Abstract. An accurate theoretical treatment of periodically driven quantum systems is crucial for various fields in the exact sciences, for instance Nuclear Magnetic Resonance (NMR) spectroscopy. Conv...

Position Summary The candidate will develop and apply solid-state NMR techniques to investigate biomolecular, biomaterial, and hard material systems.    Equal Employment Opportunity Statement All qual...

It has now been 100 years: Just over a century ago, George Uhlenbeck and Samuel Goudsmit, both graduate students at the University of Leiden, proposed a simple-looking explanation for the fine structure in the hydrogen atom spectrum that Schrödinger’s equation did not at the time predict. They tentatively ascribed to the electron an intrinsic angular momentum (the discussions at the time literally referred to “a spinning electron”) and used a relativistic effect that astronomers had already understood well but quantum mechanics yet lacked—spin-orbit coupling.

Companions Michael Andrew Fox, C.C. Burnaby, British Columbia and New York, New York, United States of America

Dr. Robert “Rob” Schurko (PhD’98) was a pioneering solid-state NMR scientist and inspiring mentor. His innovations advanced materials research, while personal warmth, musical talent and generosity lef...

Doty Scientific Inc (DSI) is a small company known worldwide for innovation and excellence in NMR and MRI instrumentation. Doty Scientific, located in an industrial park northeast of Columbia, SC, has...

Operando NMR spectroscopy of batteries: Improving sensitivity and selectivity Starting date: Before the end of 2026 Contract duration: 3 years, fully funded Closing date: Applications will be consider...

2026 Gateway NMR Conference

I am very happy to share that we have just released a new and improved version of our g-xTB model — now finally with fully analytic gradients! It took another nine months after the first g-xTB releas...

AI4Science and Science4AI

Deep learning delivers super-resolution for multidimensional NMR spectra.

We demonstrate a proof of concept for an approach to fast molecular crystal structure prediction using analogy to hypothetical crystal structures of related molecules. Our method constructs different valid analogues of predicted crystal structures of ...

Jiace Suna and Garnet Kin-Lic Chan (2026) Highlighted by Jan Jensen What this paper lacks in terms of punchy title, it makes up for in conte...

Protein-polymer conjugates (PPCs) are an important class of therapeutic macromolecules offering improvements in protein stability, circulation time, a…

Nuclear magnetic resonance (NMR) crystallography is a robust method for structure determination, but its reliance on density functional theory (DFT) for geometry refinement and tensor prediction limits its speed. While Machine Learning (ML) tools like ...

Machine-learning interatomic potentials (MLIPs) promise near ab initio accuracy at a fraction of the computational cost, unlocking atomistic simulations at scales previously inaccessible. Yet, their accuracy and generalizability remain critically limited ...

Chemical shift assignment in solids is a long and tedious process that relies on complex 1D and 2D NMR experiments. With prior knowledge of the 3D structure, this process can be significantly sped up...

Organic molecular crystals underpin technologies ranging from pharmaceuticals to organic electronics, yet predicting solid-state packing of molecules remains challenging because candidate generation i...

Density functional theory (DFT) is the most widely used method for calculating molecular properties; however, its accuracy is often insufficient for quantitative predictions. Coupled-cluster (CC) theo...

MagLab’s NMR Director described as extraordinary leader, first-rate scholar, and remarkable person.