Kulik Research Group

Deep Principle, a startup founded by Kulik group alumni Chenru Duan and Haojun Jia, has named Prof. Kulik Chief Scientist! Read more about it here !

Congratulations to David, Weiliang, and the rest of the team on the acceptance of their manuscript describing QuantumPDB in JCIM! Read more about it here !

Heather joined the Latent Space podcast for a discussion ‘Why There Is No “AlphaFold for Materials” — AI for Materials Discovery’ ! Check it out here !

We introduce pyEF, a software package for computing molecular electric fields, electrostatic interaction energies, and electrostatic potentials from quantum mechanical (QM) atom-centered multipole expansions with atom-wise decomposable contributions. We demonstrate the computational efficiency and accuracy of this QM-derived electric field evaluation tool through several tests. To assess the infl…

Mechanophores offer unique opportunities in chemistry and material science, yet current mechanophores are often limited by low reactivity, irreversible transformation, or poor thermal stability. Here, we report the computational discovery of a new class of Cu 2+ complex mechanophores comprising two tridentate scorpionate ligands that reversibly switch from octahedral to square-planar coordination…

A noncanonical radical oxygenase mechanism enables the biosynthesis of widespread cardenolide toxins in plants Publication Sci. Adv., in press

Congratulations to Melissa Manetsch on the acceptance of her manuscript describing the pyEF software package for electric field analysis in JCTC! Read more about it here !

What makes a suitable metal-organic framework linker? Discovery from a general chemical database

Congratulations to Fangzi Liu on the acceptance of his manuscript on confinement catalysis in Chem! Reac more about it here!

Biological systems utilize continuous energy inputs, such as light or chemical fuels, to sustain non-equilibrium states essential for life. In contrast, synthetic systems typically dissipate energy toward equilibrium, revealing a fundamental thermodynamic disparity compared to biological systems. Here, we demonstrate that mechanical force, delivered via ball-milling, serves as a unique energy sou…

Engineering in-plane anisotropy in 2D materials via surface-bound ligands

Husain receives GRC Poster Award Congratulations to Husain Adamji for winning a poster prize at the AI for Materials, Energy, and Chemical Sciences (AIMECS) GRC meeting! Congratulations to Husain Adamji for winning a poster prize at the AI for Materials, Energy, and Chemical Sciences (AIMECS) GRC meeting!

Artificial intelligence (AI) is poised to transform heterogeneous catalysis, opening avenues for catalytic materials discovery. By uncovering intricate patterns in high-dimensional data, AI has been reshaping our pursuit of sustainable catalytic processes across the energy, environmental and chemical sectors. This promise, however, hinges on overcoming fundamental barriers, including limitations …

Accurate estimates of the spin-splitting energy (SSE) are essential for proper modeling of transition metal complex (TMC) catalysts and functional materials but are notoriously challenging to achieve. Over a large set of over 450 TMCs, we demonstrate that adding Hartree–Fock exchange (HFX) to semilocal density functionals (e.g., PBE or SCAN) in a system-specific fashion provides the flexibility t…

Congratulations to many group members past and present who contributed to the development of molSimplify 2.0! The manuscript describing this work has been published in JCIM! Read more about it here!

We provide an overview of core molSimplify code functionality and recent updates that enhance its capabilities for automated molecular and materials modeling. We describe the mol3D and atom3D classes, which store atomic and bonding information for a wide range of functions, including reading, modifying, and characterizing molecular geometries from common file formats. Enhancements to decoration a…

Breaking the Conversion-Selectivity Constraint in Methane Oxidation through Product Stability Control

Transparent Reporting for Agentic Catalysis Enabled by Artificial Intelligence (TRACE-AI): Community Guidelines and A Publication Checklists

Customizing the toughness of polymer networks independently of their chemical composition and topology remains an unsolved challenge. Traditionally, polymer network toughening is achieved by using specialized monomers or solvents or adding secondary networks/fillers that substantially alter the composition and may limit applications. Here we report a class of force-responsive molecules—tetrafunct…

molSimplify: Structure Generation 1 This video tutorial describes the basics of building structures with molSimplify. This video tutorial describes the basics of building structures with molSimplify.