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Strong electron correlation plays an important role in transition-metal and heavy-metal chemistry, magnetic molecules, bond breaking, biradicals, excited states, and many functional materials, but it provides a significant challenge for modern electronic structure theory. The treatment of strongly correlated systems usually requires a multireference method to adequately describe spin densities and near-degeneracy correlation. However, quantitative computation of dynamic correlation with multireference wave functions is often difficult or impractical. Multiconfiguration pair-density functional theory (MC-PDFT) provides a way to blend multiconfiguration wave function theory and density functional theory to quantitatively treat both near-degeneracy correlation and dynamic correlation in strongly correlated systems; it is more affordable than multireference perturbation theory, multireference configuration interaction, or multireference coupled cluster theory and more accurate for many properties than Kohn-Sham density functional theory. This perspective article provides a brief introduction to strongly correlated systems and previously reviewed progress on MC-PDFT followed by a discussion of several recent developments and applications of MC-PDFT and related methods, including localized-active-space MC-PDFT, generalized active-space MC-PDFT, density-matrix-renormalization-group MC-PDFT, hybrid MC-PDFT, multistate MC-PDFT, spin-orbit coupling, analytic gradients, and dipole moments. We also review the more recently introduced multiconfiguration nonclassical-energy functional theory (MC-NEFT), which is like MC-PDFT but allows for other ingredients in the nonclassical-energy functional. We discuss two new kinds of MC-NEFT methods, namely multiconfiguration density coherence functional theory and machine-learned functionals.

We have screened an array of 23 metals deposited onto the metal–organic framework (MOF) NU-1000 for propyne dimerization to hexadienes under different reaction conditions for a total of ~1400 experiments. By a first-of-its-kind study utilizing data-driven algorithms and high-throughput experimentation (HTE) in MOF catalysis, yields on Cu-deposited NU-1000 were improved from 4.2% to 24.4%. Characterization of the most-performant catalysts reveal conversion to hexadiene to be due to the formation of large Cu nanoparticles, which is further supported by reaction mechanisms calculated with density functional theory (DFT). Our results demonstrate both the strengths and weaknesses of the HTE approach. As a strength, HTE excels at being able to find interesting and novel catalytic activity; any a priori theoretical approach would be hard-pressed to find success, as high-performing catalysts required highly specific operating conditions difficult to model theoretically, and initial naïve single-atom models of the active site did not prove representative of the nanoparticle catalysts responsible for conversion to hexadiene. As a weakness, our results show how the HTE approach must be designed and monitored carefully to find success; in our initial campaign (~six months and over half of the total experiments conducted) only minor catalytic performances (up to 4.2% yield) were achieved, which was only improved following a complete overhaul of our HTE approach and questioning our initial assumptions. Thus, the HTE approach is much less automated than it may seem, even if driven by machine learning algorithms – one must carefully design their HTE campaign to find success.

The synthesis of multimetallic compounds can enable the placement of two or more metals in close proximity, but efforts in this area are often hindered by reagent incompatibilities and a lack of selectivity. Here, we show that organometallic half-sandwich [Cp*M] (M = Rh, Ir) fragments (where Cp* is η5-pentamethylcyclopentadienyl) can be cleanly installed into metallomacrocyclic structures based on the workhorse diimine-monooxime-monooximato ligand system. Six new heterobimetallic compounds have been prepared to explore this synthetic chemistry, which relies on in situ protonolysis reactivity with precursor Ni(II) or Co(III) monometallic complexes in the presence of suitable [Cp*M] species. Solid-state X-ray diffraction studies confirm installation of the [Cp*M] fragments into the metallomacrocycles via effective chelation of the Rh(III) and Ir(III) centers by the nascent dioximato site. Contrasting with square-planar Ni(II) centers, the Co(III) centers prefer octahedral geometry in the heterobimetallic compounds, promoting bridging ligation of acetate across the two metals. Spectroscopic and electrochemical studies reveal subtle influences of the metals on each other's properties, consistent with the moderate M'···M distances of ca. 3.6-3.7 A in the modular compounds. Taken together, our results show that heterobimetallic complexes can be assembled with organometallic [Cp*M] fragments on the diimine-dioximato platform.

All the data necessary to reproduce and explore the results exhibited in "Large-Scale Benchmarking of Multireference Vertical-Excitation Calculations via Automated Active-Space Selection". This includes converged SA-CASSCF orbitals, eigenvectors, and metadata, as well as some example code on how to use our data with PySCF to reproduce our values.

The past decade has seen a great increase in the application of high-throughput computation to a variety of important problems in chemistry. However, one area which has been resistant to the high-throughput approach is multireference wave function methods, in large part due to the technicalities of setting up these calculations and in particular the not always intuitive challenge of active space selection. As we look toward a future of applying high-throughput computation to all areas of chemistry, it is important to prepare these methods for large-scale automation. Here, we propose a ranked-orbital approach to select active spaces with the goal of standardizing multireference methods for high-throughput computation. This method allows for the meaningful comparison of different active space selection schemes and orbital localizations, and we demonstrate the utility of this approach across 1120 multireference calculations for the excitation energies of small molecules. Our results reveal that it is helpful to distinguish the method used to generate orbitals from the method of ranking orbitals in terms of importance for the active space. Additionally, we propose our own orbital ranking scheme that estimates the importance of an orbital for the active space through a pair-interaction framework from orbital energies and features of the Hartree-Fock exchange matrix. We call this new scheme the "approximate pair coefficient" (APC) method and we show that it performs quite well for the test systems presented.

We introduce multiconfiguration data-driven functional methods (MC-DDFMs), a group of methods which aim to correct the total or classical energy of a qualitatively accurate multiconfigurational wave function using a machine-learned functional of some featurization of the wave function such as its density, on-top density, or both. On a data set of carbene singlet-triplet energy splittings, we show that MC-DDFMs are able to achieve near-benchmark performance on systems not used for training with a robust degree of active-space independence. Beyond demonstrating that the density and on-top density hold the information necessary to correct the singlet-triplet energy splittings of multiconfigurational wave functions, this approach shows great promise for the development of functionals for MC-PDFT because corrections to the classical energy appear to be more transferable to types of molecules not included in the training data than corrections to total energies such as those yielded by CASSCF or NEVPT2.

Structural data and U/Pb geochronology on zircon from central Fiordland, New Zealand show the role of pre-existing structural heterogeneities in the kinematic evolution of a newly discovered zone of transpression. The Straight River shear zone consists of steep zones of high strain that are superimposed onto older fabrics across a 10 × 80 km region. The older foliation formed during two periods of tectonism: contraction and magmatism of mostly Carboniferous (∼312–306 Ma) age and Early Cretaceous batholith emplacement ending by 113.4 ± 1.7 Ma followed by extension that ceased by 88.4 ± 1.2 Ma. The primary mechanism for the formation of steep shear zone foliations was the folding of these older fabrics. Conjugate crenulation cleavages associated with the folding record shortening at high angles to the shear zone boundaries. Fold axial surfaces and axial planar cleavages strike parallel to the shear zone with increasing strain as they progressively steepened to subvertical. In most areas, shear sense flips from oblique-sinistral (east-side-down component) to oblique-dextral (west-side-down) across zones of intermediate and high strain. High strain zones display subvertical mineral lineations, steep strike-slip faults and shear sense indicators that record strike-slip motion across the steep lineations. These patterns reflect triclinic transpression characterized by narrow zones of mostly strike-slip deformation and wide zones of mostly contraction. Zones of high strain align with offshore traces of late Tertiary strike-slip faults, suggesting that a previously undocumented component of late Tertiary shortening and strike-slip motion is accommodated within Fiordland.