The Journal of Physical Chemistry Letters最新文献

While catalytic reactions of biomolecular processes play an indispensable role in life, extracting the underlying molecular picture often remains challenging. Based on ab initio simulations of the self-cleavage reaction of hairpin ribozyme, mode-decomposed infrared spectra, and cosine similarity analysis to correlate the product with reactant IR spectra, we demonstrate a strategy to extract molecular details from characteristic spectral changes. Our results are in almost quantitative agreement with the experimental IR band library of nucleic acids and suggest that the spectral range of 800–1200 cm^–1 is particularly valuable to monitor self-cleavage. Importantly, the cosine similarities also disclose that IR peaks subject to slight shifts due to self-cleavage might be unrelated, while strongly shifting resonances can correspond to the same structural dynamics. This framework of correlating complex IR spectra at the molecular level along biocatalytic reaction pathways is broadly applicable.

The rapid advancement of machine learning has revolutionized quite a few science fields, leading to a surge in the development of highly efficient and accurate materials discovery methods. Recently, predictions of multiple related properties have received attention, with a particular emphasis on spectral properties, where the electronic density of states (DOS) stands out as the fundamental data with enormous potential to advance our understanding of crystalline materials. Leveraging the power of the Transformer framework, we introduce an Atomic Positional Embedding-Based Transformer (APET), which surpasses existing state-of-the-art models for predicting ab initio DOS. APET utilizes atomic periodical positions as its positional embedding, which incorporates all of the structural information in a crystal, providing a more complete and accurate representation. Furthermore, the interpretability of APET enables us to discover the underlying physical properties of materials with greater precision and accuracy.

The suboptimal carrier dynamics at the heterointerface between the perovskite and charge transport layer severely limit further performance enhancement of the state-of-the-art perovskite solar cells (PSCs). Herein, we completely map charge carrier extraction and recombination kinetics over a broad time range at buried electron-selective heterointerfaces via ultrafast transient technologies. It is revealed that the heterointerfaces carefully contain the electronic processes of free charge generation in perovskite within ∼2.8 ps, relaxation process of trap-state induced electron capturing less than ∼10.0 ps, electron extraction from perovskite to SnO₂ within ∼194 ps, trap-assisted recombination within ∼2047 ps, and recombination between back-injected electrons and remaining holes within ∼8.4 ns. Moreover, we further demonstrate that the inserted poly(vinyl alcohol) (PVA) thin layer can effectively enhance the electron extraction from perovskite to SnO₂, block the undesired electron back injection, and significantly suppress the nonradiative recombination, contributing to the improved device parameters of photovoltage and fill factor. This work sheds light on charge-transfer limitations at the perovskite buried heterointerface and provides an effective guide of ideal heterointerface design for promoting charge transfer and improving PSC performance.

Miniaturized coherent light sources on the nanoscale are highly desired for on-chip photonics integration. However, when approaching the diffraction limit, the sub-wavelength-scale all-dielectric lasers are difficult to realize due to the trade-off between lasing performance and physical size. Especially for a thin-film laser, usually an externally complex cavity is required to provide the necessary optical feedback. Herein, we successfully shrink the MAPbBr₃ perovskite thin-film laser to sub-wavelength scale (300 nm) with simplified cavity design using only an ultraviolet glue layer and a quartz glass. The morphology quality and the gain properties of the film are enhanced by introducing ionic liquid. Consequently, the stable and low-threshold single-mode laser with a highly linear polarization degree of 78.6% and a narrow line width of 0.35 nm is achieved under two-photon excitation. The excellent single-mode laser with sub-wavelength scale and ultrasimplified structure could provide a facile and versatile platform for future integrated optoelectronic devices.

Quantum computers have emerged as a promising platform to simulate strong electron correlation that is crucial to catalysis and photochemistry. However, owing to the choice of a trial wave function employed in the variational quantum eigensolver (VQE) algorithm, accurate simulation is restricted to certain classes of correlated phenomena. Herein, we combine the spin-flip (SF) formalism with the unitary coupled cluster with singles and doubles (UCCSD) method via the quantum equation-of-motion (qEOM) approach to allow for an efficient simulation of a large family of strongly correlated problems. We show that the developed qEOM-SF-UCCSD/VQE method outperforms its UCCSD/VQE counterpart for simulation of the cis–trans isomerization of ethylene, and the automerization of cyclobutadiene and the predicted qEOM-SF-UCCSD/VQE barrier heights are in a good agreement with the experimentally determined values. The developments presented herein will further stimulate the investigation of this approach for simulations of other types of correlated/entangled phenomena on quantum computers.

Proton exchange membrane (PEM) fuel cells are a promising and environmentally friendly device to directly convert hydrogen energy into electric energy. However, water flooding and gas transport losses degrade its power density owing to structural issues (cracks, roughness, etc.) of the microporous layer (MPL). Here, we introduce a green material, supercritical fluid exfoliated graphene (s-Gr), to act as a network to effectively improve gas transport and water management. The assembled PEM fuel cell achieves a power density of 1.12 W cm^–2. This improved performance is attributed to the reduction of cracks and the slip of water and gas on the s-Gr surface, in great contrast to the nonslip behavior on carbon black (CB). These findings open up an avenue to solve the water and gas transport problem in porous media by materials design with low friction and provide a new opportunity to boost high power density PEM fuel cells.

We present a polarization model incorporating coupled fluctuating charges and point inducible dipoles that is able to accurately describe the dipole polarizabilities of small hydrocarbons and, for sufficiently large graphene nanoflakes, reproduce the classical image potential of an infinite conducting sheet. When our fluctuating charge model is applied to the hexagonal carbon nanoflake C₆₀₀₀₀ we attain excellent agreement with the image potential and induced charge distribution of a conducting sheet. With the inclusion of inducible dipole terms, the model predicts an image plane of z_im = 1.3334 a₀, which falls in line with prior estimates for graphene. We consider the case of two charges placed on opposite sides of C₆₀₀₀₀ and find that the fluctuating charge model reproduces classical electrostatics once again. By testing opposing and similar signs of the external charges, we conclude that an atomically thin molecule or extended system does not fully screen their interaction.

An analytical description of the separation probability of a geminate pair in organic semiconductors is given. The initial diffusion of “hot” twins is anomalously strong due to energy disorder. This circumstance significantly increases the photogeneration quantum yield at low temperatures and weakens its temperature dependence relative to predictions of the Onsager model, in agreement with Monte Carlo and experimental results.