MOF-derived NiAl2O4/NiCo2O4 porous materials as supercapacitors with high electrochemical performance.

Metal-organic framework compounds are extensively utilized in various fields, such as electrode materials, owing to their distinctive porous structure and significant specific surface area. In this study, NiCoAl-MOF metal-organic framework precursors were synthesized by a solvothermal method, and NiAl2O4/NiCo2O4 electrode materials were prepared by the subsequent calcination of the precursor. These materials were characterized by XRD, XPS, BET tests, and SEM, and the electrochemical properties of the electrode materials were tested by CV and GCD methods. BET tests showed that NiAl2O4/NiCo2O4 has an abundant porous structure and a large specific surface area of up to 105 m2 g-1. The specific capacitance of NiAl2O4/NiCo2O4 measured by the GCD method reaches up to 2870.83 F g-1 at a current density of 1 A g-1. The asymmetric supercapacitor NiAl2O4/NiCo2O4//AC assembled with activated carbon electrodes has a maximum energy density of 166.98 W h kg-1 and a power density of 750.00 W kg-1 within a voltage window of 1.5 V. In addition, NiAl2O4/NiCo2O4 materials have good cycling stability. These advantages make it a good candidate for the application of high-performance supercapacitors.

Effect of Sintering Temperature on Properties of Carbon Fiber-Reinforced Titanium Matrix Composites.

Carbon fiber-reinforced titanium matrix composites were prepared by powder metallurgy. Carbon fiber (CF) powder and titanium (Ti) powder are mixed, pressed, and then sintered at a high temperature of 1300-1500 °C. The morphology and conductivity of carbon fiber-reinforced titanium matrix (Ti-CF) composites were studied. When the temperature range of the Ti-CF composites was from 1300 to 1500 °C, the porosity and resistivity first decreased and then increased. When the sintering temperature was 1350 °C, the diffraction peak of the sample was the strongest, the porosity was the smallest (4.16%), and the resistivity was the smallest (2.7 MΩ·mm). CFs have a very good strengthening effect on titanium-based composite materials.

Wavelength stability in a hybrid photonic crystal laser through controlled nonlinear absorptive heating in the reflector.

The need for miniaturized, fully integrated semiconductor lasers has stimulated significant research efforts into realizing unconventional configurations that can meet the performance requirements of a large spectrum of applications, ranging from communication systems to sensing. We demonstrate a hybrid, silicon  photonics-compatible photonic crystal (PhC) laser architecture that can be used to implement cost-effective, high-capacity light sources, with high side-mode suppression ratio and milliwatt output output powers. The emitted wavelength is set and controlled by a silicon PhC cavity-based reflective filter with the gain provided by a III-V-based reflective semiconductor optical amplifier (RSOA). The high power density in the laser cavity results in a significant enhancement of the nonlinear absorption in silicon in the high Q-factor PhC resonator. The heat generated in this manner creates a tuning effect in the wavelength-selective element, which can be used to offset external temperature fluctuations without the use of active cooling. Our approach is fully compatible with existing fabrication and integration technologies, providing a practical route to integrated lasing in wavelength-sensitive schemes.

Thin high numerical aperture metalens.

We designed, fabricated, and characterized a thin metalens in an amorphous silicon film of diameter 30 µm, focal length equal to the incident wavelength 633 nm. The lens is capable of simultaneously manipulating the state of polarization and phase of incident light. The lens converts a linearly polarized beam into radially polarized light, producing a subwavelength focus. When illuminated with a linearly polarized Gaussian beam, the lens produces a focal spot whose size at full-width half-maximum intensity is 0.49λ and 0.55λ (λ is incident wavelength). The experimental results are in good agreement with the numerical simulation, with the simulated focal spot measuring 0.46λ and 0.52λ. This focal spot is less than all other focal spots obtained using metalenses.

On simplified global nonlinear function for fitness landscape: a case study of inverse protein folding.

The construction of fitness landscape has broad implication in understanding molecular evolution, cellular epigenetic state, and protein structures. We studied the problem of constructing fitness landscape of inverse protein folding or protein design, with the aim to generate amino acid sequences that would fold into an a priori determined structural fold which would enable engineering novel or enhanced biochemistry. For this task, an effective fitness function should allow identification of correct sequences that would fold into the desired structure. In this study, we showed that nonlinear fitness function for protein design can be constructed using a rectangular kernel with a basis set of proteins and decoys chosen a priori. The full landscape for a large number of protein folds can be captured using only 480 native proteins and 3,200 non-protein decoys via a finite Newton method. A blind test of a simplified version of fitness function for sequence design was carried out to discriminate simultaneously 428 native sequences not homologous to any training proteins from 11 million challenging protein-like decoys. This simplified function correctly classified 408 native sequences (20 misclassifications, 95% correct rate), which outperforms several other statistical linear scoring function and optimized linear function. Our results further suggested that for the task of global sequence design of 428 selected proteins, the search space of protein shape and sequence can be effectively parametrized with just about 3,680 carefully chosen basis set of proteins and decoys, and we showed in addition that the overall landscape is not overly sensitive to the specific choice of this set. Our results can be generalized to construct other types of fitness landscape.

Experimental demonstration of near-infrared epsilon-near-zero multilayer metamaterial slabs.

Near-infrared epsilon-near-zero (ENZ) metamaterial slabs based on silver-germanium (Ag-Ge) multilayers are experimentally demonstrated. Transmission, reflection and absorption spectra are characterized and used to determine the complex refractive indices and the effective permittivities of the ENZ metamaterial slabs, which match the results obtained from both the numerical simulations and the optical nonlocalities analysis. A rapid post-annealing process is used to reduce the collision frequency of silver and therefore decrease the optical absorption loss of multilayer metamaterial slabs. Furthermore, multilayer grating structures are studied to enhance the optical transmission and also tune the location of ENZ wavelength. The demonstrated near-infrared ENZ multilayer metamaterial slabs are important for realizing many exotic applications, such as phase front shaping and engineering of photonic density of states.

[Analysis of amino acid contents between wild plant QiBaiZhu and YunnanBaiZhu].

Amino acid contents between in the root of wild plant QiBaiZhu (Atractylodes macracephala Koidz) and YunnanBaiZhu were analyzed. The results showed that the content of essential amino acid in QiBaiZhu was 3.5 times as much as that of YunnanBaiZhu, especially the content of Arg was very rich (1.61%) and was 53.6 times as much as that of YunnanBaiZhu. Wild plant QiBaiZhu has very good development and utilization value in nutrition and medicinal.

Developing optimal non-linear scoring function for protein design.

UNLABELLED: Motivation. Protein design aims to identify sequences compatible with a given protein fold but incompatible to any alternative folds. To select the correct sequences and to guide the search process, a design scoring function is critically important. Such a scoring function should be able to characterize the global fitness landscape of many proteins simultaneously. RESULTS: To find optimal design scoring functions, we introduce two geometric views and propose a formulation using a mixture of non-linear Gaussian kernel functions. We aim to solve a simplified protein sequence design problem. Our goal is to distinguish each native sequence for a major portion of representative protein structures from a large number of alternative decoy sequences, each a fragment from proteins of different folds. Our scoring function discriminates perfectly a set of 440 native proteins from 14 million sequence decoys. We show that no linear scoring function can succeed in this task. In a blind test of unrelated proteins, our scoring function misclassfies only 13 native proteins out of 194. This compares favorably with about three-four times more misclassifications when optimal linear functions reported in the literature are used. We also discuss how to develop protein folding scoring function.

Optimal nonlinear scoring function for global fitness landscape of protein design.

Protein design aims to identify sequences compatible with a given protein fold but incompatible to any alternative folds. To select the correct sequences and to guide the search process, a design scoring function is critically important. It is also important that a design scoring function can characterize the global fitness landscape of many proteins simultaneously. We describe how finding optimal design scoring functions can be understood from two geometric viewpoints, and propose a formulation using mixture of Gaussian kernel functions. We give results of distinguishing native sequences for a major portion of representative protein structures from a large number of alternative decoy sequences. We succeeded in deriving nonlinear scoring function that perfectly discriminate a set of 440 representative native proteins of known protein structures from 14 million sequence decoys. We show that no linear scoring function can have perfect discrimination. In an independent blind test using 194 unrelated proteins, our scoring function misclassifies only 13 native proteins. This compares favorably with 37 or 51 misclassifications when optimal linear functions reported in literature are used.

Simplicial edge representation of protein structures and alpha contact potential with confidence measure.

Protein representation and potential function are two important ingredients for studying protein folding, equilibrium thermodynamics, and sequence design. We introduce a novel geometric representation of protein contact interactions using the edge simplices from the alpha shape of the protein structure. This representation can eliminate implausible neighbors that are not in physical contact, and can avoid spurious contact between two residues when a third residue is between them. We developed statistical alpha contact potential using an odds-ratio model. A studentized bootstrap method was then introduced to assess the 95% confidence intervals for each of the 210 propensity parameters. We found, with confidence, that there is significant long-range propensity (>30 residues apart) for hydrophobic interactions. We tested alpha contact potential for native structure discrimination using several sets of decoy structures, and found that it often performs comparably with atom-based potentials requiring many more parameters. We also show that accurate geometric representation is important, and that alpha contact potential has better performance than potential defined by cutoff distance between geometric centers of side chains. Hierarchical clustering of alpha contact potentials reveals natural grouping of residues. To explore the relationship between shape and physicochemical representations, we tested the minimum alphabet size necessary for native structure discrimination. We found that there is no significant difference in performance of discrimination when alphabet size varies from 7 to 20, if geometry is represented accurately by alpha simplicial edges. This result suggests that the geometry of packing plays an important role, but the specific residue types are often interchangeable.