Integrated Calendar

Accurate prediction of electronic properties of open-shell transition metal complexes is essential for materials design and catalysis. Nevertheless, the properties that make these materials and molecules so compelling also make them extremely challenging to study accurately with any computational model. Although density functional theory (DFT) remains the method of choice for its balance of speed and accuracy in computational screening, semi-local approximations in density functional theory (DFT), such as the generalized gradient approximation (GGA), suffer from many electron self-interaction errors that causes them to predict erroneous spin states and geometries, barrier heights and dissociation energies, and orbital energies, to name a few. I will outline our recent efforts to both understand and correct these errors with a focus on predictive modeling of transition metal chemistry : i) We describe how common approximations to recover the derivative discontinuity (i.e., DFT+U and global or range separated hybrids) affect the density properties of transition metal complexes and correlated solids with respect to exact references, ii) We demonstrate recovery of the flat-plane condition that is a union of the requirement of piecewise linearity with electron removal or addition as well as unchanged energy when changing the spin of an electron in isoenergetic orbitals. We accomplish this at no computational cost over semi-local DFT by building from scratch our judiciously-modified DFT (jmDFT) functionals designed to oppose errors inherent in semi-local functionals. We show the connection to but divergence of these functional forms from hybrid expressions and standard DFT+U explain why both common approximations increase static correlation errors. We also present fundamental expressions for determining these parameters, mitigating any empiricism in the method. iii) Finally, time permitting, I will describe our efforts to overcome DFT inaccuracies through the development of data-driven structure-method relationships, including in artificial neural networks that can predict sensitivity of spin-state ordering in transition metal complexes to changes in the exchange-correlation functional.

What happens to electrons in a metal when they are illuminated? This fundamental problem is a driving force in shaping modern physics since the discovery of the photo-electric effect. In recent years, this problem resurfaced from a new angle, owing to developments in the field of nano-plasmonics, where metallic nanostructures give rise to resonantly enhanced local electromagnetic fields (surface plasmons). Presumably, these plasmons can transfer their energy to the electrons in the metal very efficiently, creating “hot electrons”, i.e. energetic electrons out of equilibrium. Such energetic electrons have been demonstrated to be useful in a variety of ways, most recently in catalysis of chemical reactions.

Or have they?

In this talk we argue that what appears to be hot-electron-mediated photo-catalysis is really a simple heating effect. We present a theory for plasmonic hot-electron generation, which takes into account non-equilibrium as well as thermal effects. Specifically, we consider the effect of both photons and phonons on the electron distribution function, and calculate self-consistently the full electron distribution and the increase in electron and lattice temperatures above ambient conditions (as observed experimentally), thus going well beyond the limit of existing theories. Calculating the efficiency of hot-electron generation, we find that it is extremely small, and most power goes into heating. We use this theory to re-interpret data from central experiments claiming hot-electron generation, and find that the data fits remarkably a simple theory of heating. Finally, we suggest control experiments to further test our conclusions, and discuss the prospect of using the hot electrons for photocatalysis.

Protein synthesis is linked to cell proliferation and its deregulation contributes to diseases such as cancer. eIF1A plays a key role in scanning and AUG selection and differentially affects translation of distinct mRNAs. Its unstructured N-terminal tail (NTT) is frequently mutated in several malignancies. Here, we show that eIF1A is essential for cell proliferation and cell-cycle progression. Ribosome-profiling of eIF1A knockdown cells revealed a substantial reduction in protein synthesis, with particular enrichment of cell-cycle mRNAs. The downregulated genes are predominantly characterized by lengthy 5’UTR. On the other hand, eIF1A depletion caused a broad stimulation of initiation in 5’UTRs at near-cognate AUG. Importantly, cancer-associated eIF1A-NTT mutants augment the positive effect of eIF1A on long 5’UTR while hardly affecting AUG selection. Our findings suggest that reduced binding of eIF1A NTT mutants to the ribosome retains its open state and facilitate scanning of long 5’UTR-containing cell cycle genes.