As a fascinating conjugated polymer, graphitic carbon nitride (g-C3N4) has become a new research hotspot and drawn broad interdisciplinary attention as a metal-free and visible-light-responsive photocatalyst in the arena of solar energy conversion and environmental remediation. This is due to its appealing electronic band structure, high physicochemical stability, and “earth-abundant” nature. This critical review summarizes a panorama of the latest progress related to the design and construction of pristine g-C3N4 and g-C3N4-based nanocomposites, including (1) nanoarchitecture design of bare g-C3N4, such as hard and soft templating approaches, supramolecular preorganization assembly, exfoliation, and template-free synthesis routes, (2) functionalization of g-C3N4 at an atomic level (elemental doping) and molecular level (copolymerization), and (3) modification of g-C3N4 with well-matched energy levels of another semiconductor or a metal as a cocatalyst to form heterojunction nanostructures. The constructi...

Graphitic Carbon Nitride (g-C3N4)-Based Photocatalysts for Artificial Photosynthesis and Environmental Remediation: Are We a Step Closer To Achieving Sustainability?

Jenny Schneider,*,† Masaya Matsuoka,‡ Masato Takeuchi,‡ Jinlong Zhang, Yu Horiuchi,‡ Masakazu Anpo,‡ and Detlef W. Bahnemann*,† †Institut fur Technische Chemie, Leibniz Universitaẗ Hannover, Callinstrasse 3, D-30167 Hannover, Germany ‡Faculty of Engineering, Osaka Prefecture University, 1 Gakuen-cho, Sakai Osaka 599-8531, Japan Key Lab for Advanced Materials and Institute of Fine Chemicals, East China University of Science and Technology, Shanghai 200237, China

Understanding TiO2 photocatalysis: mechanisms and materials.

Recent years have seen a renewed interest in the harvesting and conversion of solar energy. Among various technologies, the direct conversion of solar to chemical energy using photocatalysts has received significant attention. Although heterogeneous photocatalysts are almost exclusively semiconductors, it has been demonstrated recently that plasmonic nanostructures of noble metals (mainly silver and gold) also show significant promise. Here we review recent progress in using plasmonic metallic nanostructures in the field of photocatalysis. We focus on plasmon-enhanced water splitting on composite photocatalysts containing semiconductor and plasmonic-metal building blocks, and recently reported plasmon-mediated photocatalytic reactions on plasmonic nanostructures of noble metals. We also discuss the areas where major advancements are needed to move the field of plasmon-mediated photocatalysis forward.

Plasmonic-metal nanostructures for efficient conversion of solar to chemical energy

Metal species with different size (single atoms, nanoclusters, and nanoparticles) show different catalytic behavior for various heterogeneous catalytic reactions. It has been shown in the literature that many factors including the particle size, shape, chemical composition, metal–support interaction, and metal–reactant/solvent interaction can have significant influences on the catalytic properties of metal catalysts. The recent developments of well-controlled synthesis methodologies and advanced characterization tools allow one to correlate the relationships at the molecular level. In this Review, the electronic and geometric structures of single atoms, nanoclusters, and nanoparticles will be discussed. Furthermore, we will summarize the catalytic applications of single atoms, nanoclusters, and nanoparticles for different types of reactions, including CO oxidation, selective oxidation, selective hydrogenation, organic reactions, electrocatalytic, and photocatalytic reactions. We will compare the results o...

Metal Catalysts for Heterogeneous Catalysis: From Single Atoms to Nanoclusters and Nanoparticles.

The science and technology of ultracapacitors are reviewed for a number of electrode materials, including carbon, mixed metal oxides, and conducting polymers. More work has been done using microporous carbons than with the other materials and most of the commercially available devices use carbon electrodes and an organic electrolytes. The energy density of these devices is 3¯5 Wh/kg with a power density of 300¯500 W/kg for high efficiency (90¯95%) charge/discharges. Projections of future developments using carbon indicate that energy densities of 10 Wh/kg or higher are likely with power densities of 1¯2 kW/kg. A key problem in the fabrication of these advanced devices is the bonding of the thin electrodes to a current collector such the contact resistance is less than 0.1 cm2. Special attention is given in the paper to comparing the power density characteristics of ultracapacitors and batteries. The comparisons should be made at the same charge/discharge efficiency.

Ultracapacitors: Why, How, and Where is the Technology

Band bending in semiconductors: chemical and physical consequences at surfaces and interfaces.

https://www.cell.com/cell-stem-cell/pdf/S1934-5909(19)30431-X.pdf

Patient-Derived Organoids Predict Chemoradiation Responses of Locally Advanced Rectal Cancer

Purpose To develop an automated treatment planning strategy for external beam intensity-modulated radiation therapy (IMRT), including a deep learning-based three-dimensional (3D) dose prediction and a dose distribution-based plan generation algorithm. Methods and materials A residual neural network-based deep learning model is trained to predict a dose distribution based on patient-specific geometry and prescription dose. A total of 270 head-and-neck cancer cases were enrolled in this study, including 195 cases in the training dataset, 25 cases in the validation dataset, and 50 cases in the testing dataset. All patients were treated with IMRT with a variety of different prescription patterns. The model input consists of CT images and contours delineating the organs at risk (OARs) and planning target volumes (PTVs). The algorithm output is trained to predict the dose distribution on the CT image slices. The obtained prediction model is used to predict dose distributions for new patients. Then, an optimization objective function based on these predicted dose distributions is created for automatic plan generation. Results Our results demonstrate that the deep learning method can predict clinically acceptable dose distributions. There is no statistically significant difference between prediction and real clinical plan for all clinically relevant dose-volume histogram (DVH) indices, except brainstem, right and left lens. However, the predicted plans were still clinically acceptable. The results of plan generation show no statistically significant differences between the automatic generated plan and the predicted plan except PTV70.4 , but the difference is only 0.5% which is still clinically acceptable. Conclusion This study developed a new automated radiotherapy treatment planning system based on 3D dose prediction and 3D dose distribution-based optimization. It is a promising approach for realizing automated treatment planning in the future.

Automatic treatment planning based on three-dimensional dose distribution predicted from deep learning technique.

Objectives To determine the contribution of progress in averting premature deaths to the increase in life expectancy and the decline in lifespan variation Design International comparison of national life table data from the Human Mortality Database Setting 40 developed countries and regions, 1840–2009 Population Men and women of all ages Main outcome measure We use two summary measures of mortality: life expectancy and life disparity Life disparity is a measure of how much lifespans differ among individuals We define a death as premature if postponing it to a later age would decrease life disparity Results In 89 of the 170 years from 1840 to 2009, the country with the highest male life expectancy also had the lowest male life disparity This was true in 86 years for female life expectancy and disparity In all years, the top several life expectancy leaders were also the top life disparity leaders Although only 38% of deaths were premature, fully 84% of the increase in life expectancy resulted from averting premature deaths The reduction in life disparity resulted from reductions in early-life disparity, that is, disparity caused by premature deaths; late-life disparity levels remained roughly constant Conclusions The countries that have been the most successful in averting premature deaths have consistently been the life expectancy leaders Greater longevity and greater equality of individuals9 lifespans are not incompatible goals Countries can achieve both by reducing premature deaths

https://bmjopen.bmj.com/content/bmjopen/1/1/e000128.full.pdf

Life expectancy and disparity: an international comparison of life table data

The photoluminescence (PL) of TiO2 at 529.5 nm (2.34 eV) has been found to be a sensitive indicator of UV-induced band structure modification. As UV irradiation occurs, the positive surface potential changes and shifts the depth of the depletion layer. In addition, reversible band bending due to the adsorption of the electron-donor NH3 and CO molecules has been observed in measurements combining PL with FTIR surface spectroscopy. It has been found that the O2 molecule acts in two ways: as a reversibly adsorbed electron-acceptor molecule and as an irreversibly adsorbed molecule that heals natural oxygen vacancy defects in the near-surface region.

Zhen Zhang

Papers

Band bending in semiconductors: chemical and physical consequences at surfaces and interfaces.

Patient-Derived Organoids Predict Chemoradiation Responses of Locally Advanced Rectal Cancer

Automatic treatment planning based on three-dimensional dose distribution predicted from deep learning technique.

Life expectancy and disparity: an international comparison of life table data

Photoluminescence of TiO2: Effect of UV Light and Adsorbed Molecules on Surface Band Structure