Effects of Zr dopants on properties of PtNi nanoparticles for ORR catalysis: A DFT modeling.

Pt-based alloys, such as Pt3Ni, are among the best electrocatalysts for oxygen reduction reaction (ORR) in polymer electrolyte membrane fuel cells. Doping of PtNi alloys with Zr was shown to enhance the durability of the operating ORR catalysts. Rationalizing these observations is hindered by the absence of atomic-level data for these tri-metallic materials, even when not exposed to the fuel cell operation conditions.

A Novel Gait Event Detection Algorithm Using a Thigh-Worn Inertial Measurement Unit and Joint Angle Information.

This paper describes the development and evaluation of a novel, threshold-based gait event detection algorithm utilizing only one thigh inertial measurement unit (IMU) and unilateral, sagittal plane hip and knee joint angles. The algorithm was designed to detect heel strike (HS) and toe off (TO) gait events, with the eventual goal of detection in a real-time exoskeletal control system. The data used in the development and evaluation of the algorithm were obtained from two gait databases, each containing synchronized IMU and ground reaction force (GRF) data.

The Pediatric Data Science and Analytics Subgroup of the Pediatric Acute Lung Injury and Sepsis Investigators Network: Use of Supervised Machine Learning Applications in Pediatric Critical Care Medicine Research.

Objective: Perform a scoping review of supervised machine learning in pediatric critical care to identify published applications, methodologies, and implementation frequency to inform best practices for the development, validation, and reporting of predictive models in pediatric critical care.

Design: Scoping review and expert opinion.

Setting: We queried CINAHL Plus with Full Text (EBSCO), Cochrane Library (Wiley), Embase (Elsevier), Ovid Medline, and PubMed for articles published between 2000 and 2022 related to machine learning concepts and pediatric critical illness.

Effects of Oxygen Adsorption on the Optical Properties of Ag Nanoparticles.

Plasmonic metal nanoparticles are efficient light harvesters with a myriad of sensing- and energy-related applications. For such applications, the optical properties of nanoparticles of metals such as Cu, Ag, and Au can be tuned by controlling the composition, particle size, and shape, but less is known about the effects of oxidation on the plasmon resonances. In this work, we elucidate the effects of O adsorption on the optical properties of Ag particles by evaluating the thermodynamic properties of O-decorated Ag particles with calculations based on the density functional theory and subsequently computing the photoabsorption spectra with a computationally efficient time-dependent density functional theory approach.