Bridging Chemistry and Machine Learning for a New Era of Scientific Discovery

Chemolytics was created from a belief that the next great breakthroughs in chemistry will be fueled by a fusion of human curiosity, machine learning, and scientific precision, offering researchers and students a new way to understand, model, and advance the molecular world.

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The Story Behind Chemolytics

Chemolytics stands for a new kind of science: one that keeps the hands in the lab, the mind in the data, and the eyes on what’s next.

I built Chemolytics because I believe the future of chemistry lies in combining human expertise with the power of computation. Experimental science will always be the foundation of discovery — no algorithm or model can replace hands-on work in the lab. But machine learning can transform how we approach chemical research: by revealing hidden patterns, accelerating processes, analyzing results with greater precision, and guiding experimentation toward more informed and innovative directions.

Chemolytics is the product of years spent at the intersection of chemistry and computational science. It’s a platform for researchers who see machine learning not as a replacement for the lab, but as a tool to unlock new possibilities within it. My mission is to act as a bridge between these two worlds — bringing modern computational methods into chemical research to advance our scientific understanding faster, smarter, and with greater depth.

This is more than a platform. It’s a commitment to a new way of thinking: where chemistry and machine learning work together to push the boundaries of discovery.

What Chemolytics Offers

Knowledgebase

Learn the mathematical and computational foundations behind machine learning — including linear algebra, calculus, probability, and optimization — all framed with applications in chemistry and scientific thinking.

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Research Insights

Get concise, curated breakdowns of key research papers in AI-driven chemistry. We distill complex methods, results, and ideas into clear insights you can actually use or build upon.

Read Insights

Projects & Case Studies

See how machine learning and computational methods are applied to real chemical problems. These hands-on examples and narratives bridge theory and practice — from catalysis to reaction prediction.

Browse Projects

Tools & Resources

Explore curated datasets, code notebooks, visualization tools, and tutorials designed to accelerate your computational chemistry research and model development.

Browse resources

Who Chemolytics Is For

Students

Build a strong foundation in machine learning and artificial intelligence with a chemistry-first perspective. Whether you're new to computational methods or exploring AI-driven research for the first time, Chemolytics provides step-by-step guidance through concepts, tools, and case studies tailored to your scientific growth.

Scientists & Academics

Bridge the gap between experimental research and modern computation. This platform supports researchers looking to integrate machine learning into their work — from data analysis to catalyst design — without losing the depth and rigor of traditional chemical inquiry.

Curious & Independent Learners

For anyone driven by intellectual curiosity, Chemolytics offers a space to explore how data, models, and molecules intersect. Whether you're self-taught, interdisciplinary, or transitioning fields, you'll find structured resources and real-world applications that make machine learning in chemistry accessible and meaningful.

About Martin Solomon

Driven by a love for molecules and models, I built Chemolytics to help others learn what I had to teach myself — with purpose, persistence, and precision.

I’m Martin Solomon — a chemist by training, and a self-taught machine learning practitioner by necessity. I hold a BS in Chemistry, but most of what I know about scientific computing, data analysis, and machine learning came from years of self-study, late nights, and a refusal to give up when the path wasn’t clear.

Chemolytics is more than a website for me — it’s the platform I wish I had when I was just starting out. A space where chemistry meets code. Where ideas are broken down, not dumbed down. Where you can explore real science without needing permission from a lab, a degree, or an institution.

I built Chemolytics to help students, researchers, and curious minds find their way into the future of chemistry — a future that’s computational, data-driven, and still deeply human.

This is my life’s work. And I’m just getting started.

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Chemolytics' Vision

We’re entering an era where the most powerful chemists won’t just run experiments — they’ll model them, optimize them, and accelerate them with computation.

I built Chemolytics because I believe chemistry is evolving — and we need a new kind of scientist to lead that shift. One who understands molecules and models, who can think both experimentally and algorithmically.

Chemolytics is my answer to that need: a platform where chemists can learn machine learning not as hype, but as a tool for deeper thinking, faster discovery, and smarter science. Over time, I want Chemolytics to become the go-to resource for chemists who want to stay relevant, rigorous, and ready for what’s next.