oil and Gas Production.

This paper addresses the need for surveillance of fugitive methane emissions over broad geographical regions. Most existing techniques suffer from being either extensive (but qualitative) or quantitative (but intensive with poor scalability). A total of two novel advancements are made here.