Mohammad Ziaur Rahman

2D phosphorene as a water splitting photocatalyst: fundamentals to applications

Hydrogen from direct splitting of water molecules using photons is reckoned to be a sustainable and renewable energy solution for the post fossil-fuel era. Efficient photocatalysts, including metal-free photocatalysts, are key determinants of cost-effective hydrogen generation at a large-scale. The search for new materials that are metal-free is therefore ongoing. Recently, 2D phosphorene, a phosphorus analogue of graphene, has been added as a new semiconductor to the family of monolayer-flatland materials. In this review, we focus on analysing the fundamental electronic, optical and chemical properties of 2D phosphorene and assess its suitability as a metal-free water splitting photocatalyst. We also critically analyse its stability against claims from environmental antagonists and attempt to predict its future as a photocatalyst. This review provides timely information for researchers, scientists and professionals devoted to materials research for photocatalysis.

Surface activated carbon nitride nanosheets with optimized electro-optical properties for highly efficient photocatalytic hydrogen production

Incomplete polycondensation of the precursor, structural destruction and blue-shift of 2D nanosheets of carbon nitride are nowadays the serious problems. Therefore, optimization of the structural and electro-optical properties of carbon nitride, and reduction of its dependency on the high loading of the Pt cocatalyst needed for enhanced photocatalytic performance is of urgent necessity for sustainable and low-cost hydrogen production from water. To address this issue, we report sub-nanometer-thin carbon nitride nanosheets, which are fabricated by a combined three-step method including co-polymerization, surface activation and exfoliation. The resultant nanosheets are structurally very robust and photocatalytically highly efficient as evidenced by 38 times enhancement in their hydrogen production rate as compared to the pristine carbon nitride, with 100 times smaller loading of Pt as a co-catalyst. The extended visible-light absorption, suppressed charge carrier recombination, enhanced charge separation, low over potential and high surface area are the prominent reasons behind this unprecedented improvement.

Carbon, nitrogen and phosphorus containing metal-free photocatalysts for hydrogen production: progress and challenges

Photocatalytic hydrogen production from water is a green and renewable path for solar fuel production. Hydrogen can be advantageously stored directly and burned without emission of deleterious CO and NOx gases. Photocatalysis therefore shows significant promise as a part solution to a sustainable and affordable energy supply in an era post-fossil fuels. Influenced by the Fujishima–Honda effect, significant advances in photocatalytic hydrogen production have occurred at the laboratory-scale. For wide adoption however, the photocatalysts will need to be made from earth-abundant materials, be stable and scalable from laboratory-to-large-scale, and have high conversion efficiency. In this regard, metal-free photocatalysts show practical promise in meeting these requirements. To foster research in materials design, here we critically review recent significant developments in metal-free photocatalysts consisting of carbon, nitrogen and phosphorus, and discuss how future large-scale hydrogen production via overall water-splitting could be accomplished economically.

Counteracting Blueshift Optical Absorption and Maximizing Photon Harvest in Carbon Nitride Nanosheets Photocatalyst

Blueshift of optical absorption and corresponding widening of the bandgap is a fundamental problem with 2D carbon nitride nanosheets (CNNS). An additional problem is low quantum yields (<9%) due to higher loss of absorbed photons. These problems impose a significant restriction to photocatalytic performance of CNNS. Therefore, the synthesis of narrow bandgap CNNS with high quantum efficiency is of pressing research importance. This contribution reports melem-derived narrow bandgap CNNS with a record-low bandgap of 2.45 eV. The narrowing in bandgap comes with improved optical absorption and use of visible-light photons together with excellent charge transport dynamics. This is demonstrated by a record high hydrogen evolution rate of 863 µmol h-1 with apparent quantum efficiency of 16% at 420 nm.

Graphene oxide coupled carbon nitride homo-heterojunction photocatalyst for enhanced hydrogen production

This contribution reports the synthesis, characterization and application of a new ternary homo-heterojunction photocatalyst for improved hydrogen production via water-splitting. The heterostructure is constructed by soft-grafting of graphitic carbon nitride (GCN) and graphene oxide (GO) into an amorphous carbon nitride (ACN) substrate. In this ternary hybrid, a cascaded redox-junction is formed that significantly facilitates the separation of photogenerated electron–hole pairs (EHPs), retards EHP recombination and shuttles electrons to the photocatalyst/liquid interface for proton reduction reactions. When deposited with 3 wt% Pt as a cocatalyst, this new photocatalyst exhibits hydrogen production of 251 μmol h−1 from 10 vol% aqueous triethanolamine solution under visible light (420 nm) irradiation with an apparent quantum efficiency of 6.3%. This ternary photocatalyst therefore outperforms stand-alone/binary photocatalysts and promises to be a viable alternative to metal-based photocatalysts.

Topological carbon nitride: localized photon absorption and delocalized charge carrier separation at intertwined photocatalyst interfaces

We here introduce, for the first time, a topological carbon nitride (TCN) with built-in crystalline–amorphous phases. Topologically anchored dual complementary phases allow localized photon absorption of different wavelengths, and provide a twinned photocatalyst interface to facilitate geminate charge carrier pair separation. These unique attributes, which are absent in widely used graphitic carbon nitride (GCN) and amorphous carbon nitride (ACN) photocatalysts, are highly desirable for precious metal (i.e. Pt) cocatalyst-free hydrogen production via water-splitting. Our results are substantiated with both experiments and simulations.

Correction: 2D phosphorene as a water splitting photocatalyst: fundamentals to applications

Correction for ‘2D phosphorene as a water splitting photocatalyst: fundamentals to applications’ by Mohammad Ziaur Rahman et al., Energy Environ. Sci., 2016, 9, 709–728.

Reduced recombination and low-resistive transport of electrons for photo-redox reactions in metal-free hybrid photocatalyst

Photoinduced charge separation against their faster recombination is a rate determinant for photocatalytic proton reduction to hydrogen. Dissociation of electron-hole pairs into free electrons and holes in carbon nitrides greatly suffered from the inherent high recombination rate. This study has shown that coupling two energetically optimized, but with different phases carbon nitrides in the form of hybrid could significantly inhibit the charge carrier recombination and facilitate the overall charge transfer processes. It is also found that the potential gradient in this homojunction delocalizes electrons and holes, and increases the spatial charge separation. Therefore, this leads to a record high apparent quantum efficiency of 5% for photocatalytic H2 production from water under visible light irradiation in the absence of a precious metal (e.g., Pt) cocatalyst.Photoinduced charge separation against their faster recombination is a rate determinant for photocatalytic proton reduction to hydrogen. Dissociation of electron-hole pairs into free electrons and holes in carbon nitrides greatly suffered from the inherent high recombination rate. This study has shown that coupling two energetically optimized, but with different phases carbon nitrides in the form of hybrid could significantly inhibit the charge carrier recombination and facilitate the overall charge transfer processes. It is also found that the potential gradient in this homojunction delocalizes electrons and holes, and increases the spatial charge separation. Therefore, this leads to a record high apparent quantum efficiency of 5% for photocatalytic H2 production from water under visible light irradiation in the absence of a precious metal (e.g., Pt) cocatalyst.

A new statistical framework for genetic pleiotropic analysis of high dimensional phenotype data

BackgroundThe widely used genetic pleiotropic analyses of multiple phenotypes are often designed for examining the relationship between common variants and a few phenotypes. They are not suited for both high dimensional phenotypes and high dimensional genotype (next-generation sequencing) data.To overcome limitations of the traditional genetic pleiotropic analysis of multiple phenotypes, we develop sparse structural equation models (SEMs) as a general framework for a new paradigm of genetic analysis of multiple phenotypes. To incorporate both common and rare variants into the analysis, we extend the traditional multivariate SEMs to sparse functional SEMs. To deal with high dimensional phenotype and genotype data, we employ functional data analysis and the alternative direction methods of multiplier (ADMM) techniques to reduce data dimension and improve computational efficiency.ResultsUsing large scale simulations we showed that the proposed methods have higher power to detect true causal genetic pleiotropic structure than other existing methods. Simulations also demonstrate that the gene-based pleiotropic analysis has higher power than the single variant-based pleiotropic analysis. The proposed method is applied to exome sequence data from the NHLBI’s Exome Sequencing Project (ESP) with 11 phenotypes, which identifies a network with 137 genes connected to 11 phenotypes and 341 edges. Among them, 114 genes showed pleiotropic genetic effects and 45 genes were reported to be associated with phenotypes in the analysis or other cardiovascular disease (CVD) related phenotypes in the literature.ConclusionsOur proposed sparse functional SEMs can incorporate both common and rare variants into the analysis and the ADMM algorithm can efficiently solve the penalized SEMs. Using this model we can jointly infer genetic architecture and casual phenotype network structure, and decompose the genetic effect into direct, indirect and total effect. Using large scale simulations we showed that the proposed methods have higher power to detect true causal genetic pleiotropic structure than other existing methods.

Tuning the Intrinsic Properties of Carbon Nitride for High Quantum Yield Photocatalytic Hydrogen Production

Abstract The low quantum yield of photocatalytic hydrogen production in carbon nitride (CN) has been improved upon via the modulation of both the extrinsic and intrinsic properties of the material. Although the modification of extrinsic properties has been widely investigated in the past, recently there has been growing interest in the alteration of intrinsic properties. Refining the intrinsic properties of CN provides flexibility in controlling the charge transport and selectivity in photoredox reactions, and therefore makes available a pathway toward superior photocatalytic performance. An analysis of recent progress in tuning the intrinsic photophysical properties of CN facilitates an assessment of the goals, achievements, and gaps. This article is intended to serve this purpose. Therefore, selected techniques and mechanisms of the tuning of intrinsic properties of CN are critically discussed here. This article concludes with a recommendation of the issues that need to be considered for the further enhancement in the quantum efficiency of CN photocatalysts.