Carbon dioxide reduction is an essential component of many prospective technologies for the renewable synthesis of carbon-containing fuels. Known catalysts for this reaction generally suffer from low energetic efficiency, poor product selectivity, and rapid deactivation. We show that the reduction of thick Au oxide films results in the formation of Au nanoparticles ("oxide-derived Au") that exhibit highly selective CO(2) reduction to CO in water at overpotentials as low as 140 mV and retain their activity for at least 8 h. Under identical conditions, polycrystalline Au electrodes and several other nanostructured Au electrodes prepared via alternative methods require at least 200 mV of additional overpotential to attain comparable CO(2) reduction activity and rapidly lose their activity. Electrokinetic studies indicate that the improved catalysis is linked to dramatically increased stabilization of the CO(2)(•-) intermediate on the surfaces of the oxide-derived Au electrodes.
The importance of tin oxide (SnO(x)) to the efficiency of CO(2) reduction on Sn was evaluated by comparing the activity of Sn electrodes that had been subjected to different pre-electrolysis treatments. In aqueous NaHCO(3) solution saturated with CO(2), a Sn electrode with a native SnO(x) layer exhibited potential-dependent CO(2) reduction activity consistent with previously reported activity. In contrast, an electrode etched to expose fresh Sn(0) surface exhibited higher overall current densities but almost exclusive H(2) evolution over the entire 0.5 V range of potentials examined. Subsequently, a thin-film catalyst was prepared by simultaneous electrodeposition of Sn(0) and SnO(x) on a Ti electrode. This catalyst exhibited up to 8-fold higher partial current density and 4-fold higher faradaic efficiency for CO(2) reduction than a Sn electrode with a native SnO(x) layer. Our results implicate the participation of SnO(x) in the CO(2) reduction pathway on Sn electrodes and suggest that metal/metal oxide composite materials are promising catalysts for sustainable fuel synthesis.
A family of three-dimensional chiral metal-formate frameworks of [NH(4)][M(HCOO)(3)] (M = Mn, Fe, Co, Ni, and Zn) displays paraelectric to ferroelectric phase transitions between 191 and 254 K, triggered by disorder-order transitions of NH(4)(+) cations and their displacement within the framework channels, combined with spin-canted antiferromagnetic ordering within 8-30 K for the magnetic members, providing a new class of metal-organic frameworks showing the coexistence of magnetic and electric orderings.
We present here a structural and mechanistic description of how a protein changes its fold and function, mutation by mutation. Our approach was to create 2 proteins that (i) are stably folded into 2 different folds, (ii) have 2 different functions, and (iii) are very similar in sequence. In this simplified sequence space we explore the mutational path from one fold to another. We show that an IgG-binding, 4؉␣ fold can be transformed into an albumin-binding, 3-␣ fold via a mutational pathway in which neither function nor native structure is completely lost. The stabilities of all mutants along the pathway are evaluated, key high-resolution structures are determined by NMR, and an explanation of the switching mechanism is provided. We show that the conformational switch from 4؉␣ to 3-␣ structure can occur via a single amino acid substitution. On one side of the switch point, the 4؉␣ fold is >90% populated (pH 7.2, 20°C). A single mutation switches the conformation to the 3-␣ fold, which is >90% populated (pH 7.2, 20°C). We further show that a bifunctional protein exists at the switch point with affinity for both IgG and albumin.evolution ͉ NMR ͉ protein design ͉ protein folding
We investigate the statistical mechanics of a gas of fractional statistics particles in 2+1 dimensions. In the case of statistics very close to Fermi statistics (statistical parameter θ=π(1−1/n), for large n), the effect of the statistics is a weak attraction. Building upon earlier RPA calculation of Fetter, Hanna, and Laughlin for the case n=2, we argue that for large n perturbation theory is reliable and exhibits superfluidity (or superconductivity after coupling to electromagnetism). We attempt to describe the order parameter for this superconducting phase in terms of “spontaneous breaking of commutativity of translations” as opposed to the usual pairing order parameters. The vortices of the superconducting anyon gas are charged, and superconducting order parameters of the usual type vanish. We investigate the characteristic P and T violating phenomenology.
To identify a simplified code for conformational switching, we have redesigned two natural proteins to have 88% sequence identity but different tertiary structures: a 3-␣ helix fold and an ␣/ fold. We describe the design of these homologous heteromorphic proteins, their structural properties as determined by NMR, their conformational stabilities, and their affinities for their respective ligands: IgG and serum albumin. Each of these proteins is completely folded at 25°C, is monomeric, and retains the native binding activity. The complete binding epitope for both ligands is encoded within each of the proteins. The IgG-binding epitope is functional only in the ␣/ fold, and the albumin-binding epitope is functional only in the 3-␣ fold. These results demonstrate that two monomeric folds and two different functions can be encoded with only 12% of the amino acids in a protein (7 of 56). The fact that 49 aa in these proteins are compatible with both folds shows that the essential information determining a fold can be highly concentrated in a few amino acids and that a very limited subset of interactions in the protein can tip the balance from one monomer fold to another. This delicate balance helps explain why protein structure prediction is so challenging. Furthermore, because a few mutations can result in both new conformation and new function, the evolution of new folds driven by natural selection for alternative functions may be much more probable than previously recognized.evolution ͉ folding ͉ NMR ͉ protein design ͉ protein structure
Three new tailor-made molecules (DPDCTB, DPDCPB, and DTDCPB) were strategically designed and convergently synthesized as donor materials for small-molecule organic solar cells. These compounds possess a donor-acceptor-acceptor molecular architecture, in which various electron-donating moieties are connected to an electron-withdrawing dicyanovinylene moiety through another electron-accepting 2,1,3-benzothiadiazole block. The molecular structures and crystal packings of DTDCPB and the previously reported DTDCTB were characterized by single-crystal X-ray crystallography. Photophysical and electrochemical properties as well as energy levels of this series of donor molecules were thoroughly investigated, affording clear structure-property relationships. By delicate manipulation of the trade-off between the photovoltage and the photocurrent via molecular structure engineering together with device optimizations, which included fine-tuning the layer thicknesses and the donor:acceptor blended ratio in the bulk heterojunction layer, vacuum-deposited hybrid planar-mixed heterojunction devices utilizing DTDCPB as the donor and C(70) as the acceptor showed the best performance with a power conversion efficiency (PCE) of 6.6 ± 0.2% (the highest PCE of 6.8%), along with an open-circuit voltage (V(oc)) of 0.93 ± 0.02 V, a short-circuit current density (J(sc)) of 13.48 ± 0.27 mA/cm(2), and a fill factor (FF) of 0.53 ± 0.02, under 1 sun (100 mW/cm(2)) AM 1.5G simulated solar illumination.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
334 Leonard St
Brooklyn, NY 11211
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.