Artificial Intelligence & Information Technology

We focus on the development of advanced AI Models and software with tailored properties to meet specific application needs. Our research integrates chemistry, AI-Models, and Coding to design AI & IT solution that cope with current and future challenges, enhance performance, and enable new technologies.

Applications include Machine Learning Models for simulation, Management Databases, and Codes to operate devices. Our team uses cutting-edge coding techniques and programming tools to push the boundaries of material science.

Machine‑Learning Powered Adsorption Suite for Real‑Time Qe Prediction and Model Fitting

🔬 Research Problem

Accurate prediction of adsorption capacity (Qe) is essential for designing efficient sorbents and optimizing batch processes.
Traditional adsorption analysis depends on manual curve fitting, static datasets, and slow model comparisons.
Real‑time adsorption data is often complex and noisy, making interpretation difficult without advanced computational tools.
Predicting Qe for new samples or batch experiments typically requires repeated laboratory trials.
Researchers lack an integrated platform that can learn from experimental data, identify best‑fit sorption models, and visualize results in one workflow.

✅ Proposed Solution

An advanced Adsorption Suite was developed that integrates machine learning with classical sorption models.
Real‑time adsorption data is used to train predictive algorithms, enabling the system to learn adsorption behavior directly from experiments.
The suite predicts Qe values for both individual samples and batch datasets, reducing the need for repeated lab work.
Built‑in sorption models automatically fit the data and identify the best‑fit isotherm.
The platform generates high‑quality visual graphs for instant interpretation of trends and prediction accuracy.
This integrated solution accelerates the development of high‑performance sorbents.

Remotely Operated Titration System for Safe, Accessible, and Scalable Chemistry Education

🔬 Research Problem

Real-time chemistry experiments can be hazardous for young students and early-stage chemists.
Physically impaired learners often cannot safely manipulate lab equipment.
Large groups struggle to perform individual experiments in traditional labs.
Virtual labs lack real chemical behavior, while robotic labs remove human interaction.
A balanced system was needed that preserves real chemistry while enabling safe remote operation.

✅ Proposed Solution

A fully functional remotely operated titration setup was developed.
The system performs complete titration workflows:
- Solution preparation
- Standardization
- Conductometric titration
- Potentiometric titration
- Colorimetric titration
Students control every step remotely through an interactive interface.
A live camera feed allows real-time observation of the experiment.
This hybrid approach delivers safe, accessible, and scalable chemistry education.

Integrated Lab Management Database for Smart, Efficient, and Traceable Laboratory Operations

🔬 Research Problem

Laboratories generate large volumes of user data, equipment logs, chemical inventories, and usage records.
Tracking instrument availability becomes inefficient as lab size grows.
Manual inventory management leads to missing chemicals and expired reagents.
Incomplete usage records complicate maintenance planning.
Labs needed a unified digital system to centralize data and streamline operations.

✅ Proposed Solution

A comprehensive Lab Management Database was developed.
The system maintains user profiles, equipment inventory, chemical inventory, and usage logs.
Instrument reservation and availability tracking ensure efficient scheduling.
Real-time chemical usage monitoring supports accurate stock management.
Equipment usage records help plan maintenance and ensure responsible operation.
This centralized platform modernizes laboratory management.