Using Data-Rich Experimentation to Enable the Development of Continuous Processes

Oxidative Nitration reaction with a fast and highly exothermic oxidation step using reaction calorimetry and process analytical technology

David Ford of Nalas investigated an Oxidative Nitration reaction with a fast and highly exothermic oxidation step using reaction calorimetry and Process Analytical Technology (PAT).

The methodology of and benefits of converting from a batch to a continuous process are presented, including:

  • Initial calorimetry screening to understand thermal risks
  • Application of Process Analytical Technology (PAT) to improve the stability of an intermediate
  • Improving mixing, yield and heat transfer by applying continuous stirred tank reactors (CSTR) in series

Who Should View this Presentation?

  • Chemists and Chemical Engineers in the Chemical, Petrochemical and Pharmaceutical industries as well as Academia.

What is Data-Rich Experimentation (DRE)?

Data-rich experimentation (DRE) is an essential methodology that refers to the systematic processes of data capture, data reduction, and data analysis. By leveraging the power of DRE, researchers can ensure high levels of reproducibility and accuracy when designing experiments for late-stage process characterization. Adopting DRE as a standard practice can significantly improve the efficiency and reliability of scientific research, leading to breakthroughs in various fields.

Data-rich experimentation can be used to characterize processes using automated reactor and sampling technologies, develop continuous flow processes, and facilitate pharmaceutical development.


David Ford, Ph.D.

Nalas Engineering

Upon receiving his B.S. in Chemistry at the University of California, Berkeley, David Ford performed his graduate studies in Professor Eric Jacobsen’s group at Harvard University. The theme of his thesis research was the use of physical-organic chemistry techniques to elucidate mechanistic details of catalytic reactions. After completing his Ph.D., he joined Nalas as a process chemist. Dr. Ford has worked on using data-rich experimentation to develop sound process understanding, and also applied those insights to the design of continuous processes.