We improved (p)KREG models for an accurate representation of molecular potential energy surfaces (PESs) by including gradient information explicitly in their formalism. Our models are better or on par with other state-of-the-art machine learning models as we show on extensive …

(p)KREG Models for Accurate Molecular Potential Energy Surfaces Read more »

Alkyne-embedding [11]cycloparaphenylene ([11]CPPs) was functionalized with electron-donating, -neutral, and -withdrawing aryl substituents to yield a series of nanolassos via click chemistry. We used our state-of-the-art, artificial intelligence-enhanced quantum mechanical method 1 (AIQM1) to thoroughly analyze the electronic and photophysical properties of these …

Large Cycloparaphenylene Nanolassos Characterized with AIQM1 Read more »

Recent giant AI experiments such as ChatGPT and GPT-4 are increasingly becoming disruptive and have the potential of bringing lots of harm. These alarming developments have led to a call to pause such experiments. I show my support for such …

In realization of the big dangers posed by giant AI experiments, I sign an open letter calling for their pause Read more »

Our work published in Scientific Data presents the WS22 database, which contains 10 flexible organic molecules of increasing complexity in chemical composition and accessible conformations. The WS22 database provides 1.18 million equilibrium and non-equilibrium molecular geometries together with many quantum …

WS22 database, Wigner Sampling and geometry interpolation for configurationally diverse molecular datasets Read more »

In our work published in the Journal of Chemical Physics, we investigate the performance of AIQM1 on reaction barrier heights. Our benchmark results show that, with the built-in uncertainty quantification, the accuracy of confident AIQM1 predictions outperforms its baseline ODM2* method, …

Evaluating AIQM1 on Reaction Barrier Heights Read more »

Materials can simultaneously absorb not just one but two photons and molecules with strong two-photon absorption (TPA) are important in many fields such as unconverted laser, photodynamic therapy, and 3D printing. In our work published in Advanced Science (open access), …

Explaining and Predicting Two-Photon Absorption with Machine Learning Read more »

Artificial Intelligence Chemistry, a new chemical journal launched by Elsevier, with international peer review and online open access, is now officially open to submissions. MLatom founder and XACS co-founder Professor Pavlo O. Dral joins the Editorial Board of this new …

Prof. Pavlo O. Dral joins the Editorial Board of the new journal “Artificial Intelligence Chemistry” Read more »