We report the bulk properties and ab initio thermodynamics surface free energies for α-Fe2O3(0001) using density functional theory (DFT) with calculated Hubbard U values for chemically distinct surface Fe atoms. There are strong electron correlation effects in hematite that are not well-described by standard DFT. A better description can be achieved by using a DFT + U approach in which U represents a Hubbard on-site Coulomb repulsion term. While DFT + U calculations result in improved predictions of the bulk hematite band gap, surface free energies using DFT + U total energies result in surface structure predictions that are at odds with most experimental results. Specifically, DFT + U predictions stabilize a ferryl termination relative to an oxygen termination that is widely reported under a range of experimental conditions. We explore whether treating chemically distinct surface Fe atoms with different U values can lead to improved bulk and surface predictions. We use a linear response technique to derive specific U d values for all Fe atoms in several slab geometries. We go on to add a Coulomb correction, U p, to better describe the hybridization between the Fe d and oxygen p orbitals, accurately predicting the structural and electronic properties of bulk hematite. Our results show that the site-specific U d is a key factor in obtaining theoretical results for surface stability that are congruent with the experimental literature results of α-Fe2O3(0001) surface structure. Finally, we use a model surface reaction to trace how the various DFT + U methods affect the surface electronic structure and heterogeneous reactivity.

The utilization of substoichiometric amounts of commercially available nickel(II) triflate as an activator in the reagent-controlled glycosylation reaction for the stereoselective construction of biologically relevant targets containing 1,2-cis-2-amino glycosidic linkages is reported. This straightforward and accessible methodology is mild, operationally simple and safe through catalytic activation by readily available Ni(OTf)2 in comparison to systems employing our previously in-house prepared Ni(4-F-PhCN)4(OTf)2. We anticipate that the bench-stable and inexpensive Ni(OTf)2, coupled with little to no extra laboratory training to set up the glycosylation reaction and no requirement of specialized equipment, should make this methodology be readily adopted by non-carbohydrate specialists. This report further highlights the efficacy of Ni(OTf)2 to prepare several bioactive motifs, such as blood type A-type V and VI antigens, heparin sulfate disaccharide repeating unit, aminooxy glycosides, and α-GalNAc-Serine conjugate, which cannot be achieved in high yield and α-selectivity utilizing in-house prepared Ni(4-F-PhCN)4(OTf)2 catalyst. The newly-developed protocol eliminates the need for the synthesis of Ni(4-F-PhCN)4(OTf)2 and is scalable and reproducible. Furthermore, computational simulations in combination with 1H NMR studies analyzed the effects of various solvents on the intramolecular hydrogen bonding network of tumor-associated mucin Fmoc-protected GalNAc-threonine amino acid antigen derivative, verifying discrepancies found that were previously unreported.

Computationally efficient and accurate quantum mechanical approximations to solve the many-electron Schrödinger equation are crucial for computational materials science. Methods such as coupled cluster theory show potential for widespread adoption if computational cost bottlenecks can be removed. For example, extremely dense k-point grids are required to model long-range electronic correlation effects, particularly for metals. Although these grids can be made more effective by averaging calculations over an offset (or twist angle), the resultant cost in time for coupled cluster theory is prohibitive. We show here that a single special twist angle can be found using the transition structure factor, which provides the same benefit as twist averaging with one or two orders of magnitude reduction in computational time. We demonstrate that this not only works for metal systems but also is applicable to a broader range of materials, including insulators and semiconductors.

In this article, we characterize the behavior of water on the surface of a diverse group of carbohydrates and attempt to determine the role of saccharide size, linkage, and branching as well as secondary structure on the dynamics and structure of water at the surface. In order to better understand the similarities and differences in the behavior of the solvent on the carbohydrate surface, we explore residence times, rotational correlation functions, local solvent occupancy numbers, and diffusivities. We find that due to the differences in secondary structure water residence times are longer and translational and rotational dynamics are retarded when in contact with wide helices and branched sugars. In the case of extended helices and smaller oligosaccharides, water dynamics is faster and less hindered. This indicates that branching, the type of linkage between monomers, and the anomeric configuration all play a major role in determining the structure and dynamics of water on the surface of carbohydrates.

In common with many high-accuracy electronic structure methods, the initiator adaptation of full configuration interaction quantum Monte Carlo (i−FCIQMC) has difficulty treating realistic systems with large numbers of electrons. This barrier has prevented the application of i−FCIQMC to questions of catalysis that, even for the simplest of models, require high-accuracy modeling of several features of the electronic structure, such as strong and dynamic correlation, and localized vs. delocalized bonding. We here present a fully-quantum embedded version of i−FCIQMC , which we apply to calculate the bond dissociation energy of an ionic bond (LiH) and a covalent bond (HF) physisorbed to a benzene molecule. The embedding is performed using a recently-developed Huzinaga projection operator approach, which affords good synergy with i−FCIQMC by minimizing the number of orbitals in the calculation. We find that, without embedding, i−FCIQMC struggles to converge these calculations due to their substantial system sizes and a lack of error cancellation between reactants and products. With embedding, the i−FCIQMC calculation converges straightforwardly to CCSD(T) benchmarks. Our results suggest that embedded i−FCIQMC will be able treat system sizes well beyond our current reach (even though embedding introduces an error). We discuss how embedding might be improved (and thus the introduced error reduced) using i−FCIQMC energies as benchmarks.