Photonic Crystal Palette of Binary Block Copolymer Blends for Full Visible Structural Color Encryption

Structural color (SC) arising from a periodically ordered self-assembled block copolymer (BCP) photonic crystal (PC) is useful for reflective-mode sensing displays owing to its capability of stimuli-responsive structure alteration. However, a set of PC inks, each providing a precisely addressable SC in the full visible range, has rarely been demonstrated. Here, a strategy for developing BCP PC inks with tunable structures is presented. This involves solution-blending of two lamellar-forming BCPs with different molecular weights. By controlling the mixing ratio of the two BCPs, a thin 1D BCP PC film is developed with alternating in-plane lamellae whose periodicity varies linearly from ≈46 to ≈91 nm. Subsequent preferential swelling of one-type lamellae with either solvent or non-volatile ionic liquid causes the photonic band gap of the films to red-shift, giving rise to full-visible-range SC correlated with the pristine nanostructures of the blended films in both liquid and solid states. The BCP PC palette of solution-blended binary solutions is conveniently employed in various coating processes, allowing facile development of BCP SC on the targeted surface. Furthermore, full-color SC paintings are realized with their transparent PC inks, facilitating low-power pattern encryption.     

Parallel Cloth Simulation Using OpenGL Shading Language

The primary goal of cloth simulation is to express object behavior in a realistic manner and achieve real-time performance by following the fundamental concept of physic. In general, the mass–spring system is applied to real-time cloth simulation with three types of springs. However, hard spring cloth simulation using the mass–spring system requires a small integration time-step in order to use a large stiffness coefficient. Furthermore, to obtain stable behavior, constraint enforcement is used instead of maintenance of the force of each spring. Constraint force computation involves a large sparse linear solving operation. Due to the large computation, we implement a cloth simulation using adaptive constraint activation and deactivation techniques that involve the mass–spring system and constraint enforcement method to prevent excessive elongation of cloth. At the same time, when the length of the spring is stretched or compressed over a defined threshold, adaptive constraint activation and deactivation method deactivates the spring and generate the implicit constraint. Traditional method that uses a serial process of the Central Processing Unit (CPU) to solve the system in every frame cannot handle the complex structure of clothmodel in real-time. Our simulation utilizes the Graphic Processing Unit (GPU) parallel processing with compute shader in OpenGL Shading Language (GLSL) to solve the system effectively. In this paper, we design and implement parallel method for cloth simulation, and experiment on the performance and behavior comparison of the mass–spring system, constraint enforcement, and adaptive constraint activation and deactivation techniques the using GPU-based parallel method.     

Re-weighting regression and sparsity regularization for multi-view classification

Applied Intelligence - Multi-view data widely exists in real life, which contains rich and comprehensive information. Multi-view learning aims to make full use of the information of multiple views...     

Self-organizing maps for pattern recognition in design of alloys

A combined experimental–computational methodology for accelerated design of AlNiCo-type permanent magnetic alloys is presented with the objective of simultaneously extremizing several magnetic properties. Chemical concentrations of eight alloying elements were initially generated using a quasi-random number generator so as to achieve a uniform distribution in the design variable space. It was followed by manufacture and experimental evaluation of these alloys using an identical thermo-magnetic protocol. These experimental data were used to develop meta-models capable of directly relating the chemical composition with desired macroscopic properties of the alloys. These properties were simultaneously optimized to predict chemical compositions that result in improvement of properties. These data were further utilized to discover various correlations within the experimental dataset by using several concepts of artificial intelligence. In this work, an unsupervised neural network known as self-organizing maps was used to discover various patterns reported in the literature. These maps were also used to screen the composition of the next set of alloys to be manufactured and tested in the next iterative cycle. Several of these Pareto-optimized predictions out-performed the initial batch of alloys. This approach helps significantly reducing the time and the number of alloys needed in the alloy development process.     

Effects of Ti and Mn Co-substitution on P4mm BiFeO3: An Ab Initio Calculation

Tetragonal BiFeO₃ (BFO), which has a giant spontaneous polarization, has attracted a great deal of attention recently. In this paper, we systematically study the structural, magnetic, electronic and optic properties of BFO, BiFe_0.75Mn_0.25 O ₃ (BFMM), and BiFe_0.75Ti_0.125Mn_0.125 O ₃ (BFMT). Results show that doping Ti and Mn into the Fe sites increases the c/a ratio and enhances the magnetization of BiFeO₃ from 0 to 5 μ_B. The crystal symmetry changes from orthogonality to tetragonality with half of the Mn atoms being replaced by Ti in BiFe_0.75Mn_0.25 O ₃, which suppresses the energy splitting of the Mn 3d orbitals and thus enlarge the band gap to 1.21 eV for BiFe_0.75Ti_0.125Mn_0.125 O ₃. Our calculated Bader charge and charge density difference show that the smallest volume of BiFe_0.75Mn_0.25 O ₃ arises from the strong Mn–O bonds in BiFe_0.75Mn_0.25 O ₃. Further investigations indicate similar optical behaviors for BiFeO₃ and BiFe_0.75Ti_0.125Mn_0.125 O ₃. However, BiFe_0.75Mn_0.25 O ₃ exhibits strong absorption in the infrared region for the transition from O 2p to Mn \({e_{g}^{2}}\) and \(t_{2g}^{3}\).     

Redox and pH Dual Responsive Polymer Based Nanoparticles for In Vivo Drug Delivery

Responsive nanomaterials have emerged as promising candidates as drug delivery vehicles in order to address biomedical diseases such as cancer. In this work, polymer‐based responsive nanoparticles prepared by a supramolecular approach are loaded with doxorubicin (DOX) for the cancer therapy. The nanoparticles contain disulfide bonds within the polymer network, allowing the release of the DOX payload in a reducing environment within the endoplasm of cancer cells. In addition, the loaded drug can also be released under acidic environment. In vitro anticancer studies using redox and pH dual responsive nanoparticles show excellent performance in inducing cell death and apoptosis. Zebrafish larvae treated with DOX‐loaded nanoparticles exhibit an improved viability as compared with the cases treated with free DOX by the end of a 3 d treatment. Confocal imaging is utilized to provide the daily assessment of tumor size on zebrafish larva models treated with DOX‐loaded nanoparticles, presenting sustainable reduction of tumor. This work demonstrates the development of functional nanoparticles with dual responsive properties for both in vitro and in vivo drug delivery in the cancer therapy.     

Broadband Light Absorption and Efficient Charge Separation Using a Light Scattering Layer with Mixed Cavities for High‐Performance Perovskite Photovoltaic Cells with Stability

CH₃NH₃PbI₃ is one of the promising light sensitizers for perovskite photovoltaic cells, but a thick layer is required to enhance light absorption in the long‐wavelength regime ranging from PbI₂ absorption edge (500 nm) to its optical band‐gap edge (780 nm) in visible light. Meanwhile, the thick perovskite layer suppresses visible‐light absorption in the short wavelengths below 500 nm and charge extraction capability of electron–hole pairs produced upon light absorption. Herein, we find that a new light scattering layer with the mixed cavities of sizes in 100 and 200 nm between transparent fluorine‐doped tin oxide and mesoporous titanium dioxide electron transport layer enables full absorption of short‐wavelength photons (λ < 500 nm) to the perovskite along with enhanced absorption of long‐wavelength photons (500 nm < λ < 780 nm). Moreover, the light‐driven electric field is proven to allow efficient charge extraction upon light absorption, thereby leading to the increased photocurrent density as well as the fill factor prompted by the slow recombination rate. Additionally, the photocurrent density of the cell with a light scattering layer of mixed cavities is stabilized due to suppressed charge accumulation. Consequently, this work provides a new route to realize broadband light harvesting of visible light for high‐performance perovskite photovoltaic cells.     

Rechargeable Aluminum‐Ion Batteries Based on an Open‐Tunnel Framework

Rechargeable batteries based on an abundant metal such as aluminum with a three‐electron transfer per atom are promising for large‐scale electrochemical energy storage. Aluminum can be handled in air, thus offering superior safety, easy fabrication, and low cost. However, the development of Al‐ion batteries has been challenging due to the difficulties in identifying suitable cathode materials. This study presents the use of a highly open framework Mo_{2.5 + y} VO_{9 + z} as a cathode for Al‐ion batteries. The open‐tunnel oxide allows a facile diffusion of the guest species and provides sufficient redox centers to help redistribute the charge within the local host lattice during the multivalent‐ion insertion, thus leading to good rate capability with a specific capacity among the highest reported in the literature for Al‐based batteries. This study also presents the use of Mo_{2.5 + y} VO_{9 + z} as a model host to develop a novel ultrafast technique for chemical insertion of Al ions into host structures. The microwave‐assisted method employing diethylene glycol and aluminum diacetate (Al(OH)(C₂H₃O₂)₂) can be performed in air in as little as 30 min, which is far superior to the traditional chemical insertion techniques involving moisture‐sensitive organometallic reagents. The Al‐inserted Al _x Mo_{2.5 + y} VO_{9 + z} obtained by the microwave‐assisted chemical insertion can be used in Al‐based rechargeable batteries.