There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Semiconductor photocatalysis has received much attention as a potential solution to the worldwide energy shortage and for counteracting environmental degradation. This article reviews state-of-the-art research activities in the field, focusing on the scientific and technological possibilities offered by photocatalytic materials. We begin with a survey of efforts to explore suitable materials and to optimize their energy band configurations for specific applications. We then examine the design and fabrication of advanced photocatalytic materials in the framework of nanotechnology. Many of the most recent advances in photocatalysis have been realized by selective control of the morphology of nanomaterials or by utilizing the collective properties of nano-assembly systems. Finally, we discuss the current theoretical understanding of key aspects of photocatalytic materials. This review also highlights crucial issues that should be addressed in future research activities.

Nano‐photocatalytic Materials: Possibilities and Challenges

Rising atmospheric levels of carbon dioxide and the depletion of fossil fuel reserves raise serious concerns about the ensuing effects on the global climate and future energy supply. Utilizing the abundant solar energy to convert CO2 into fuels such as methane or methanol could address both problems simultaneously as well as provide a convenient means of energy storage. In this Review, current approaches for the heterogeneous photocatalytic reduction of CO2 on TiO2 and other metal oxide, oxynitride, sulfide, and phosphide semiconductors are presented. Research in this field is focused primarily on the development of novel nanostructured photocatalytic materials and on the investigation of the mechanism of the process, from light absorption through charge separation and transport to CO2 reduction pathways. The measures used to quantify the efficiency of the process are also discussed in detail.

Photocatalytic reduction of CO2 on TiO2 and other semiconductors.

Global warming and climate change concerns have triggered global efforts to reduce the concentration of atmospheric carbon dioxide (CO2). Carbon dioxide capture and storage (CCS) is considered a crucial strategy for meeting CO2 emission reduction targets. In this paper, various aspects of CCS are reviewed and discussed including the state of the art technologies for CO2 capture, separation, transport, storage, leakage, monitoring, and life cycle analysis. The selection of specific CO2 capture technology heavily depends on the type of CO2 generating plant and fuel used. Among those CO2 separation processes, absorption is the most mature and commonly adopted due to its higher efficiency and lower cost. Pipeline is considered to be the most viable solution for large volume of CO2 transport. Among those geological formations for CO2 storage, enhanced oil recovery is mature and has been practiced for many years but its economical viability for anthropogenic sources needs to be demonstrated. There are growing interests in CO2 storage in saline aquifers due to their enormous potential storage capacity and several projects are in the pipeline for demonstration of its viability. There are multiple hurdles to CCS deployment including the absence of a clear business case for CCS investment and the absence of robust economic incentives to support the additional high capital and operating costs of the whole CCS process.

https://www.elsevier.com/__data/assets/pdf_file/0005/96980/Current-status-carbon-capture.pdf

An overview of current status of carbon dioxide capture and storage technologies

A review on g-C3N4-based photocatalysts

Chemi-Capacitive Gas Sensors Based on TiO2 and BaTiO3 Nanotube Arrays

Immersed-boundary methods (IBM) have been constantly gaining popularity and are increasingly expanding to new areas of applications in computational mechanics since last three decades due to the potentials of their application in modeling complex multiphysics phenomena which involves flow over complex and moving boundaries. The specific advantages of an immersed boundary method are due to its accuracy and simplicity. As this method uses a fixed structured Cartesian mesh, the complex grid generation processes can be fully avoided whereas the complex/moving boundary is described using another surface mesh. The computational overheads in an immersed boundary implementation can be very high due to expensive search and interpolation steps through which the effects of the boundary conditions on the surface mesh are translated to the fixed Cartesian volume mesh. Therefore, computationally efficient numerical implementation of an IBM solver is of extreme importance to researchers. This paper presents an accelerated discrete finite difference based immersed boundary (IB) solver that is used to study the external flow behavior around complex geometries. The flow is assumed to be incompressible. The immersed boundary solver is parallelized using OpenACC for quick acceleration with minimal code changes and to ensure performance portability across both GPUs and multicore CPUs. Our experimental results indicate that the OpenACC-based IB solver run on a NVIDIA Tesla P100 GPU is 21x faster than the sequential legacy solver and is 3.3x faster than the OpenACC-based IB solver run on a dual socket Intel Xeon Gold 6148, 20 core CPU. The recirculation lengths obtained for Reynolds numbers of 20 and 40 and the Strouhal number for Reynolds number 100, for a standard flow visualization problem over a fixed cylinder, are in accordance with the reported data in available literature, thereby validating the accuracy of the parallel solver. We also analyze the performance of the accelerated solver on different GPU architectures: Kepler, Pascal and Volta.

Acceleration of a 3D Immersed Boundary Solver Using OpenACC

Irradiation of materials by high energy (∼MeV) ions causes intense electronic excitations through inelastic transfer of energy that significantly modifies physicochemical properties. We report the effect of 100 MeV Ag ion irradiation and resultant localized (∼few nm) thermal spike on vertically oriented TiO2 nanorods (∼100 nm width) towards tailoring their structural and electronic properties. Rapid quenching of the thermal spike induced molten state within ∼0.5 picosecond results in a distortion in the crystalline structure that increases with increasing fluences (ions per cm2). Microstructural investigations reveal ion track formation along with a corrugated surface of the nanorods. The thermal spike simulation validates the experimental observation of the ion track dimension (∼10 nm diameter) and melting of the nanorods. The optical absorption study shows direct bandgap values of 3.11 eV (pristine) and 3.23 eV (5 × 1012 ions per cm2) and an indirect bandgap value of 3.10 eV for the highest fluence (5 × 1013 ions per cm2). First principles electronic structure calculations corroborate the direct-to-indirect transition that is attributed to the structural distortion at the highest fluence. This work presents a unique technique to selectively tune the properties of nanorods for versatile applications.

/pdf/localized-thermal-spike-driven-morphology-and-electronic-mpat7fa1vv.pdf

Localized thermal spike driven morphology and electronic structure transformation in swift heavy ion irradiated TiO2 nanorods

A 1D Cu(II) coordination polymer exhibiting ferromagnetic interactions and a mononuclear Cu(II) complex of substituted pyrazole carboxylic acids: Synthesis, characterization and crystal structure

High fidelity solutions of turbulent flow equations are obtained by large eddy simulation (LES) and direct numerical simulation (DNS). These techniques are devoted for resolving most of the energy-carrying scales in a turbulent flow. Grid resolution in LES or DNS is determined by the lengths of the finest scale of motion which is to be directly simulated. In multiphase flows, further refinement in the grid topology is required to capture the bubble or droplet front and also to resolve the small structures that are created in the wake zone of the bubble/droplet. Owing to the grid size and finer timescales, the computational complexities in LES or DNS are extremely high, and parallel computing resources are often deployed. The present chapter reviews computational efforts involved in turbulent multiphase flow simulation in industrial devices. Several high-performance computing (HPC) strategies like distributed computing using message passing interface (MPI), general purpose graphics processing unit (GPGPU) accelerated computing using CUDA and their hybridizations are also reviewed. Estimations of the computational requirement for simulation of large industrial devices are presented, and potential use of modern computational science and hardware are critically assessed.

Somnath C. Roy

Papers

Chemi-Capacitive Gas Sensors Based on TiO2 and BaTiO3 Nanotube Arrays

Acceleration of a 3D Immersed Boundary Solver Using OpenACC

Localized thermal spike driven morphology and electronic structure transformation in swift heavy ion irradiated TiO2 nanorods

A 1D Cu(II) coordination polymer exhibiting ferromagnetic interactions and a mononuclear Cu(II) complex of substituted pyrazole carboxylic acids: Synthesis, characterization and crystal structure

LES and DNS of Multiphase Flows in Industrial Devices: Application of High-Performance Computing