Structure-catalytic functionality of size-facet-performance in pentlandite nanoparticles

As one of the pentlandites,Fe5Ni4S8(FNS) based materials have attracted increasing attention due to their excellent catalytic properties and promising applicability.The control over the catalyst surface structure often benefits its heterogeneous catalytic activity.However,this has not been investigated for FNS materials at the nanoscale regarding the catalytic activity related to high-index facets.Herein,FNS nanoparticles(FNSNPs) with enclosed continuous tunable high-index facets were prepared and studied to clarify the relationship between the structure and catalytic functionality.The results suggested strong dependence between exposed facets of FNSNPs and their sizes.The decline in the average size to5.8 nm led to enclosing by high-index facets(422) and(511) to yield optimal electrocatalytic activities toward the hydrogen evolution reaction.The catalytic activity of FNSNPs was closely related to the surface energy of the main exposed facets.These findings clarified the relationship between high-index-facet and high-surface-energy FNSNPs,as promising approaches in crystal surface control engineering.

Computational functionality-driven design of semiconductors for optoelectronic applications

The rapid development of the semiconductor industry has motivated researchers passion for accelerating the discovery of advanced optoelectronic materials.Computational functionality-driven design is an emerging branch of material science that has become effective at making material predictions.By combining advanced solid-state knowledge and high-throughput firstprinciples computational approaches with intelligent algorithms plus database development,experts can now efficiently explore many novel materials by taking advantage of the power of supercomputer architectures.Here,we discuss a set of typical design strategies that can be used to accelerate inorganic optoelectronic materials discovery from computer simulations:In silico computational screening;knowledge-based inverse design;and algorithm-based searching.A few representative examples in optoelectronic materials design are discussed to illustrate these computational functionality-driven modalities.Challenges and prospects for the computational functionality-driven design of materials are further highlighted at the end of the review.

New design for highly durable infrared-reflective coatings

The fundamental challenge in designing durable infrared-reflective coatings is achieving the ideal combination of both high reflectivity and durability.Satisfying these competing demands is traditionally achieved by deposition of durable layers on highly reflective metals.We overturn the traditional logic of‘first reflectivity and then durability’and propose an alternative of‘first durability and then reflectivity’:First,a transition-metal compound is selected as a durable base;then its reflectivity is improved by incorporating silver/gold to form an alloy or by overcoating a multilayer stack.Two validation experiments prove that the new strategy works extremely well:the coatings thus obtained have infrared reflectivities close to that of aluminum,and their hardness and acid and salt corrosion resistances are 27–50,400–1500 and 7500–25000 times that of aluminum.The traditional mirror coating(e.g.,Al/SiO2 films)is more suitable for moderate environments,while our mirror coating that was obtained by the new strategy(e.g.,an Ag-doped hafnium nitride film)is more suitable for harsh environments,such as ones with dust,windblown sand,moisture,acid rain or salt fog.This work opens up new opportunities for highly durable infrared-reflective coatings and rejuvenates the study of transition metal compounds in a completely new area of optics.