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DigiChem Lab

AI-Driven Research in Computational Chemistry, Spectral Intelligence & Chemical Data Science

Bridging Chemistry, Computation, and Artificial Intelligence for Real-World Impact

About

The DigiChem Lab at the University of Mumbai focuses on integrating Computational Chemistry, Artificial Intelligence and data-driven approaches to solve complex chemical problems. Our work combines theoretical understanding with modern computational tools to develop efficient, scalable and intelligent solutions for chemical analysis and research. We develop cutting-edge platforms such as Spectral Hub which simplifies complex spectral data analysis and Q-Nebula which is an AI-powered quantum chemistry environment for molecular modelling and prediction. By combining chemometrics, quantum mechanics and machine learning, we aim to empower researchers, industries and academic institutions with intelligent tools that accelerate innovation and decision-making in chemistry.

Research Areas

Computational Chemistry

Quantum chemical modeling of molecular systems and reaction mechanisms

AI in Chemistry

Machine learning models for chemical prediction and data analysis

Spectral Intelligence

AI-based interpretation of IR, NMR, and Mass spectra

Process Automation

Digital tools for automating laboratory workflows

Key Innovation

Spectral-Hub

We are developing Spectral-Hub, an AI-powered platform that transforms spectral data into real-time chemical insights.

Unmix-X

1.Advanced signal separation

2.Extracts chemical patterns

3.Handles mixed datasets

Decode-X

1.Automated data interpretation

2.Generates chemical insights

3.Predicts structures

Predict-X

1.AI-based simulation

2.Predicts unknown spectra

3.Analyzes new compounds

Q-Nebula

Q-Nebula, AI-Powered Quantum Chemistry Platform, Q-Nebula is a cloud-enabled computational chemistry platform that integrates quantum mechanical calculations with AI/ML models to deliver faster and more scalable molecular insights.

Q-Core

High-accuracy simulations for:-

1. Molecular structure optimization

2. Energy calculations (HOMO-LUMO, band gaps)

3. Reaction pathway analysis

Q-Intellect

Hybrid AI models trained on quantum data to:-

1. Predict molecular properties instantly

2. Reduce computational cost significantly

3. Enable high-throughput virtual screening

Impact

Faster and more efficient chemical analysis

Reduced cost and time in laboratory workflows

Integration of AI into chemical research

Training students in modern digital chemistry

Leadership

Dr.Purav Badani

Associate Professor

Department of Chemistry

University of Mumbai

Our lab consists of passionate researchers and students working across computational chemistry, AI, and spectroscopy.

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