Frequently Asked Questions

Computational chemistry leverages computational techniques to predict properties of molecules, complexes and materials in experimental settings. These properties range from basic features (e.g., the geometric structure of a certain molecule) to how materials react with each other and their environment (e.g., how they behave when we shine light on them or what happens if we mix them with other materials).

Computational chemistry is emerging as a powerful tool for material design and discovery; it allows us to predict how materials behave before we test them experimentally, which can be slow and expensive. For example, in a search for new materials with a desired property (e.g., a drug that can cure a disease), we typically need to screen through millions of compounds to find the most promising ones. However, by using computational techniques, it helps narrow the search and guides us as to what are the few most promising candidates that can then be tested experimentally.
Quantum chemistry is a branch of computational chemistry. It predicts material properties by explicitly taking into account how electrons within a certain material interact with each other and their environment. Since these small particles follow the laws of quantum mechanics, these methods are called “quantum chemistry”. Quantum chemical methods tend to be more accurate than other computational chemistry methods in describing how materials react with each other, but they are also more computationally expensive. Thus, powerful algorithms like those developed by Good Chemistry are needed for application to a wider range of real-world problems.
No! In fact, most quantum chemists have historically focused on “how can we simulate quantum mechanical properties of materials using good old classical computers?” Since the 1980s, there was a hypothesis that if we had quantum computers, they may help us do quantum chemistry faster or more accurately. And it is probably the case. But for that, we need scalable quantum computing hardware and we are a few years away from that. For the time being, classical computers and novel algorithms that are designed to simulate chemistry will be powerful tools with a lot of potential to change material discovery as we know it!
Historically, computational chemistry calculations come with a tradeoff between speed and accuracy — to speed up a calculation, approximations are required which can reduce the final accuracy. The holy grail for computational chemistry is to achieve high-accuracy and high-throughput simulations. Our team seeks to achieve this through the scaling power available in the cloud, highly optimized cloud-native computational chemistry algorithms, as well as AI-driven acceleration of those simulations. Once quantum computers are ready, they will add another tool to our portfolio, helping us achieve that vision.
QEMIST Cloud is Good Chemistry’s cloud-native computational chemistry platform. It is built for computational chemistry developers and is designed to enable high-accuracy, high-throughput simulations on demand. It offers users cloud-optimized implementations of quantum chemistry algorithms, eliminates the need to worry about the hardware infrastructure on which computation is run, and is designed to capture the power of emerging tools in computational chemistry, such as AI and, down the road, quantum computers.

QEMIST Cloud helps multiple industries accelerate materials, including the chemical industry, pharmaceutical industry, advanced materials, academic research, oil and gas, automotive, and any industry or academic group that studies chemistry for developing new materials/drugs.

Any researcher or organization with a focus on chemistry can leverage QEMIST Cloud.

You or your organization can easily apply to be considered for the Beta platform. Researchers wishing to run simulations using QEMIST Cloud only need basic knowledge of python in order to leverage its API and execute simulations — regardless of complexity. There is no need to set up different computational chemistry packages or worry about high performance on the platform — QEMIST Cloud manages it all for you in the backend.

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