Transition metal complexes are ubiquitous in biology and chemical catalysis, yet they remain difficult to accurately describe with ab initio methods due to the presence of a large degree of dynamic electron correlation, and, in some cases, strong static correlation which results from a manifold of low-lying states. Progress has been hindered by a scarcity of high quality gas-phase experimental data, while exact ab initio predictions are usually computationally unaffordable due to the large size of the relevant complexes.In this work, we present a data set of 34 tetrahedral, square planar, and octahedral 3d metal-containing complexes with gas-phase ligand-dissociation energies that have reported uncertainties of ≤ 2 kcal/mol. We perform all-electron phaseless auxiliaryfield quantum Monte Carlo (ph-AFQMC) calculations utilizing multi-determinant trial wavefunctions selected by a blackbox procedure. We compare the results with those from density functional theory (DFT) with the B3LYP, B97, M06, PBE0, ωB97X-V, and DSD-PBEP86/2013 functionals, and a localized orbital variant of coupled cluster theory with single, double, and perturbative triple excitations (DLPNO-CCSD(T)). We find mean averaged errors of 1.09 ± 0.28 kcal/mol for our best ph-AFQMC method, vs 2.89 kcal/mol for DLPNO-CCSD(T) and 1.57 -3.87 kcal/mol for DFT. We find maximum errors of 2.96 ± 1.71 kcal/mol for our best ph-AFQMC method, vs 9.15 kcal/mol for DLPNO-CCSD(T) and 5.98 -13.69 kcal/mol for DFT. The reasonable performance of a number of DFT functionals is in stark contrast to the much poorer accuracy previously demonstrated for diatomic species, suggesting a moderation in electron correlation due to ligand coordination. However, the unpredictably large errors for a small subset of cases with both DFT and DLPNO-CCSD(T) methods leave cause for concern, especially in light of the unreliability of common multi-reference indicators. In contrast, the robust and, in principle, systematically improvable results of ph-AFQMC for these realistic complexes establish the method as a useful tool for elucidating the electronic structure of transition metal-containing complexes and predicting their gas-phase properties.

Triplet−triplet annihilation upconversion (TTA-UC) is an unconventional photophysical process that yields high-energy photons from low-energy incident light and offers pathways for innovation across many technologies, including solar energy harvesting, photochemistry, and optogenetics. Within aromatic organic chromophores, TTA-UC is achieved through several consecutive energy conversion events that ultimately fuse two triplet excitons into a singlet exciton. In chromophores where the singlet exciton is roughly isoergic with two triplet excitons, the limiting step is the triplet−triplet annihilation pathway, where the kinetics and yield depend sensitively on the energies of the lowest singlet and triplet excited states. Herein we report up to 40-fold improvements in upconversion quantum yields using molecular engineering to selectively tailor the relative energies of the lowest singlet and triplet excited states, enhancing the yield of triplet−triplet annihilation and promoting radiative decay of the resulting singlet exciton. Using this general and effective strategy, we obtain upconversion yields with red emission that are among the highest reported, with remarkable chemical stability under ambient conditions.

State-of-the art photoactivation strategies in chemical biology provide spatiotemporal control and visualization of biological processes. However, using high energy light (l < 500 nm) for substrate or photocatalyst sensitization can lead to background activation of photoactive small molecule probes and reduce its efficacy in complex biological environments. Here we describe the development of targeted aryl azide activation via deep red light (l = 660 nm) photoredox catalysis and its use in photocatalyzed proximity labeling. We demonstrate that aryl azides are converted to triplet nitrenes via a novel redox-centric mechanism and show that its spatially localized-formation requires both red light and a photocatalyst-targeting modality. This technology was applied in different colon cancer cell systems for targeted protein environment labeling of epithelial cell adhesion molecule (EpCAM). We identified a small subset of proteins with previously known and unknown association to EpCAM, including CDH3, a clinically relevant protein that shares high tumor selective expression with EpCAM.

The accurate ab initio prediction of ionization energies is essential to understanding the electrochemistry of transition metal complexes in both materials science and biological applications. However, such predictions have been complicated by the scarcity of gas phase experimental data, the relatively large size of the relevant molecules, and the presence of strong electron correlation effects. In this work, we apply all-electron phaseless auxiliary-field quantum Monte Carlo (ph-AFQMC) utilizing multideterminant trial wave functions to six metallocene complexes to compare the computed adiabatic and vertical ionization energies with experimental results. We find that ph-AFQMC yields mean absolute errors (MAEs) of 1.69 ± 1.02 kcal/mol for the adiabatic energies and 2.85 ± 1.13 kcal/mol for the vertical energies. We also carry out density functional theory (DFT) calculations using a variety of functionals, which yields MAEs of 3.62−6.98 kcal/mol and 3.31−9.88 kcal/mol, as well as one variant of localized coupled cluster calculations (DLPNO-CCSD(T 0 ) with moderate PNO cutoffs), which has MAEs of 4.96 and 6.08 kcal/mol, respectively. We also test the reliability of DLPNO-CCSD(T 0 ) and DFT on acetylacetonate (acac) complexes for adiabatic energies measured in the same manner experimentally, and we find higher MAEs, ranging from 4.56 to 10.99 kcal/mol (with a different ordering) for DFT and 6.97 kcal/mol for DLPNO-CCSD(T 0 ). Finally, by utilizing experimental solvation energies, we show that accurate reduction potentials in solution for the metallocene series can be obtained from the AFQMC gas phase results.

Phaseless auxiliary-field quantum Monte Carlo (ph-AFQMC) has recently emerged as a promising method for the production of benchmark-level simulations of medium- to large-sized molecules because of its accuracy and favorable polynomial scaling with system size. Unfortunately, the memory footprints of standard energy evaluation algorithms are nontrivial, which can significantly impact timings on graphical processing units (GPUs) where memory is limited. Previous attempts to reduce scaling by taking advantage of the low-rank structure of the Coulombic integrals have been successful but exhibit high prefactors, making their utility limited to very large systems. Here we present a complementary cubic-scaling route to reduce memory and computational scaling based on the low rank of the Coulombic interactions between localized orbitals, focusing on the application to ph-AFQMC. We show that the error due to this approximation, which we term localized-orbital AFQMC (LO-AFQMC), is systematic and controllable via a single variable and that the method is computationally favorable even for small systems. We present results demonstrating robust retention of accuracy versus both experiment and full ph-AFQMC for a variety of test cases chosen for their potential difficulty for localized-orbital-based methods, including the singlet–triplet gaps of the polyacenes benzene through pentacene, the heats of formation for a set of Platonic hydrocarbon cages, and the total energy of ferrocene, Fe­(Cp)2. Finally, we reproduce our previous result for the gas-phase ionization energy of Ni­(Cp)2, agreeing with full ph-AFQMC to within statistical error while using less than 1/15th of the computer time.

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Electronic structure theories such as AFQMC can accurately predict the low-lying excited state energetics of organic chromophores involved in triplet–triplet annihilation upconversion. A novel class of benzothiadiazole annihilators is discovered.