Single-Step Direct Laser Writing of Multimetal Oxygen Evolution Catalysts from Liquid Precursors

Laser Synthesis of PtMo Single-Atom Alloy Electrode for Ultralow Voltage Hydrogen Generation

Maximizing atom-utilization efficiency and high current stability are crucial for the platinum (Pt)-based electrocatalysts for hydrogen evolution reaction (HER). Herein, the Pt single-atom anchored molybdenum (Mo) foil (Pt-SA/Mo-L) as a single-atom alloy electrode is synthesized by the laser ablation strategy. The local thermal effect with fast rising-cooling rate of laser can achieve the single-atom distribution of the precious metals (e.g., Pt, Rh, Ir, and Ru) onto the Mo foil. The synthesized self-standing Pt-SA/Mo-L electrode exhibits splendid catalytic activity (31 mV at 10 mA cm-2 ) and high-current-density stability (≈850 mA cm-2 for 50 h) for HER in acidic media. The strong coordination of Pt-Mo bonding in Pt-SA/Mo-L is critical for the efficient and stable HER. In addition, the ultralow electrolytic voltage of 0.598 V to afford the current density of 50 mA cm-2 is realized by utilization of the anodic molybdenum oxidation instead of the oxygen evolution reaction (OER). Here a universal synthetic strategy of single-atom alloys (PtMo, RhMo, IrMo, and RuMo) as self-standing electrodes is provided for ultralow voltage and membrane-free hydrogen production.

In Pursuit of the Exceptional: Research Directions for Machine Learning in Chemical and Materials Science

Exceptional molecules and materials with one or more extraordinary properties are both technologically valuable and fundamentally interesting, because they often involve new physical phenomena or new compositions that defy expectations. Historically, exceptionality has been achieved through serendipity, but recently, machine learning (ML) and automated experimentation have been widely proposed to accelerate target identification and synthesis planning. In this Perspective, we argue that the data-driven methods commonly used today are well-suited for optimization but not for the realization of new exceptional materials or molecules. Finding such outliers should be possible using ML, but only by shifting away from using traditional ML approaches that tweak the composition, crystal structure, or reaction pathway. We highlight case studies of high-Tc oxide superconductors and superhard materials to demonstrate the challenges of ML-guided discovery and discuss the limitations of automation for this task. We then provide six recommendations for the development of ML methods capable of exceptional materials discovery: (i) Avoid the tyranny of the middle and focus on extrema; (ii) When data are limited, qualitative predictions that provide direction are more valuable than interpolative accuracy; (iii) Sample what can be made and how to make it and defer optimization; (iv) Create room (and look) for the unexpected while pursuing your goal; (v) Try to fill-in-the-blanks of input and output space; (vi) Do not confuse human understanding with model interpretability. We conclude with a description of how these recommendations can be integrated into automated discovery workflows, which should enable the discovery of exceptional molecules and materials.

Invisible Bactericidal Coatings on Generic Surfaces through a Convenient Hand Spray

Robust antimicrobial coatings featuring high transparency, strong bactericidal activity, and an easy application procedure on generic surfaces can be widely accepted by the public to prevent pandemics. In this work, we demonstrated the hand-sprayer-based approach to deposit complex oxide coatings composed of Co-Mn-Cu-Zn-Ag on screen protectors of smartphones through acidic redox-assisted deposition (ARD). The as-obtained coatings possess high transparency (99.74% transmittance at 550 nm) and long-lasting durability against swiping (for 135 days of average use) or wet cleaning (for a routine of 3 times/day for 33 days). The spray coating enabling 3.14% Escherichia coli viability can further be reduced to 0.21% through a consistent elemental composition achieved via the immersion method. The high intake of Cu²⁺ in the coating is majorly responsible for the bactericidal activity, and the presence of Ag⁺ and Zn²⁺ is necessary to achieve almost complete eradication. The success of extending the bactericidal coatings on other typical hand-touched surfaces (e.g., stainless steel railings, rubber handrails, and plastic switches) in public areas has been demonstrated.

Improvement of Yttrium Oxyfluoride Coating with Modified Precursor Solution for Laser-Induced Hydrothermal Synthesis

In the semiconductor manufacturing process, the inner walls of the equipment are coated with yttrium-based oxides for etch resistance against plasma exposure. Yttrium oxyfluoride (YOF) particle synthesis and coating methods have been actively studied owing to their high erosion resistance compared to Y2O3 and Al2O3. Owing to the formation of a rough and porous coating layer by thermal spray-coating, the coating layer disintegrates, as the etching process has been conducted for a long time. Laser-induced synthesis and coating technology offer several advantages, including simplified process steps, ease of handling, and formation of a dense coating layer on the target material. In this study, YOF was coated on an aluminum substrate using a modified precursor solution. The NaF and HMTA were added to the precursor solution, resulting in enhanced synthetic reactivity and stabilizing the oxides. The material coated on the surface was analyzed based on the characteristics of composition, chemical bonding, and phase identification. We found that the coating properties can be improved by using an appropriate combination of modified precursor solutions and laser parameters. Therefore, the findings in this study are expected to be utilized in the field of coating technology.

Modulating the oxidation states in nickel–iron layered double hydroxides by natural cooling for enhanced oxygen evolution activity

Modulating the relationship of oxidation state–OER activity by natural cooling.