Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
31
result(s) for
"Chalcogenides Industrial applications."
Sort by:
Progress of Metal Chalcogenides as Catalysts for Efficient Electrosynthesis of Hydrogen Peroxide
Hydrogen peroxide (H2O2) is a high-demand chemical, valued as a powerful and eco-friendly oxidant for various industrial applications. The traditional industrial method for producing H2O2, known as the anthraquinone process, is both costly and environmentally problematic. Electrochemical synthesis, which produces H2O2 using electricity, offers a sustainable alternative, particularly suited for small-scale, continuous on-site H2O2 generation due to the portability of electrocatalytic devices. For efficient H2O2 electrosynthesis, electrocatalysts must exhibit high selectivity, activity, and stability for the two-electron pathway-oxygen reduction reaction (2e− ORR). Transition-metal chalcogenide (TMC)-based materials have emerged as promising candidates for effective 2e− ORR due to their high activity in acidic environments and the abundance of their constituent elements. This review examines the potential of TMC-based catalysts in H2O2 electrosynthesis, categorizing them into noble-metal and non-noble-metal chalcogenides. It underscores the importance of achieving high selectivity, activity, and stability in 2e− ORR. By reviewing recent advancements and identifying key challenges, this review provides valuable insights into the development of TMC-based electrocatalysts for sustainable H2O2 production.
Journal Article
A Review on Chemical Vapour Deposition of Two-Dimensional MoS2 Flakes
Two-dimensional (2D) materials such as graphene, transition metal dichalcogenides, and boron nitride have recently emerged as promising candidates for novel applications in sensing and for new electronic and photonic devices. Their exceptional mechanical, electronic, optical, and transport properties show peculiar differences from those of their bulk counterparts and may allow for future radical innovation breakthroughs in different applications. Control and reproducibility of synthesis are two essential, key factors required to drive the development of 2D materials, because their industrial application is directly linked to the development of a high-throughput and reliable technique to obtain 2D layers of different materials on large area substrates. Among various methods, chemical vapour deposition is considered an excellent candidate for this goal thanks to its simplicity, widespread use, and compatibility with other processes used to deposit other semiconductors. In this review, we explore the chemical vapour deposition of MoS2, considered one of the most promising and successful transition metal dichalcogenides. We summarize the basics of the synthesis procedure, discussing in depth: (i) the different substrates used for its deposition, (ii) precursors (solid, liquid, gaseous) available, and (iii) different types of promoters that favour the growth of two-dimensional layers. We also present a comprehensive analysis of the status of the research on the growth mechanisms of the flakes.
Journal Article
Chalcogenide mechanochemistry in materials science: insight into synthesis and applications (a review)
The aim of this paper on recent development in chalcogenide mechanochemistry is to provide a comprehensive review of advances achieved in the field of mechanochemical synthesis of nanocrystalline binary, ternary and quaternary chalcogenides and their nanocomposites. The synthetic approaches from elements and compounds are reviewed. The current focus of mechanochemical synthesis is on materials with potential utilization in future. In order to demonstrate the suitability of mechanochemically prepared chalcogenides for various applications, the concrete examples of the utilization of these materials in materials engineering, bioimaging and cancer treatment are provided. The possibility of scaling for industrial applications is also reviewed. The simplification of the synthesis processes with their reproducibility and easy way of operation, ecological safety and the product extraordinariness (nanoscale aspects) emphasizes the suitability of mechanochemistry application in chalcogenide synthesis.
Journal Article
Stability and Performance of 3d Transition Metal Carbo‐Sulfides: A Density Functional Theory Exploration for Li‐Ion Battery Anodes
As the demand for high‐performance and reliable energy storage devices continues to rise, identifying new anode materials is crucial for advancing Li‐ion battery (LIB) technology. Inspired by recent experimental breakthroughs in synthesizing two‐dimensional transition metal carbo‐chalcogenides (2D‐TMCCs), density functional theory calculations are performed to systematically explore their sulfide variants (TM2S2C) spanning all 3d transition metals in three possible phases. Through comprehensive evaluations of thermodynamic, dynamic, mechanical, and thermal stabilities, seven stable 2D‐TMCC candidates are identified, four of which exhibit superior battery performance. Notably, V‐based 2D‐TMCCs across all three phases deliver moderate open‐circuit voltages (OCV), efficient Li diffusion, and substantial capacities, making them promising candidates for industrial applications without requiring specific phase controls. A Cr‐based 2D‐TMCC (with sulfur atoms above carbon atoms) offers the highest capacity of 515.40 mAh g−1, the lowest Li diffusion barrier, and an optimal OCV, highlighting its appealing potential as an anode material for LIBs. Furthermore, significant Li–Li spacing and pronounced electron delocalization in these four 2D‐TMCCs suggest a reduced risk of dendrite formation. This work expands the 2D‐TMCC family and identifies up‐and‐coming candidates for next‐generation LIB anodes. 2D‐TM2S2C materials across 3d transition metals for Li‐ion battery (LIB) anodes are computationally screened. V‐ and Cr‐based systems present moderate open‐circuit voltages, high capacities, and fast Li diffusion. The results expand the two‐dimensional transition metal carbo‐chalcogenides family and highlight phase‐independent advantages, especially on V‐based systems, for next‐generation high‐performance and dendrite‐free LIB applications.
Journal Article
Active learning for accelerated design of layered materials
Hetero-structures made from vertically stacked monolayers of transition metal dichalcogenides hold great potential for optoelectronic and thermoelectric devices. Discovery of the optimal layered material for specific applications necessitates the estimation of key material properties, such as electronic band structure and thermal transport coefficients. However, screening of material properties via brute force ab initio calculations of the entire material structure space exceeds the limits of current computing resources. Moreover, the functional dependence of material properties on the structures is often complicated, making simplistic statistical procedures for prediction difficult to employ without large amounts of data collection. Here, we present a Gaussian process regression model, which predicts material properties of an input hetero-structure, as well as an active learning model based on Bayesian optimization, which can efficiently discover the optimal hetero-structure using a minimal number of ab initio calculations. The electronic band gap, conduction/valence band dispersions, and thermoelectric performance are used as representative material properties for prediction and optimization. The Materials Project platform is used for electronic structure computation, while the BoltzTraP code is used to compute thermoelectric properties. Bayesian optimization is shown to significantly reduce the computational cost of discovering the optimal structure when compared with finding an optimal structure by building a regression model to predict material properties. The models can be used for predictions with respect to any material property and our software, including data preparation code based on the Python Materials Genomics (PyMatGen) library as well as python-based machine learning code, is available open source.
Journal Article
Solvothermally fabricated cobalt selenide supported on graphitic carbon nitride for enhanced oxygen evolution reaction
Potentially superior to rare earth metal-containing electrocatalysts for the oxygen evolution reaction electrolysis, transition metal chalcogenides have yet to reach a catalytic activity that would allow them to be extensively adopted. In light of this, it is crucial to develop coherent designs for transition metal-based electrocatalysts on conducting polymer support to achieve high-efficiency OER. Herein, we present an easy solvothermal synthesis and exceptional catalytic performance of CoSe@gCN as an OER electrocatalyst in basic media. The synthesized materials were observed by various analysis. The phase composition confirmed by the X-rays diffraction (XRD) technique and further morphological analysis indicates the morphology of CoSe@gCN, which are considered responsible for revealing a great number of active spots and enhanced electrochemically active surface area. On the other hand, superior OER crusade and stability of the CoSe@gCN electrode with (overpotential of 174 mV, Tafel slope of 57 mV dec
−1
) in 1.0 M basic KOH are caused by the NF's excellent conductivity and highly porous framework, and a higher value of specific surface area. It also maintained high stability for almost 20 h, showing the higher OER activity in industrial application. As a result, our findings interpret that the transition metal chalcogenides with certain morphology can enhance electrocatalytic efficiency with graphitic carbon nitride, which demonstrates its potential for stable and sustainable energy production.
Graphical Abstract
Journal Article
Active learning for the power factor prediction in diamond-like thermoelectric materials
The Materials Genome Initiative requires the crossing of material calculations, machine learning, and experiments to accelerate the material development process. In recent years, data-based methods have been applied to the thermoelectric field, mostly on the transport properties. In this work, we combined data-driven machine learning and first-principles automated calculations into an active learning loop, in order to predict the p-type power factors (PFs) of diamond-like pnictides and chalcogenides. Our active learning loop contains two procedures (1) based on a high-throughput theoretical database, machine learning methods are employed to select potential candidates and (2) computational verification is applied to these candidates about their transport properties. The verification data will be added into the database to improve the extrapolation abilities of the machine learning models. Different strategies of selecting candidates have been tested, finally the Gradient Boosting Regression model of Query by Committee strategy has the highest extrapolation accuracy (the Pearson R = 0.95 on untrained systems). Based on the prediction from the machine learning models, binary pnictides, vacancy, and small atom-containing chalcogenides are predicted to have large PFs. The bonding analysis reveals that the alterations of anionic bonding networks due to small atoms are beneficial to the PFs in these compounds.
Journal Article
Predicting two-dimensional topological phases in Janus materials by substitutional doping in transition metal dichalcogenide monolayers
Ultrathin Janus two-dimensional (2D) materials are attracting intense interest currently. Substitutional doping of 2D transition metal dichalcogenides (TMDs) is of importance for tuning and possible enhancement of their electronic, physical and chemical properties toward industrial applications. Using systematic first-principles computations, we propose a class of Janus 2D materials based on the monolayers MX
2
(M = V, Nb, Ta, Tc, or Re; X = S, Se, or Te) with halogen (F, Cl, Br, or I) or pnictogen (N, P, As, Sb, or Bi) substitution. Nontrivial phases are obtained on pnictogen substitution of group VB (V, Nb, or Ta), whereas for group VIIB (Tc or Re), the nontrivial phases are obtained for halogen substitution. Orbital analysis shows that the nontrivial phase is driven by the splitting of M-
d
yz
and M-
d
xz
orbitals. Our study demonstrates that the Janus 2D materials have the tunability and suitability for synthesis under various conditions.
Journal Article
Accelerated discovery of a large family of quaternary chalcogenides with very low lattice thermal conductivity
The development of efficient thermal energy management devices such as thermoelectrics and barrier coatings often relies on compounds having low lattice thermal conductivity (κl). Here, we present the computational discovery of a large family of 628 thermodynamically stable quaternary chalcogenides, AMM′Q3 (A = alkali/alkaline earth/post-transition metals; M/M′ = transition metals, lanthanides; Q = chalcogens) using high-throughput density functional theory (DFT) calculations. We validate the presence of low κl in these materials by calculating κl of several predicted stable compounds using the Peierls–Boltzmann transport equation. Our analysis reveals that the low κl originates from the presence of either a strong lattice anharmonicity that enhances the phonon-scatterings or rattler cations that lead to multiple scattering channels in their crystal structures. Our thermoelectric calculations indicate that some of the predicted semiconductors may possess high energy conversion efficiency with their figure-of-merits exceeding 1 near 600 K. Our predictions suggest experimental research opportunities in the synthesis and characterization of these stable, low κl compounds.
Journal Article