Construction and Multifunctional Photonic Applications of Light Absorption-Enhanced Silicon-Based Schottky Coupled Structures.

To expand the detection capabilities of silicon (Si)-based photodetector and address key scientific challenges such as low light absorption efficiency and short carrier lifetime in Si-based graphene photodetector. This work introduces a novel Si-based Schottky coupled structure by in situ growth of 3D-graphene and molybdenum disulfide quantum dots (MoS QDs) on Si substrates using chemical vapor deposition (CVD) and plasma-enhanced chemical vapor deposition (PECVD) techniques. The findings validate the "dual-enhanced absorption" effect, enhancing the understanding of the mechanisms that improve optoelectronic performance.

Enhancing Burning Rate of Ammonium Nitrate by Ammonia Borane: Mechanism from Reactive Molecular Dynamics Simulation.

The development of ammonium nitrate (AN)/ammonia borane (AB) as a green propellant is crucial for their applicability in different engines. This study investigates the release patterns of small products, particularly nitrogen-containing molecules, during the initial pyrolysis of AN/AB at low and high pressures using ReaxFF MD simulations. Compared with pure AN, the addition of AB gives the hybrid system enhanced reactivity, leading to faster decomposition and higher energy release.

Nitrogen-Doped 3D-Graphene Advances Near-Infrared Photodetector for Logic Circuits and Image Sensors Overcoming 2D Limitations.

The limitations of two-dimensional (2D) graphene in broadband photodetector are overcome by integrating nitrogen (N) doping into three-dimensional (3D) structures within silicon (Si) via plasma-assisted chemical vapor deposition (PACVD) technology. This contributes to the construction of vertical Schottky heterojunction broad-spectrum photodetectors and applications in logic devices and image sensors. The natural nanoscale resonant cavity structure of 3D-graphene enhances photon capture efficiency, thereby increasing photocarrier generation.

Polymer-Unit Graph: Advancing Interpretability in Graph Neural Network Machine Learning for Organic Polymer Semiconductor Materials.

The graph representation of complex materials plays a crucial role in the field of inorganic and organic materials investigations for developing data-centric materials science, such as those using graph neural networks (GNNs). However, the currently prevalent GNN models are primarily employed for investigating periodic crystals and organic small molecule data, yet they still encounter challenges in terms of interpretability and computational efficiency when applied to polymer monomers and organic macromolecules data. There is still a lack of graph representation of organic polymers and macromolecules specifically tailored for GNN models to explore the structural characteristics.

Symmetry-Triggered Tunable Phosphorescence Lifetime of Graphene Quantum Dots in a Solid State.

Studying the phosphorescent mechanisms of carbon nanostructures synthesized by the "bottom-up" approach is key to understanding the structure modulation and the interfacial properties of carbon nanostructures. In this work, the relationships among symmetry of precursors in the "bottom-up" synthesis, structures of products, and phosphorescence lifetimes of graphene quantum dots (GQDs) are studied. The symmetry matching of precursors in the formation of a D graphene-like framework is considered the key factor in controlling the separability of sp domains in GQDs.

Polaron interfacial entropy as a route to high thermoelectric performance in DAE-doped PEDOT:PSS films.

Enhancing the thermoelectric transport properties of conductive polymer materials has been a long-term challenge, in spite of the success seen with molecular doping strategies. However, the strong coupling between the thermopower and the electrical conductivity limits thermoelectric performance. Here, we use polaron interfacial occupied entropy engineering to break through this intercoupling for a PEDOT:PSS (poly(3,4-ethylenedioxythiophene)-poly(4-styrenesulfonate)) thin film by using photochromic diarylethene (DAE) dopants coupled with UV-light modulation.

The Synergistic Effect on the Mimetic Optical Structure of Feline Eyes toward Household Health Monitoring of Acute and Chronic Diseases.

A breakthrough in the performance of bionic optical structures will only be achieved if we can obtain an in-depth understanding of the synergy mechanisms operating in natural optical structures and find ways to imitate them. In this work, inspired by feline eyes, an optical substrate that takes advantage of a synergistic effect that occurs between resonant and reflective structures was designed. The synergistic effect between the reflective and resonant components leads to a Raman enhancement factor (EF) of 1.

Fast proton transport enables the magnetic relaxation response of graphene quantum dots for monitoring the oxidative environment .

A magnetic relaxation switch (MRS) that targets small molecules such as HO is difficult to realize because of the small size of the targets, which cannot gather enough MRS probes to form aggregates and generate a difference in magnetic relaxation times. Therefore, the development of small molecule-targeted MRS is strongly dependent on changes in the interfacial structure of the probe, which modulates the proton transport behavior near the probe. Herein, functionalized graphene quantum dots (GQDs) consisting of GQDs with disulfide bonds, polyethylene glycol (PEG), and paramagnetic Gd were used as the MRS probe to sense HO.

Bio-inspired Double Angstrom-Scale Confinement in Ti-deficient Ti O Nanosheet Membranes for Ultrahigh-performance Osmotic Power Generation.

Osmotic power, a clean energy source, can be harvested from the salinity difference between seawater and river water. However, the output power densities are hampered by the trade-off between ion selectivity and ion permeability. Here we propose an effective strategy of double angstrom-scale confinement (DAC) to design ion-permselective channels with enhanced ion selectivity and permeability simultaneously.

Accelerated deprotonation with a hydroxy-silicon alkali solid for rechargeable zinc-air batteries.

Transition metal oxides are promising electrocatalysts for zinc-air batteries, yet surface reconstruction caused by the adsorbate evolution mechanism, which induces zinc-ion battery behavior in the oxygen evolution reaction, leads to poor cycling performance. In this study, we propose a lattice oxygen mechanism involving proton acceptors to overcome the poor performance of the battery in the OER process. We introduce a stable solid base, hydroxy BaCaSiO, onto the surfaces of PrBaCaCoO perovskite nanofibers with a one-step exsolution strategy.

Facet Engineering-Induced Construction of NiP/ZnInS Heterostructures for Boosted Photocatalytic CO Reduction.

Facet engineering was realized to enhance the CO photoreduction performance of the NiP/ZnInS heterostructure, in which the commonly exposed (1 0 2) face of ZnInS was converted to the (1 0 1) face due to the unique properties of the phosphide. The variation in the crystal plane strengthened the intense interfacial contact between NiP and ZnInS, resulting in the promotion of utilization and absorption efficiency for incident light and boosting the surface reaction rate. Combined with the significant metallicity of NiP, inhibited recombination and strengthened transfer efficiency were achieved, leading to an obvious enhancement of photoreduction activity over NiP/ZnInS compared to pure samples.

Polymer-Unit Fingerprint (PUFp): An Accessible Expression of Polymer Organic Semiconductors for Machine Learning.

High-performance organic semiconductors (OSCs) can be designed based on the identification of functional units and their role in the material properties. Herein, we present a polymer-unit fingerprint (PUFp) generation framework, "Python-based polymer-unit-recognition script" (PURS), to identify the subunits "polymer unit" in the polymer and generate polymer-unit fingerprint (PUFp). Using 678 collected OSC data, machine learning (ML) models can be used to determine structure-mobility relationships by using PUFp as a structural input, and the classification accuracy reaches 85.

Tailored BiVO Photoanode Hydrophobic Microenvironment Enables Water Oxidative H O Accumulation.

Direct photoelectrochemical 2-electron water oxidation to renewable H O production on an anode increases the value of solar water splitting. BiVO has a theoretical thermodynamic activity trend toward highly selective water oxidation H O formation, but the challenges of competing 4-electron O evolution and H O decomposition reaction need to overcome. The influence of surface microenvironment has never been considered as a possible activity loss factor in the BiVO -based system.

Molecular dynamic insight into octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX) and the nano-HMX decomposition mechanism.

Herein, we demonstrate the use of large-scale reactive molecular dynamics simulations to identify the influence of nanostructures, size effects, and temperature for the decomposition processes of octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX). The bulk-phase and six types of HMX nanoparticle (30-70 Å) systems were investigated at two high temperatures (2000 K and 3000 K). The evolution of the potential energy (PE) and total number of molecules (TM) of HMX crystals and their six nanoparticle systems were analyzed and addressed, and it was revealed that the nanostructure has a great accelerative effect on the thermal decomposition of HMX.

Theoretical Studies on the Role of Guest in α-CL-20/Guest Crystals.

The contradiction between energy and safety of explosives is better balanced by the host-guest inclusion strategy. To deeply analyze the role of small guest molecules in the host-guest system, we first investigated the intermolecular contacts of host and guest molecules through Hirshfeld surfaces, 2-D fingerprint plots and electrostatic interaction energy. We then examined the strength and nature of the intermolecular interactions between CL-20 and various small molecules in detail, using state-of-the-art quantum chemistry calculations and elaborate wavefunction analyses.

Investigation of a Highly Sensitive Surface-Enhanced Raman Scattering Substrate Formed by a Three-Dimensional/Two-Dimensional Graphene/Germanium Heterostructure.

Three-dimensional graphene (3D-graphene) is used in surface-enhanced Raman spectroscopy (SERS) because of its plasmonic nanoresonator structure and good ability to interact with light. However, a thin (3-5 nm) layer of amorphous carbon (AC) inevitably appears as a template layer between the 3D-graphene and object substrate when the 3D-graphene layer is synthesized, weakening the enhancement factor. Herein, two-dimensional graphene (2D-graphene) is employed as a template layer to directly synthesize 3D-graphene on a germanium (Ge) substrate via plasma-assisted chemical vapor deposition, bypassing the formation of an AC layer.

Ordered Element Distributed C N Quantum Dots Manipulated Crystallization Kinetics for 2D CsPbI Solar Cells with Ultra-High Performance.

Two-dimensional (2D) CsPbI is developed to conquer the phase-stability problem of CsPbI by introducing bulky organic cations to produce a steric hindrance effect. However, organic cations also inevitably increase the formation energy and difficulty in crystallization kinetics regulation. Such poor crystallization process modulation of 2D CsPbI leads to disordered phase-arrangement, which impedes the transport of photo-generated carriers and worsens device performance.

5-IP is a GPCR messenger mediating neural control of synaptotagmin-dependent insulin exocytosis and glucose homeostasis.

5-diphosphoinositol pentakisphosphate (5-IP) is a signalling metabolite linked to various cellular processes. How extracellular stimuli elicit 5-IP signalling remains unclear. Here we show that 5-IP in β cells mediates parasympathetic stimulation of synaptotagmin-7 (Syt7)-dependent insulin release.

Prediction and Classification of Formation Energies of Binary Compounds by Machine Learning: An Approach without Crystal Structure Information.

It is well believed that machine learning models could help to predict the formation energies of materials if all elemental and crystal structural details are known. In this paper, it is shown that even without detailed crystal structure information, the formation energies of binary compounds in various prototypes at the ground states can be reasonably evaluated using machine-learning feature abstraction to screen out the important features. By combining with the "white-box" sure independence screening and sparsifying operator (SISSO) approach, an interpretable and accurate formation energy model is constructed.

Enhancing the magnetic relaxivity of MRI contrast agents via the localized superacid microenvironment of graphene quantum dots.

The design of contrast agents (CAs) with high magnetic relaxivities is a key issue in the field of magnetic resonance imaging (MRI). The traditional strategy employed is aimed at optimizing the structural design of the magnetic atoms in the CA. However, it is difficult to obtain an agent with magnetic relaxivity over 100 mM s using this approach.

Polarizing Graphene Quantum Dots toward Long-Acting Intracellular Reactive Oxygen Species Evaluation and Tumor Detection.

The evaluation of intracellular reactive oxygen species (ROS) would greatly deepen the understanding of cell metabolism/proliferation and tumor detection. However, current long-acting level tracking techniques for intracellular ROS remain unsuited to practical applications. To solve this problem, we synthesized cyclotriphosphazene-doped graphene quantum dots (C-GQDs) whose quantum yield is highly sensitive to ROS (increased by 400% from 0.

Crystal Morphology Prediction and Anisotropic Evolution of 1,1-Diamino-2,2-dinitroethylene (FOX-7) by Temperature Tuning.

Temperature-induced morphological changes are one of the strategies for designing crystal shapes, but the role of temperature in enhancing or inhibiting crystal growth is not well understood yet. To meet the requirements of high density and low sensitivity, we need to control the crystal morphology of the energetic materials. We studied the crystal morphology of 1,1-diamino-2,2-dinitroethylene (FOX-7) in dimethyl sulfoxide/water mixed solvent by using the modified Hartman-Perdok theorem.

C N-A 2D Crystalline, Hole-Free, Tunable-Narrow-Bandgap Semiconductor with Ferromagnetic Properties.

Graphene has initiated intensive research efforts on 2D crystalline materials due to its extraordinary set of properties and the resulting host of possible applications. Here the authors report on the controllable large-scale synthesis of C N, a 2D crystalline, hole-free extension of graphene, its structural characterization, and some of its unique properties. C N is fabricated by polymerization of 2,3-diaminophenazine.

Prediction of the crystal packing of di-tetrazine-tetroxide (DTTO) energetic material.

Previous calculations suggested that di-tetrazine-tetroxide (DTTO), aka tetrazino-tetrazine-tetraoxide, might have a particularly large density (2.3 g/cm(3) ) and high energy release (8.8 kJ/kg), but it has not yet been synthesized successfully.