Nanomaterials最新文献

Using gradient-corrected density functional theory we investigate the mechanical properties of ultrathin boron (B) and phosphorus (P) doped silicon nanowires (SiNWs) along the [001] and [111] orientations within the PBE approximation. Both pristine and doped SiNWs under study have diameters ranging from 5 to 8 Å. Our results show that doping significantly enhances the bulk modulus (B0), shear modulus (GV), Young's modulus (Y), and other mechanical parameters. The significant anisotropy observed in the mechanical properties of Si[111] NWs, with varying moduli along different axes, further illustrates the complex interplay between mechanical behavior and electronic structure at the nanoscale. The mechanical flexibility of SiNWs, combined with their tunable electronic properties due to quantum confinement, makes them promising candidates for advanced nanoelectronic devices, nanoelectromechanical systems (NEMS), and advanced technologies.

Miniaturized pixel sizes in near-eye digital displays lead to pixel emission patterns with large divergence angles, necessitating efficient beam collimation solutions to improve the light coupling efficiency. Traditional beam collimation optics, such as lenses and cavities, are wavelength-sensitive and cannot simultaneously collimate red (R), green (G), and blue (B) light. In this work, we employed inverse design optimization and finite-difference time-domain (FDTD) simulation techniques to design a collimator comprised of nano-sized photonic structures. To alleviate the challenges of the spatial incoherence nature of micro-LED emission light, we developed a strategy called dual-task optimization. Specifically, the method models light collimation as a dual task of color routing. By optimizing a color router, which routes incident light within a small angular range to different locations based on its spectrum, we simultaneously obtained a beam collimator, which can restrict the output of the light emitted from the routing destination with a small divergence angle. We further evaluated the collimation performance for spatially incoherent RGB micro-LED light in an FDTD using a multiple-dipole simulation method, and the simulation results demonstrate that our designed collimator can increase the light coupling efficiency from approximately 30% to 60% within a divergence angle of ±20° for all R/G/B light under the spatially incoherent emission.

Most life activities of organisms are realized through protein-protein interactions, and these interactions are mainly achieved through residue-residue contact between monomer proteins. Consequently, studying residue-residue contact at the protein interaction interface can contribute to a deeper understanding of the protein-protein interaction mechanism. In this paper, we focus on the research of the trimer protein interface residue pair. Firstly, we utilize the amino acid k-interval product factor descriptor (AAIPF(k)) to integrate the positional information and physicochemical properties of amino acids, combined with the electric properties and geometric shape features of residues, to construct an 8 × 16 multi-feature map. This multi-feature map represents a sample composed of two residues on a trimer protein. Secondly, we construct a CNN-GRU deep learning framework to predict the trimer protein interface residue pair. The results show that when each dimer protein provides 10 prediction results and two protein-protein interaction interfaces of a trimer protein needed to be accurately predicted, the accuracy of our proposed method is 60%. When each dimer protein provides 10 prediction results and one protein-protein interaction interface of a trimer protein needs to be accurately predicted, the accuracy of our proposed method is 93%. Our results can provide experimental researchers with a limited yet precise dataset containing correct trimer protein interface residue pairs, which is of great significance in guiding the experimental resolution of the trimer protein three-dimensional structure. Furthermore, compared to other computational methods, our proposed approach exhibits superior performance in predicting residue-residue contact at the trimer protein interface.

Mustard gas (HD) is a well-known chemical warfare agent, recognized for its extreme toxicity and severe hazards. Metal-organic frameworks (MOFs), with their unique structural properties, show significant potential for HD adsorption applications. Due to the extreme hazards of HD, most experimental studies focus on its simulants, but molecular simulation research on these simulants remains limited. Simulation analyses of simulants can uncover structure-performance relationships and enable experimental validation, optimizing methods, and improving material design and performance predictions. This study integrates molecular simulations, machine learning (ML), and molecular fingerprinting (MFs) to identify MOFs with high adsorption performance for the HD simulant diethyl sulfide (DES), followed by in-depth structural analysis and comparison. First, MOFs are categorized into Top, Middle, and Bottom materials based on their adsorption efficiency. Univariate analysis, machine learning, and molecular fingerprinting are then used to identify and compare the distinguishing features and fingerprints of each category. Univariate analysis helps identify the optimal structural ranges of Top and Bottom materials, providing a reference for initial material screening. Machine learning feature importance analysis, combined with SHAP methods, identifies the key features that most significantly influence model predictions across categories, offering valuable insights for future material design. Molecular fingerprint analysis reveals critical fingerprint combinations, showing that adsorption performance is optimized when features such as metal oxides, nitrogen-containing heterocycles, six-membered rings, and C=C double bonds co-exist. The integrated analysis using HTCS, ML, and MFs provides new perspectives for designing high-performance MOFs and demonstrates significant potential for developing materials for the adsorption of CWAs and their simulants.

This paper presents a simple, post-synthesis treatment of carbon dots (C-dots) that relies on the oxidizing activity of sodium hypochlorite to induce surface oxidation, etching and pronounced structural rearrangements. The thus treated C-dots (ox-C-dots) exhibit up to six-fold enhancement in quantum yield compared to non-oxidised analogues, while maintaining low levels of cytotoxicity against HeLa and U87 cell lines. In addition, we demonstrate that a range of polymeric materials (polyurethane sponge, polyvinylidene fluoride membrane, polyester fabric) impregnated with ox-C-dots show advanced antifungal properties against Talaromyces pinophilus, while their untreated counterparts fail to do so.

The combination of nanotechnology and biotechnology is paving the way for new medical treatments, with promising results in therapy [...].

As highly porous nanomaterials, aerogels are fascinating due to their remarkable structural properties and performance [...].

We have estimated the intrinsic complex refractive index spectrum of a CsPbBr₃ nanocrystal. With various dilute solutions of CsPbBr₃ nanocrystals dissolved in toluene, effective refractive indices were measured at two different wavelengths using Michelson interferometry. Given the effective absorption spectrum of the solution, a full spectrum of the effective refractive index was also obtained through the Kramers-Krönig relations. Based on the Maxwell-Garnett model in the effective medium approximation, the real and imaginary spectrum of the complex refractive index was estimated for the CsPbBr₃ nanocrystal, and the dominant inaccuracy was attributed to the size inhomogeneity.

The use of nanoparticles is becoming increasingly apparent in a growing number of medical fields. To exploit the full potential of these particles, it is essential to examine their behavior in the blood and their possible interactions with blood cells. Dendritic core multi-shell DendroSol™ nanoparticles (DS-NPs) are able to penetrate into viable layers of human skin, but nothing is known about their interaction with blood cells. In the present study, we analyze the effect of DS-NPs on red blood cells (RBCs) using confocal laser scanning microscopy (CLSM), flow cytometry, sedimentation rate analysis, spectrophotometry, and hemolysis assays. DS-NPs labeled with Nile red (NR) were added to RBC suspensions and their accumulation in the area of the RBC membranes was demonstrated by CLSM as well as by flow cytometry. In the presence of DS-NPs, the RBCs show an increased sedimentation rate, which also confirms the binding of the NPs to the cells. Interestingly, in the presence of DS-NPs, the RBCs are stabilized against hypotonic hemolysis as well as against the hemolytic action of Triton X-100. This proven anti-hemolytic effect could be utilized to enhance the circulation time of RBCs loaded with drugs for prolonged sustained release and drug delivery with enhanced bioavailability.

Metals are known for conductivity and luster due to the abundance of free electrons [...].