D-Index & Metrics Best Publications
William H. Green

William H. Green

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Chemistry D-index 68 Citations 11,992 217 World Ranking 2939 National Ranking 1062

Overview

What is he best known for?

The fields of study he is best known for:

  • Quantum mechanics
  • Organic chemistry
  • Hydrogen

William H. Green mostly deals with Combustion, Computational chemistry, Thermodynamics, Kinetic energy and Reaction rate constant. His Combustion research is under the purview of Physical chemistry. His biological study spans a wide range of topics, including Fullerene, Thermochemistry, Additive function, Methane and Intramolecular force.

His Thermodynamics research includes elements of Alkane, Kinetics, Transition state and Pilot plant. William H. Green has included themes like Diffusion flame, Autoignition temperature, Flame structure, Inorganic chemistry and Disproportionation in his Reaction rate constant study. His Reaction mechanism research focuses on subjects like Radical, which are linked to Photochemistry.

His most cited work include:

  • Prediction of Organic Reaction Outcomes Using Machine Learning (217 citations)
  • Detailed modeling of PAH and soot formation in a laminar premixed benzene/oxygen/argon low-pressure flame (217 citations)
  • Reaction Mechanism Generator: Automatic construction of chemical kinetic mechanisms ☆ (212 citations)

What are the main themes of his work throughout his whole career to date?

William H. Green spends much of his time researching Computational chemistry, Combustion, Reaction mechanism, Thermodynamics and Kinetic energy. His work investigates the relationship between Computational chemistry and topics such as Additive function that intersect with problems in Group. His Combustion study frequently draws connections between adjacent fields such as Butanol.

His study in Thermodynamics is interdisciplinary in nature, drawing from both Kinetics and Density functional theory. His Kinetic energy research includes themes of Work and Physical chemistry. William H. Green has researched Physical chemistry in several fields, including Reaction rate constant and Reaction rate.

He most often published in these fields:

  • Computational chemistry (15.63%)
  • Combustion (15.36%)
  • Reaction mechanism (11.86%)

What were the highlights of his more recent work (between 2017-2021)?

  • Reaction mechanism (11.86%)
  • Computational chemistry (15.63%)
  • Radical (6.74%)

In recent papers he was focusing on the following fields of study:

William H. Green mainly investigates Reaction mechanism, Computational chemistry, Radical, Thermochemistry and Artificial intelligence. His Reaction mechanism research also works with subjects such as

  • Chemical kinetics which is related to area like Chemical engineering,
  • Flash photolysis, which have a strong connection to Analytical chemistry. His research investigates the connection between Computational chemistry and topics such as Kinetics that intersect with issues in Mass spectrometry.

William H. Green combines subjects such as Combustion, Ring, Cyclopentanone, Acetylene and Quantum chemistry with his study of Radical. The Combustion study which covers Extinction that intersects with Work. His Thermochemistry research incorporates elements of Additive function, Group and Computational science.

Between 2017 and 2021, his most popular works were:

  • A graph-convolutional neural network model for the prediction of chemical reactivity. (159 citations)
  • Machine Learning in Computer-Aided Synthesis Planning (149 citations)
  • A robotic platform for flow synthesis of organic compounds informed by AI planning. (135 citations)

In his most recent research, the most cited papers focused on:

  • Quantum mechanics
  • Organic chemistry
  • Hydrogen

His primary areas of study are Artificial intelligence, Thermochemistry, Reaction mechanism, Reaxys and Computational chemistry. His Artificial intelligence research integrates issues from Field, Machine learning, Medicinal chemistry and Reactivity. His biological study spans a wide range of topics, including Computation, Computational science, Chemical process modeling, Butane and Debugging.

His research integrates issues of Heteroatom, Nitrogen, Ignition system, Gasoline and Combinatorial chemistry in his study of Reaction mechanism. His research in Computational chemistry intersects with topics in Additive function, Chemical reaction, Organic reaction and Group. William H. Green has researched Kinetic energy in several fields, including Combustion, Nitrogen dioxide, Thermodynamics and Analytical chemistry.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Prediction of Organic Reaction Outcomes Using Machine Learning

Connor W. Coley;Regina Barzilay;Tommi S. Jaakkola;William H. Green.
ACS central science (2017)

472 Citations

A graph-convolutional neural network model for the prediction of chemical reactivity

Connor W. Coley;Wengong Jin;Luke Rogers;Timothy F. Jamison.
Chemical Science (2019)

386 Citations

Detailed modeling of PAH and soot formation in a laminar premixed benzene/oxygen/argon low-pressure flame

Henning Richter;Silvia Granata;Silvia Granata;William H. Green;Jack B. Howard.
Proceeding of the Combustion Institute, 2005 (2005)

363 Citations

Reaction Mechanism Generator: Automatic construction of chemical kinetic mechanisms ☆

Connie W. Gao;Joshua W. Allen;William H. Green;Richard H. West.
Computer Physics Communications (2016)

322 Citations

Comprehensive reaction mechanism for n-butanol pyrolysis and combustion

Michael R. Harper;Kevin M. Van Geem;Steven P. Pyl;Guy B. Marin.
Combustion and Flame (2011)

316 Citations

High‐gradient magnetic separation of coated magnetic nanoparticles

Geoffrey D. Moeser;Kaitlin A. Roach;William H. Green;T. Alan Hatton.
Aiche Journal (2004)

266 Citations

Rate-Based Construction of Kinetic Models for Complex Systems

Roberta G. Susnow;Anthony M. Dean;William H. Green;P. Peczak.
Journal of Physical Chemistry A (1997)

253 Citations

Optimally-reduced kinetic models: reaction elimination in large-scale kinetic mechanisms

Binita Bhattacharjee;Douglas A. Schwer;Paul I. Barton;William H. Green.
Combustion and Flame (2003)

242 Citations

Machine Learning in Computer-Aided Synthesis Planning

Connor W Coley;William H Green;Klavs F Jensen.
Accounts of Chemical Research (2018)

233 Citations

Intramolecular hydrogen migration in alkylperoxy and hydroperoxyalkylperoxy radicals: accurate treatment of hindered rotors.

Sandeep Sharma;Sumathy Raman;William H. Green.
Journal of Physical Chemistry A (2010)

231 Citations

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