Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Fast parallel algorithms for short-range molecular dynamics

Gold nanorods have been receiving extensive attention owing to their extremely attractive applications in biomedical technologies, plasmon-enhanced spectroscopies, and optical and optoelectronic devices. The growth methods and plasmonic properties of Au nanorods have therefore been intensively studied. In this review, we present a comprehensive overview of the flourishing field of Au nanorods in the past five years. We will focus mainly on the approaches for the growth, shape and size tuning, functionalization, and assembly of Au nanorods, as well as the methods for the preparation of their hybrid structures. The plasmonic properties and the associated applications of Au nanorods will also be discussed in detail.

Gold nanorods and their plasmonic properties

Hybrid nanostructures composed of semiconductor and plasmonic metal components are receiving extensive attention. They display extraordinary optical characteristics that are derived from the simultaneous existence and close conjunction of localized surface plasmon resonance and semiconduction, as well as the synergistic interactions between the two components. They have been widely studied for photocatalysis, plasmon-enhanced spectroscopy, biotechnology, and solar cells. In this review, the developments in the field of (plasmonic metal)/semiconductor hybrid nanostructures are comprehensively described. The preparation of the hybrid nanostructures is first presented according to the semiconductor type, as well as the nanostructure morphology. The plasmonic properties and the enabled applications of the hybrid nanostructures are then elucidated. Lastly, possible future research in this burgeoning field is discussed.

Metal/Semiconductor Hybrid Nanostructures for Plasmon-Enhanced Applications

Water electrolysis is an advanced energy conversion technology to produce hydrogen as a clean and sustainable chemical fuel, which potentially stores the abundant but intermittent renewable energy sources scalably. Since the overall water splitting is an uphill reaction in low efficiency, innovative breakthroughs are desirable to greatly improve the efficiency by rationally designing non-precious metal-based robust bifunctional catalysts for promoting both the cathodic hydrogen evolution and anodic oxygen evolution reactions. We report a hybrid catalyst constructed by iron and dinickel phosphides on nickel foams that drives both the hydrogen and oxygen evolution reactions well in base, and thus substantially expedites overall water splitting at 10 mA cm−2 with 1.42 V, which outperforms the integrated iridium (IV) oxide and platinum couple (1.57 V), and are among the best activities currently. Especially, it delivers 500 mA cm−2 at 1.72 V without decay even after the durability test for 40 h, providing great potential for large-scale applications.

/pdf/high-performance-bifunctional-porous-non-noble-metal-15q99mum9p.pdf

High Performance Bifunctional Porous Non-Noble Metal Phosphide Catalyst for Overall Water Splitting

The controlled synthesis of nanohybrids composed of noble metals (Au, Ag, Pt and Pd, as well as AuAg alloy) and metal oxides (ZnO, TiO2, Cu2O and CeO2) have received considerable attention for applications in photocatalysis, solar cells, drug delivery, surface enhanced Raman spectroscopy and many other important areas. The overall architecture of nanocomposites is one of the most important factors dictating the physical properties of nanohybrids. Noble metals can be coupled to metal oxides to yield diversified nanostructures, including noble metal decorated-metal oxide nanoparticles (NPs), nanoarrays, noble metal/metal oxide core/shell, noble metal/metal oxide yolk/shell and Janus noble metal–metal oxide nanostructures. In this review, we focus on the significant advances in tailored nanostructures of noble metal–metal oxide nanohybrids. The improvement in performance in the representative solar energy conversion applications including photocatalytic degradation of organic pollutants, photocatalytic hydrogen generation, photocatalytic CO2 reduction, dye-sensitized solar cells (DSSCs) and perovskite solar cells (PSCs) are discussed. Finally, we conclude with a perspective on the future direction and prospects of these controllable nanohybrid materials.

Noble metal–metal oxide nanohybrids with tailored nanostructures for efficient solar energy conversion, photocatalysis and environmental remediation

Energy consumption forecasting for buildings has immense value in energy efficiency and sustainability research. Accurate energy forecasting models have numerous implications in planning and energy optimization of buildings and campuses. For new buildings, where past recorded data is unavailable, computer simulation methods are used for energy analysis and forecasting future scenarios. However, for existing buildings with historically recorded time series energy data, statistical and machine learning techniques have proved to be more accurate and quick. This study presents a comprehensive review of the existing machine learning techniques for forecasting time series energy consumption. Although the emphasis is given to a single time series data analysis, the review is not just limited to it since energy data is often co-analyzed with other time series variables like outdoor weather and indoor environmental conditions. The nine most popular forecasting techniques that are based on the machine learning platform are analyzed. An in-depth review and analysis of the ‘hybrid model’, that combines two or more forecasting techniques is also presented. The various combinations of the hybrid model are found to be the most effective in time series energy forecasting for building.

A review on time series forecasting techniques for building energy consumption

Time series forecasting for building energy consumption using weighted Support Vector Regression with differential evolution optimization technique

Anisotropic Growth of Titania onto Various Gold Nanostructures: Synthesis, Theoretical Understanding, and Optimization for Catalysis

Organic materials have gained considerable attention for electrochromic (EC) applications owing to improved EC performance and good processability. As a class of well-recognized organic EC materials, viologens have received persistent attention due to the structural versatility and property tunability, and are major active EC components for most of the marketed EC devices. Over the past two decades, extensive efforts have been made to design and synthesize different types of viologen-based materials with enhanced EC properties. This review summarizes chemical structures, preparation and EC properties of various latest viologen-based electrochromes, including small viologen derivatives, main-chain viologen-based polymers, conjugated polymers with viologen side-chains and viologen-based organic/inorganic composites. The performance enhancement mechanisms are concisely discussed. The current marketed viologens-based electrochromic devices (ECDs) are briefly introduced and an outlook on the challenges and future exploration directions for viologen-based materials and their ECDs are also proposed.

https://www.mdpi.com/2073-4360/11/11/1839/pdf

Kwok Wei Shah

Papers

A review on time series forecasting techniques for building energy consumption

Time series forecasting for building energy consumption using weighted Support Vector Regression with differential evolution optimization technique

Anisotropic Growth of Titania onto Various Gold Nanostructures: Synthesis, Theoretical Understanding, and Optimization for Catalysis

Viologen-Based Electrochromic Materials: From Small Molecules, Polymers and Composites to Their Applications

Synthesis and multiple reuse of eccentric Au@TiO2 nanostructures as catalysts