Quinones participate in diverse electron transfer and proton-coupled electron transfer processes in chemistry and biology. To understand the relationship between these redox processes, an experimental study was carried out to probe the 1 e– and 2 e–/2 H+ reduction potentials of a number of common quinones. The results reveal a non-linear correlation between the 1 e– and 2 e–/2 H+ reduction potentials. This unexpected observation prompted a computational study of 134 different quinones, probing their 1 e– reduction potentials, pKa values, and 2 e–/2 H+ reduction potentials. The density functional theory calculations reveal an approximately linear correlation between these three properties and an effective Hammett constant associated with the quinone substituent(s). However, deviations from this linear scaling relationship are evident for quinones that feature intramolecular hydrogen bonding in the hydroquinone, halogen substituents, charged substituents, and/or sterically bulky substituents. These results, particularly the different substituent effects on the 1 e– versus 2 e–/2 H+ reduction potentials, have important implications for designing quinones with tailored redox properties.
We report the first example of a sulfinato Fe(III) complex acting as a highly active electrocatalyst for proton reduction. The sulfinate binds to the metal through oxygen, resulting in a seven-membered chelate ring that is likely hemilabile during catalysis. Proton reduction occurs at -1.57 V versus Fc/Fc(+) in CH3CN with an ic/ip = 13 in CH3CN (kobs = 3300 s(-1)) and an overpotential of 800 mV. The catalysis is first order with respect to [catalyst] and second order with respect to [trifluoracetic acid]. An 11% increase in catalytic activity is observed in the presence of water, suggesting that sulfinate moieties are viable functional groups for aqueous proton reduction catalysts.
The search for novel forms of computing to the dominant von Neumann model-based approach is important as it will enable different classes of problems to be solved. Molecular computers are a promising alternative to semiconductor-based computers given their potential biocompatibility and cost advantages. The vast space of chemical reactions makes molecules a tunable, scalable, and energy-efficient computational vehicle. In molecular computers, memory and processing units can be combined into a single, inherently parallelized device. Here, we present a microdroplet array molecular computer to solve combinatorial optimization problems by employing an Ising Hamiltonian to map problems heuristically to droplet-droplet interactions. The droplets represent binary digits and problems are encoded in intra-and inter-droplet reactions. We propose two implementations: first, a hybrid classical-molecular computer that enforces inter-droplet constraints in a classical computer and, second, a purely molecular computer where the problem is entirely pre-programmed in the nearest-neighbor droplet reactions.
Direct tracking of lithium ions with time and spatial resolution can provide an important diagnostic tool for understanding mechanisms in lithium ion batteries. A fluorescent indicator of lithium ions, 2-(2-hydroxyphenyl)naphthoxazole, was synthesized and used for real-time tracking of lithium ions via widefield fluorescence microscopy. The fluorophore can be excited with visible light and was shown to enable quantitative determination of the lithium ion diffusion constant in a microfluidic model system for a plasticized polymer electrolyte lithium battery. The use of widefield fluorescence microscopy for in situ tracking of lithium ions in batteries is discussed.
The interplay between micromorphology and electronic properties is an important theme in organic electronic materials. Here, we show that a spirofluorenefunctionalized boron-dipyrromethene (BODIPY) with an alkyl norbornyl tail self-assembles into nanoparticles with qualitatively different properties as compared to the polymerized species. Further, the nanoparticles exhibit a host of unique emissive properties, including photobrightening, a blue satellite peak, and spectral diffusion. Extensive photophysical characterization, including single-particle imaging and spectroscopy, and time-resolved fluorescence, coupled with electronic structure calculations based on an experimentally determined crystal structure, allow a mechanism to be developed. Specifically, BODIPY chromophores are observed to form quasi-two-dimensional layers, where stacking of unit cells adds either J-aggregate character or H-aggregate character depending on the direction of the stacking. Particularly strongly H-coupled domains show the rare process of emission from an upper exciton state, in violation of Kasha's rule, and result in the blue satellite peak. The spatial heterogeneity of structure thus maps onto a gradient of photophysical behavior as seen in single-particle imaging, and the temporal evolution of structure maps onto fluctuating emissive behavior, as seen in single-particle spectroscopy. Taken together, this system provides a striking example of how physical structure and electronic properties are intertwined, and a rare opportunity to use one to chart the other.
Two complementary measurements, fluorescence polarization anisotropy and aggregation-induced emission, allow for in situ optical monitoring of polymerization reaction progress in droplets across varying temporal regimes of the reaction.
The search for novel forms of computing that show advantages as alternatives to the dominant von-Neuman model-based computing is important as it will enable different classes of problems to be solved. By using droplets and room-temperature processes, molecular computing is a promising research direction with potential biocompatibility and cost advantages. In this work, we present a new approach for computation using a network of chemical reactions taking place within an array of spatially localized droplets whose contents represent bits of information. Combinatorial optimization problems are mapped to an Ising Hamiltonian and encoded in the form of intra- and inter- droplet interactions. The problem is solved by initiating the chemical reactions within the droplets and allowing the system to reach a steady-state; in effect, we are annealing the effective spin system to its ground state. We propose two implementations of the idea, which we ordered in terms of increasing complexity. First, we introduce a hybrid classical-molecular computer where droplet properties are measured and fed into a classical computer. Based on the given optimization problem, the classical computer then directs further reactions via optical or electrochemical inputs. A simulated model of the hybrid classical-molecular computer is used to solve boolean satisfiability and a lattice protein model. Second, we propose architectures for purely molecular computers that rely on pre-programmed nearest-neighbour inter-droplet communication via energy or mass transfer.
The search for novel forms of computing that show advantages as alternatives to the dominant von-Neuman model-based computing is important as it will enable different classes of problems to be solved. By using droplets and room-temperature processes, molecular computing is a promising research direction with potential biocompatibility and cost advantages. In this work, we present a new approach for computation using a network of chemical reactions taking place within an array of spatially localized droplets whose contents represent bits of information. Combinatorial optimization problems are mapped to an Ising Hamiltonian and encoded in the form of intra- and inter- droplet interactions. The problem is solved by initiating the chemical reactions within the droplets and allowing the system to reach a steady-state; in effect, we are annealing the effective spin system to its ground state. We propose two implementations of the idea, which we ordered in terms of increasing complexity. First, we introduce a hybrid classical-molecular computer where droplet properties are measured and fed into a classical computer. Based on the given optimization problem, the classical computer then directs further reactions via optical or electrochemical inputs. A simulated model of the hybrid classical-molecular computer is used to solve boolean satisfiability and a lattice protein model. Second, we propose architectures for purely molecular computers that rely on pre-programmed nearest-neighbour inter-droplet communication via energy or mass transfer.
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