What is he best known for?
The fields of study he is best known for:
- Organic chemistry
- Thermodynamics
- Hydrogen
Alan K. Burnham spends much of his time researching Mineralogy, Pyrolysis, Oil shale, Kerogen and Thermodynamics.
His studies deal with areas such as Kinetic analysis, Fossil fuel and Source rock as well as Mineralogy.
His work carried out in the field of Pyrolysis brings together such families of science as Decomposition, Fischer assay, Oil shale gas and Analytical chemistry.
His Oil shale research is multidisciplinary, incorporating elements of Overburden and Hydrocarbon.
His Kerogen course of study focuses on Petroleum and Natural gas and Petroleum reservoir.
His Thermodynamics study combines topics in areas such as Reaction rate and Activation energy.
His most cited work include:
- ICTAC Kinetics Committee recommendations for performing kinetic computations on thermal analysis data (2725 citations)
- Evaluation of a Simple Model of Vitrinite Reflectance Based on Chemical Kinetics (1247 citations)
- Computational aspects of kinetic analysis: Part A: The ICTAC kinetics project-data, methods and results (719 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Oil shale, Mineralogy, Pyrolysis, Kerogen and Thermodynamics.
The Oil shale study combines topics in areas such as Retort and Petroleum engineering.
His Mineralogy research incorporates themes from Sedimentary rock, Vitrinite, Fischer assay and Fossil fuel.
His study in Pyrolysis is interdisciplinary in nature, drawing from both Yield, Chemical reaction and Analytical chemistry.
Alan K. Burnham has researched Kerogen in several fields, including Organic matter, Petroleum and Hydrocarbon.
His research in Thermodynamics focuses on subjects like Activation energy, which are connected to Thermal decomposition.
He most often published in these fields:
- Oil shale (30.97%)
- Mineralogy (26.99%)
- Pyrolysis (25.66%)
What were the highlights of his more recent work (between 2010-2021)?
- Oil shale (30.97%)
- Mineralogy (26.99%)
- Kerogen (21.24%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Oil shale, Mineralogy, Kerogen, Pyrolysis and Petroleum engineering.
Alan K. Burnham combines subjects such as Retort, Permeability and Formation evaluation with his study of Oil shale.
Alan K. Burnham merges Mineralogy with Spatial heterogeneity in his study.
Kerogen is a subfield of Source rock that he explores.
His Pyrolysis study integrates concerns from other disciplines, such as Adsorption, Polyethylene, Activation energy and Thermodynamics.
In the subject of general Thermodynamics, his work in Volatility is often linked to Statistical error and Differential thermal analysis, thereby combining diverse domains of study.
Between 2010 and 2021, his most popular works were:
- ICTAC Kinetics Committee recommendations for performing kinetic computations on thermal analysis data (2725 citations)
- Critical Review of the Global Chemical Kinetics of Cellulose Thermal Decomposition (76 citations)
- ICTAC Kinetics Committee recommendations for analysis of multi-step kinetics (62 citations)
In his most recent research, the most cited papers focused on:
- Organic chemistry
- Thermodynamics
- Hydrogen
Oil shale, Kerogen, Mineralogy, Petroleum engineering and Thermodynamics are his primary areas of study.
His research in Oil shale intersects with topics in Phase transition, Capillary action and Microstructure.
His work deals with themes such as Organic matter, Asphalt, Maceral and Reflectivity, which intersect with Kerogen.
Alan K. Burnham has included themes like Phase boundary, Stress, Green River Formation and Vitrinite in his Mineralogy study.
The various areas that Alan K. Burnham examines in his Petroleum engineering study include Waste management, Shale oil extraction, Petroleum and Open system.
His biological study spans a wide range of topics, including Industrial engineering, Pyrolysis, Activation energy and Computation.
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.
