Envision is released worldwide as Wallace Derricotte joins Entos to lead community building

Envision: Interactive Quantum Chemistry Free for Academic and Educational Users

Entos is excited to announce two major developments for Envision. First and foremost, we are delighted to be able to make Envision accessible to all academic researchers, educators, and students. Anyone with a valid email address from an educational establishment will be able to sign on to envision.entos.ai and use the resource for free, from March 31, 2021.

Secondly, we are delighted that Wallace Derricotte is joining Entos to focus on community development for researchers and educators who use Envision. Wallace is joining Entos from a faculty position at Morehouse College, and has become a leading chemistry educator through popular YouTube lectures and other online learning resources.

"Entos Envision is the gold standard for incorporating computational chemistry in the classroom. To have the freedom for students to run simple calculations and produce visualizations using a web browser is phenomenal. Envision is poised to be an indispensable tool in our educational arsenal for years to come, and I am excited to have the opportunity to lead this effort."

- Wallace Derricotte, Community Lead and Sales Engineer at Entos

Computational chemistry is central to the discovery effort of every major scientific industry, as well as academic research areas that include chemistry, biology, materials science, geology, and chemical engineering. By solving the equations of quantum mechanics, computational chemistry enables predictions of whether a potential drug molecule will be effective, how a new polymer will behave, how fast a reaction will occur, and much more.

Typical simulations on complex molecules take hours or days to perform, creating a slow discovery process in which a chemist endures long waits for any computational prediction. Entos has overcome this problem via breakthrough machine-learning algorithms that accelerate simulations by factors of 1000 or greater. The dramatic reductions in simulation time create a unique opportunity to change the mode of human interaction for computational chemistry. Inspired by these possibilities, Entos has created Envision with support from Schmidt Futures, a philanthropic initiative co-founded by Eric and Wendy Schmidt.

"We are excited to support this project that combines the latest research in computational chemistry and a plan for an open platform that can radically improve chemistry education and support researchers who need novel compounds. This style of innovation and broad impact is precisely what we seek to fund."

- Stuart Feldman, Schmidt Futures

Entos Envision uses cloud technology to integrate interactive simulation with the discovery and learning process, vastly simplifying the user experience and yielding new opportunities for research and education. Made possible by a generous grant from Amazon Web Services (AWS), Entos Envision will be freely available to any academic or educational user, with no cost and no hassle beyond creating an account at envision.entos.ai. Entos Envision is conceived as a cloud-based platform that brings together rigorous quantum mechanics and machine learning to enable chemists to predict molecular properties and to discover promising new molecular systems, without the need for expert computational chemistry training.

"We are tremendously excited to have Wallace Derricotte join us to advance the research and educational impact of Envision and other Entos software tools. Our vision is to revolutionize the discovery of molecules and materials by fundamentally changing the way in which we discuss, interact with, and design for chemistry."

- Tom Miller, co-founder and CEO of Entos

Entos Inc., a company based in Pasadena, California, develops technologies for molecular discovery. Founded in April 2020, Entos has built a team of over 25 world-class scientists and engineers, and the company continues to grow as it pursues ambitious challenges at the interface of chemistry, biology, and machine learning.