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This work reports a combined experimental and computational study of the activation of an otherwise catalytically inactive cobalt complex, [Co(TIM)Br2]+, for aqueous nitrite reduction. The presence of phosphate buffer leads to efficient electrocatalysis, with rapid reduction to ammonium occurring close to the thermodynamic potential and with high Faradaic efficiency. At neutral pH, increasing buffer concentrations increase catalytic current while simultaneously decreasing overpotential, although high concentrations have an inhibitory effect. Controlled potential electrolysis and rotating ring-disk electrode experiments indicate that ammonium is directly produced from nitrite by [Co(TIM)Br2]+, along with hydroxylamine. Mechanistic investigations implicate a vital role for the phosphate buffer, specifically as a proton shuttle, although high buffer concentrations inhibit catalysis. These results indicate a role for buffer in the design of electrocatalysts for nitrogen oxide conversion. 

Molecular dynamics simulations often classically evolve the nuclear geometry on adiabatic potential energy surfaces (PESs), punctuated by random hops between energy levels in regions of strong coupling, in an algorithm known as surface hopping. However, the computational expense of integrating the geometry on a full-dimensional PES and computing the required couplings can quickly become prohibitive as the number of atoms increases. In this work, we describe a method for surface hopping that uses only important reaction coordinates, performs all expensive evaluations of the true PESs and couplings only once before simulating dynamics (offline), and then queries the stored values during the surface hopping simulation (online). Our Python codes are freely available on GitHub. Using photodissociation of azomethane as a test case, this method is able to reproduce experimental results that have thus far eluded ab initio surface hopping studies. 

Over the past century, the global concentration of environmental nitrate has increased significantly from human activity, which has resulted in the contamination of drinking water and aquatic hypoxia around the world, so the development of effective nitrate-reducing agents is urgent. This work compares three potential macrocycle-based nitrate reduction electrocatalysts: [Co(DIM)] 3+ , [Co(cyclam)] 3+ and [Co(TIM)] 3+ . Although all three complexes have similar structures, only [Co(DIM)] 3+ has been experimentally determined to be an active electrocatalyst for selective nitrate reduction to produce ammonia in water. While [Co(cyclam)] 3+ can reduce aqueous nitrate to ammonia and hydroxylamine at heavy metal electrodes, [Co(TIM)] 3+ is inactive for the reduction of nitrate. As an initial step to understanding what structural and electronic properties are important for efficient electrocatalysts for nitrate reduction, density functional theory (DFT) was employed to investigate the electronic structure of the three Co complexes, with the reduction potentials calibrated to experimental results. Moreover, DFT was employed to explore four different reaction mechanisms for the first steps of nitrate reduction. The calculated reaction barriers reveal how a combination of electron transfer in a redox non-innocent complex, substrate binding, and intramolecular hydrogen bonding dictates the activity of Co-based catalysts toward nitrate reduction. 

Electronic structure calculations on small systems such as H₂, H₂O, LiH, and BeH₂with chemical accuracy are still a challenge for the current generation of noisy intermediate‐scale quantum (NISQ) devices. One of the reasons is that due to the device limitations, only minimal basis sets are commonly applied in quantum chemical calculations, which allows one to keep the number of qubits employed in the calculations at a minimum. However, the use of minimal basis sets leads to very large errors in the computed molecular energies as well as potential energy surface shapes. One way to increase the accuracy of electronic structure calculations is through the development of small basis sets better suited for quantum computing. In this work, we show that the use of adaptive basis sets, in which exponents and contraction coefficients depend on molecular structure, provides an easy way to dramatically improve the accuracy of quantum chemical calculations without the need to increase the basis set size and thus the number of qubits utilized in quantum circuits. As a proof of principle, we optimize an adaptive minimal basis set for quantum computing calculations on an H₂molecule, in which exponents and contraction coefficients depend on the HH distance, and apply it to the generation of H₂potential energy surface on IBM‐Q quantum devices. The adaptive minimal basis set reaches the accuracy of the double‐zeta basis sets, thus allowing one to perform double‐zeta quality calculations on quantum devices without the need to utilize twice as many qubits in simulations. This approach can be extended to other molecular systems and larger basis sets in a straightforward manner.

 

Mechanistic investigations into electrocatalytic nitrate reduction by a cobalt complex reveal the critical role played by the flexible, redox-active ligand.