Presentations

2026

  1. Mohan et al. Interpretable Machine Learning for Predicting Lignocellulosic Biomass Delignification Using Organosolv Processes. at ACS Spring 2026, March 21-26, 2026, Atlanta, GA, USA. Presentation type: Oral.
  2. Mohan et al. Machine Learning to Predict Solvatochromic Parameters of Designer Solvents. at ACS Spring 2026, March 21-26, 2026, Atlanta, GA, USA. Presentation type: Poster.

2025

  1. Mohan et al. Natural Language Processing in Molecular Chemistry: Property Predictions for Organic Compounds. at Artificial Intelligence for Materials Science (AIMS) Workshop, Rockville, Maryland, Jul 09-10, 2025. Presentation type: Poster.
  2. Mohan et al. Interpretable Machine Learning for Predicting Lignocellulosic Biomass Delignification Using Organosolv Processes. at the DOE BSSD PI Meeting, Arlington, VA, March 31-April 2, 2025. Presentation type: Poster.
  3. Mohan et al. Designer Solvents in Sustainable Chemistry: Physics-Informed Machine Learning for Accurate Prediction of Thermodynamic Properties. at the 28th ACS Annual Green Chemistry & Engineering Conference, Atlanta, GA, June 2-5, 2024. Presentation type: Poster.
  4. Mohan et al. Designer Solvents in Sustainable Chemistry: Physics-Informed Machine Learning for Accurate Prediction of Molecular Properties. Next-Generation Computational Chemistry: Innovation, Collaboration, and Impact at Georgia Institute of Technology, Atlanta, GA, March 21, 2025. Presentation type: Oral.

2024

  1. Mohan et al. Designer Solvents in Sustainable Chemistry: Physics-Informed Machine Learning for Accurate Prediction of Thermodynamic Properties. 28th ACS Annual Green Chemistry & Engineering Conference, Atlanta, GA, June 2-5, 2024. Presentation type: Poster.
  2. Mohan et al. Machine Learning Models Predict Carbon Dioxide Solubility in Chemically Reactive Deep Eutectic Solvents. at the ACS Spring Meeting 2024, New Orleans, March 17-21, 2024. Presentation type: Poster.
  3. Mohan et al. Quantum Chemistry-Driven Machine Learning Approach for the Prediction of the Surface Tension and Speed of Sound of Ionic Liquids. at the ACS Spring Meeting 2024, New Orleans, March 17-21, 2024. Presentation type: Oral.

2023

  1. Mohan et al. Accurate Prediction of Carbon Dioxide Capture by Deep Eutectic Solvents using Quantum Chemistry and a Neural Network. at the ACS Fall Meeting 2023, San Francisco, CA, August 12-17, 2023. Presentation type: Oral.

2019

  1. Mohan et al. Prediction of Solubility Parameters from Multiscale Molecular Simulations Approaches. at the Lignin Workshop, October 21-22, 2019, JBEI, CA. Presentation type: Oral.

2017

  1. Mohan et al. Dissolution Mechanism of Cellulose in Ionic Liquids: Understanding the Role of Protic and Aprotic Solvents by Molecular Dynamic Simulations. at Thermodynamics 2017, September 5-8, 2017, Edinburgh, UK. Presentation type: Poster.
  2. Mohan et al. Experimental and Quantum Chemical Calculations for the Dissolution of Cellulose/Hemicellulose in Ionic Liquids. at Gaussian16: Theory and Practice Workshop, 16-20 Jan 2017, SCUBE Scientific Software Solutions (P) Ltd, New Delhi, India. Presentation type: Poster.

2013

  1. Mohan et al. Solubility of monosaccharides and disaccharides in ionic liquids by COSMO-RS. at the International Conference on Membrane and Applications-13, 22-23 November 2013, CGCRI-CSIR, Kolkata, India. Presentation type: Oral.