Interfacial Properties of Bilayer and Trilayer Graphene on Metal Substrates

One popular approach to prepare graphene is to grow them on transition metal substrates via chemical vapor deposition. By using the density functional theory with dispersion correction, we systematically investigate for the first time the interfacial properties of bilayer (BLG) and trilayer graphene (TLG) on metal substrates. Three categories of interfacial structures are revealed. The adsorption of B(T)LG on Al, Ag, Cu, Au, and Pt substrates is a weak physisorption, but a band gap can be opened. The adsorption of B(T)LG on Ti, Ni, and Co substrates is a strong chemisorption, and a stacking-insensitive band gap is opened for the two uncontacted layers of TLG. The adsorption of B(T)LG on Pd substrate is a weaker chemisorption, with a band gap opened for the uncontacted layers. This fundamental study also helps for B(T)LG device study due to inevitable graphene/metal contact.Comment: 1 table, 8 figure

A scheme for simulating multi-level phase change photonics materials

Abstract Chalcogenide phase change materials (PCMs) have been extensively applied in data storage, and they are now being proposed for high resolution displays, holographic displays, reprogrammable photonics, and all-optical neural networks. These wide-ranging applications all exploit the radical property contrast between the PCMs’ different structural phases, extremely fast switching speed, long-term stability, and low energy consumption. Designing PCM photonic devices requires an accurate model to predict the response of the device during phase transitions. Here, we describe an approach that accurately predicts the microstructure and optical response of phase change materials during laser induced heating. The framework couples the Gillespie Cellular Automata approach for modelling phase transitions with effective medium theory and Fresnel equations. The accuracy of the approach is verified by comparing the PCM’s optical response and microstructure evolution with the results of nanosecond laser switching experiments. We anticipate that this approach to simulating the switching response of PCMs will become an important component for designing and simulating programmable photonics devices. The method is particularly important for predicting the multi-level optical response of PCMs, which is important for all-optical neural networks and PCM-programmable perceptrons

Experimental Test of Quantum Jarzynski Equality with a Trapped Ion System

The past two decades witnessed important developments in the field of non-equilibrium statistical mechanics. Among these developments, the Jarzynski equality, being a milestone following the landmark work of Clausius and Kelvin, stands out. The Jarzynski equality relates the free energy difference between two equilibrium states and the work done on the system through far from equilibrium processes. While experimental tests of the equality have been performed in classical regime, the verification of the quantum Jarzynski equality has not yet been fully demonstrated due to experimental challenges. Here, we report an experimental test of the quantum Jarzynski equality with a single \Yb ion trapped in a harmonic potential. We perform projective measurements to obtain phonon distributions of the initial thermal state. Following that we apply the laser induced force on the projected energy eigenstate, and find transition probabilities to final energy eigenstates after the work is done. By varying the speed of applying the force from equilibrium to far-from equilibrium regime, we verified the quantum Jarzynski equality in an isolated system.Comment: 18 pages, 4 figures, 1 tabl

Unsupervised Text Topic-Related Gene Extraction for Large Unbalanced Datasets

There is a common notion that traditional unsupervised feature extraction algorithms follow the assumption that the distribution of the different clusters in a dataset is balanced. However, feature selection is guided by the calculation of similarities among features when topic keywords are extracted from a large number of unmarked, unbalanced text datasets. As a result, the selected features cannot truly reflect the information of the original data set, which thus affects the subsequent performance of classifiers. To solve this problem, a new method of extracting unsupervised text topic-related genes is proposed in this paper. Firstly, a sample cluster group is obtained by factor analysis and a density peak algorithm, based on which the dataset is marked. Then, considering the influence of the unbalanced distribution of sample clusters on feature selection, the CHI statistical matrix feature selection method, which combines average local density and information entropy together, is used to strengthen the features of low-density small-sample clusters. Finally, a related gene extraction method based on the exploration of high-order relevance in multidimensional statistical data is described, which uses independent component analysis to enhance the generalisability of the selected features. In this way, unsupervised text topic-related genes can be extracted from large unbalanced datasets. The results of experiments suggest that the proposed method of extracting unsupervised text topic-related genes is better than existing methods in extracting text subject terms from low-density small-sample clusters, and has higher prematurity and feature dimension-reduction ability

Effectiveness of low-intensity pulsed ultrasound on osteoarthritis: molecular mechanism and tissue engineering

Osteoarthritis (OA) is distinguished by pathological alterations in the synovial membrane, articular cartilage, and subchondral bone, resulting in physical symptoms such as pain, deformity, and impaired mobility. Numerous research studies have validated the effectiveness of low-intensity pulsed ultrasound (LIPUS) in OA treatment. The periodic mechanical waves generated by LIPUS can mitigate cellular ischemia and hypoxia, induce vibration and collision, produce notable thermal and non-thermal effects, alter cellular metabolism, expedite tissue repair, improve nutrient delivery, and accelerate the healing process of damaged tissues. The efficacy and specific mechanism of LIPUS is currently under investigation. This review provides an overview of LIPUS’s potential role in the treatment of OA, considering various perspectives such as the synovial membrane, cartilage, subchondral bone, and tissue engineering. It aims to facilitate interdisciplinary scientific research and further exploration of LIPUS as a complementary technique to existing methods or surgery. Ongoing research is focused on determining the optimal dosage, frequency, timing, and treatment strategy of LIPUS for OA. Additional research is required to clarify the precise mechanism of action and potential impacts on cellular, animal, and human systems prior to its integration into therapeutic applications