Can Artificial Intelligence and Machine Learning Be Used to Accelerate Sustainable Chemistry and Engineering?

Predicting flammability-leading properties for liquid aerosol safety via machine learning

(2021) Chenxi Ji et al.   PROCESS SAFETY AND ENVIRONMENTAL PROTECTION

Deep learning and knowledge-based methods for computer-aided molecular design—toward a unified approach: State-of-the-art and future directions

(2020) Abdulelah S. Alshehri et al.   COMPUTERS & CHEMICAL ENGINEERING

The importance of synthetic chemistry in the pharmaceutical industry

(2019) Kevin R. Campos et al.   SCIENCE

Enhancing materials property prediction by leveraging computational and experimental data using deep transfer learning

(2019) Dipendra Jha et al.   Nature Communications

ReLU networks as surrogate models in mixed-integer linear programs

(2019) Bjarne Grimstad et al.   COMPUTERS & CHEMICAL ENGINEERING

Machine learning for heterogeneous catalyst design and discovery

(2018) Bryan R. Goldsmith et al.   AICHE JOURNAL

Machine learning: Overview of the recent progresses and implications for the process systems engineering field

(2018) Jay H. Lee et al.   COMPUTERS & CHEMICAL ENGINEERING

Extracting Knowledge from Data through Catalysis Informatics

(2018) Andrew J. Medford et al.   ACS Catalysis

Planning chemical syntheses with deep neural networks and symbolic AI

(2018) Marwin H. S. Segler et al.   NATURE

The promise of artificial intelligence in chemical engineering: Is it here, finally?

(2018) Venkat Venkatasubramanian   AICHE JOURNAL

ChemDataExtractor: A Toolkit for Automated Extraction of Chemical Information from the Scientific Literature

(2016) Matthew C. Swain et al.   Journal of Chemical Information and Modeling

A multi-scale framework for CO 2 capture, utilization, and sequestration: CCUS and CCU

(2015) M.M. Faruque Hasan et al.   COMPUTERS & CHEMICAL ENGINEERING

Towards a holistic approach to metrics for the 21st century pharmaceutical industry

(2015) C. Robert McElroy et al.   GREEN CHEMISTRY