Structure-Function Relationship of Highly Reactive CuOx Clusters on Co3 O4 for Selective Formaldehyde Sensing at Low Temperatures

Designing reactive surface clusters at the nanoscale on metal-oxide supports enables selective molecular interactions in low-temperature catalysis and chemical sensing. Yet, finding effective material combinations and identifying the reactive site remains challenging and an obstacle for rational catalyst/sensor design. Here, the low-temperature oxidation of formaldehyde with CuOx clusters on Co3 O4 nanoparticles is demonstrated yielding an excellent sensor for this critical air pollutant. When fabricated by flame-aerosol technology, such CuOx clusters are finely dispersed, while some Cu ions are incorporated into the Co3 O4 lattice enhancing thermal stability. Importantly, infrared spectroscopy of adsorbed CO, near edge X-ray absorption fine structure spectroscopy and temperature-programmed reduction in H2 identified Cu+ and Cu2+ species in these clusters as active sites. Remarkably, the Cu+ surface concentration correlated with the apparent activation energy of formaldehyde oxidation (Spearman's coefficient ρ = 0.89) and sensor response (0.96), rendering it a performance descriptor. At optimal composition, such sensors detected even the lowest formaldehyde levels of 3 parts-per-billion (ppb) at 75°C, superior to state-of-the-art sensors. Also, selectivity to other aldehydes, ketones, alcohols, and inorganic compounds, robustness to humidity and stable performance over 4 weeks are achieved, rendering such sensors promising as gas detectors in health monitoring, air and food quality control.

A proposal for a new PhD level curriculum on quantitative methods for drug development

This paper provides an overview of "Improving Design, Evaluation and Analysis of early drug development Studies" (IDEAS), a European Commission-funded network bringing together leading academic institutions and small- to large-sized pharmaceutical companies to train a cohort of graduate-level medical statisticians. The network is composed of a diverse mix of public and private sector partners spread across Europe, which will host 14 early-stage researchers for 36 months. IDEAS training activities are composed of a well-rounded mixture of specialist methodological components and generic transferable skills. Particular attention is paid to fostering collaborations between researchers and supervisors, which span academia and the private sector. Within this paper, we review existing medical statistics programmes (MSc and PhD) and highlight the training they provide on skills relevant to drug development. Motivated by this review and our experiences with the IDEAS project, we propose a concept for a joint, harmonised European PhD programme to train statisticians in quantitative methods for drug development.