Speaking to a full audience at HBKU, Dr. Meghali Chopra detailed the science behind her business concept and the journey of transforming ideas from an academic to a business setting.

The identification of a recipe for a specific etch process is time consuming and expensive, requiring extensive experiments and metrology. Here we present two modules in SandBox StudioTM, SB-Bayesian and SBNeuralNet, to accelerate the prediction and optimization of etch recipes for across the wafer uniformity.

A methodology is presented to virtually predict etch profiles on flexible substrates across multi-dimensional process spaces using a minimal number of calibration experiments.

SandBox Semiconductor is an Austin-based startup aiming to address this problem by revolutionizing process development for Semiconductor manufacturing.

Meghali Chopra is CEO of Sandbox Semiconductor, which aims to solve a bottleneck in semiconductor manufacturing: the long development cycles necessary to create new chips.

Meghali and Sonali Chopra will represent The University of Texas at Austin to compete against some of world’s top universities for more than $1 million in prizes at the 17th annual Rice Plan Competition at Rice University in Houston.

More than $1 billion is spent on etch and deposition semiconductor process development per year. Developed from her five years of doctoral research, Chopra’s software accelerates the creation of etch and deposition recipes by a factor of three, saving development costs and speeding time to market for semiconductor products by 66 percent.