The Journal of Physical Chemistry Letters最新文献

Hamiltonian simulation is one of the most anticipated applications of quantum computing. Quantum circuit depth for implementing Hamiltonian simulation is commonly time dependent using Trotter-Suzuki product formulas so that long time quantum dynamic simulations (QDSs) become impratical for near-term quantum processors. Hamiltonian simulation based on Cartan decomposition (CD) provides an appealing scheme for QDSs with fixed-depth circuits, while it is limited to a time-independent Hamiltonian. In this work, we generalize this CD-based Hamiltonian simulation algorithm for studying time-dependent systems by combining it with variational quantum algorithms. The time-dependent and time-independent parts of the Hamiltonian are treated by using variational and CD-based Hamiltonian simulation algorithms, respectively. As such, this hybrid Hamiltonian simulation requires only fixed-depth quantum circuits to handle time-dependent cases while maintaining a high accuracy. We apply this new algorithm to study the response of spin and molecular systems to δ-kick electric fields and obtain accurate spectra for these excitation processes.

With the power conversion efficiency (PCE) of perovskite solar cells (PSCs) exceeding 26.7%, achieving further enhancements in device performance has become a key research focus. Here, we investigate the impact of electrical doping in the perovskite layer using the drift-diffusion equation-based device physics model, coupled with a self-developed equivalent circuit model. Our results demonstrate that electrical doping can increase the PCE from 24.78% to >28%. In-depth theoretical analysis reveals that these improvements in performance are driven by the modulation of carrier recombination processes through doping, leading to significant increases in the open-circuit voltage and fill factor. Additionally, we explore the influence of physical parameters on device performance. Our study identifies an optimal doping concentration range from 1.0 × 10¹⁷ to 1.0 × 10¹⁹ cm^–3 and a transport layer mobility of >0.01 cm² V^–1 s^–1. This work provides a theoretical foundation for the development of ultra-high-performance PSCs through targeted electrical doping strategies.

The high concentration of proteins and other biological macromolecules inside biomolecular condensates leads to dense and confined environments, which can affect the dynamic ensembles and the time scales of the conformational transitions. Here, we use atomistic molecular dynamics (MD) simulations of the intrinsically disordered low complexity domain (LCD) of the human fused in sarcoma (FUS) RNA-binding protein to study how self-crowding inside a condensate affects the dynamic motions of the protein. We found a heterogeneous retardation of the protein dynamics in the condensate with respect to the dilute phase, with large-amplitude motions being strongly slowed by up to 2 orders of magnitude, whereas small-scale motions, such as local backbone fluctuations and side-chain rotations, are less affected. The results support the notion of a liquid-like character of the condensates and show that different protein motions respond differently to the environment.

Characterization of the surface of iridium oxide (IrO_x) materials is of crucial importance to understand catalysts for the oxygen evolution reaction (OER) in low-temperature water electrolysis. While much of our current knowledge is based on well-defined single-crystal surfaces, surface-sensitive techniques like X-ray photoelectronic spectroscopy (XPS) are relevant to characterize the nanostructures considered. In this work, we describe a simple approach to use oxygen 1s spectra as an identifier of the amorphous/crystalline characteristics of iridium oxide structures from purely amorphous to purely crystalline. This conceptual approach was validated on seven commercially available materials. The presence of oxygen-associated defects in the surface moieties/species is shown even for purely crystalline materials with defect concentration increasing with greater amorphous character. This methodology provides us with an accessible ex situ descriptor of the catalyst surface as a baseline for further studies of the impact on catalytic properties.

One-pot hydrothermal synthesis assisted by sodium citrate and citric acid is developed to fabricate mixed-phased MoVTeNbO_x catalysts with different phase compositions for selective oxidation of propane to acrylic acid. Structures of various catalysts are comprehensively characterized. Interfacial interactions occur among the M1 and M2 phases of mixed-phase MoVTeNbO_x catalysts to exert synergistic effects on the selective production of acrylic acid. Various mixed-phase MoVTeNbO_x catalysts exhibit the same type of active site on the M1-phase component, with a significantly enhanced ability to adsorb and activate propane. The propane conversion increases linearly with the density of surface site for propane adsorption, while the propene selectivity increases linearly with the density of surface site for propene adsorption. Among the synthesized catalysts, a MoVTeNbO_x catalyst composed of 35.3 wt % M1 phase, 19.2 wt % M2 phase, and 45.7 wt % amorphous phase exhibits the largest density of active site and consequently the best catalytic performance with 38.9% propane conversion and 71.2% acrylic acid selectivity at 380 °C.

Despite the demand for nanoscale thermal management technologies of material surfaces and interfaces using organic molecules, heat transport properties at the single molecular level remain elusive due to the experimental difficulty of measuring temperature at the nanoscopic scale. Here we show how chemical bonding modes can affect the heat transport properties of single molecules. We focused on four molecular systems: benzylthiol linked to another phenyl group by either a triple (compound 1), double (3), or amide (4) bond and a common linear alkanethiol (2), all of which are nearly identical in molecular length. We prepared binary self-assembled monolayers (SAMs) using 1 as a common reference in combination with 2–4 and investigated their relative heat transport properties using scanning thermal microscopy (SThM). Two-dimensional temperature mapping of the binary SAMs showed that C≡C and C=C bonds provide more effective pathways for heat transport compared to C–C bonds. Since the amide molecule has resonance structures with C=N double bond character, we expected that its heat transport properties would be comparable to those of the thiols containing triple or double bonds. However, the heat transport properties of this molecule prevailed over the others, most likely due to the formation of additional heat transport pathways caused by intermolecular hydrogen bonding. These findings may provide important guidelines for the design of organic materials for nanoscale thermal management.

Memristors have been extensively studied for tremendous potential for future neuromorphic computing hardware applications because of their ability to imitate biological synaptic processes. Herein, we report an interfacial memristor based on a Ga₂O₃/Nb:SrTiO₃ heterojunction that shows stable bipolar resistive switching behavior, long retention time, and high switching ratio. The conductance of the Au/Ga₂O₃/Nb:SrTiO₃/In memristor can be gradually modulated under the voltage sweep mode as well as positive and negative pulse voltage stimulations, respectively, thus realizing the long-term potentiation/depression characteristics of the simulated biological synapse. A neural network based on the prepared memristor was built to recognize the handwritten picture data set with a recognition accuracy of 92.78% by using the NeuroSimV3.0 platform. Our work indicates that the Ga₂O₃/Nb:SrTiO₃ heterojunction memristor has significant potential in a neuromorphic computing system.

The hybridization of plasmonic energy and charge donors with polymeric acceptors is a possible means to overcome fast internal relaxation that limits potential photocatalytic applications for plasmonic nanomaterials. Polyaniline (PANI) readily hybridizes onto gold nanorods (AuNRs) and has been used for the sensitive monitoring of local refractive index changes. Here, we use single-particle spectroscopy to quantify a previously unreported plasmon damping mechanism in AuNR–PANI hybrids while actively tuning the PANI chemical structure. By eliminating contributions from heterogeneous line width broadening and refractive index changes, we identify efficient resonance energy transfer (RET) between AuNRs and PANI. We find that RET dominates the optical response in our AuNR–PANI hybrids during the dynamic tuning of the spectral overlap of the AuNR donor and PANI acceptor. Harnessing RET between plasmonic nanomaterials and an affordable and processable polymer such as PANI offers an alternate mechanism toward efficient photocatalysis with plasmonic nanoparticle antennas.

Considering the augmentation of new generation energy harvesting devices and applications of electron–hole separation therein, conversion of 3D cubic CsPbBr₃ perovskite nanocrystals into 2D-platelets through ligand–ligand hydrophobic interactions has been conceived here. Cationic surfactants with various chain length coated the gold nanoclusters (AuNCs) that interact with oleic acid (OA) and oleylamine (OAm) coated 3D CsPbBr₃ nanocrystals to disintegrate the crystallinity of the perovskites and reformation of AuNC-grafted 2D-platelets of unusually large size. The planar perovskite-derivatives act as an exciton donor to the embedded AuNCs through photoinduced electron transfer (PET). This process is controlled by the optimum surfactant chain length. Transient absorption spectroscopy shows that the fastest radical growth time (4 ps) was with the 14-carbon containing tail of the surfactant, followed by the 16-carbon (45 ps) and the 12-carbon (290 ps) ones. PET is administered by the energy gaps of the participating candidates that control the transition dynamics. Our findings can be a potential tool to develop metal nanocluster-based hybrid 2D perovskite-derived platelets for optoelectronic applications.