What’s Up With Catalight! · Episode

In a year-long study analyzing 725 autistic children across the United States, the Catalight Research Institute found that higher hours helped with short-term goals but did not improve broader functio...

Modeling polymer brushes is essential for understanding their complex behavior at surfaces and interfaces, enabling the design of materials with tunable properties. We present a computational protocol to model polymer brushes composed of grafted, brush-like chains of the charged polymer poly(N,N-dimethylaminoethyl methacrylate) (p(DMAEMA)) using an all-atom representation that captures detailed molecular interactions and structural properties. The approach is flexible and non-grid-based and allows for randomized strand configurations and the incorporation of periodic boundary conditions, enabling the construction of asymmetric polymer brush setups. An atactic p(DMAEMA) configuration is demonstrated as an example, though the protocol can be readily adapted to construct other brush-like polymer systems with varying tacticities or compositions, depending on the pH environment. Furthermore, this can be extended to stimuli-responsive materials, which generate conformation or charge upon changes in pH value or other external triggers. Molecular dynamics simulations are then employed to gain insights into the conformational behavior of the grafted p(DMAEMA) brushes and their surrounding aqueous environment, as well as their response to temperature, protonation, and variations in grafting densities, in terms of the solvent-accessible surface area, radius of gyration, and radial distribution functions. This versatile protocol provides a robust tool for simulating and analyzing the properties of diverse polyelectrolyte polymer brush systems and also as composite materials.

Education Podcast · Updated Monthly · Catalight is changing how the world supports people with autism along with other intellectual and developmental disabilities. We’re building a more equitable futu...

A recent peer-reviewed study reveals how the Catalight Family Wellbeing Scale adapts across cultures, aiding families with autism and developmental disabilities in understanding their wellbeing.

A new collaboration between Catalight Group and Cognoa aims to revolutionize autism diagnosis and treatment, addressing significant access issues faced by families.

A recent study challenges long-held beliefs that more treatment hours help autistic children. Discover essential insights into therapy effectiveness.

Let’s shift the narrative.

Catalight Academy has launched five online courses aimed at helping parents of autistic children. These courses cover essential topics and strategies.

An open-source and modular Python package, Catalight, is developed and demonstrated to automate (photo)catalysis measurements. (Photo)catalysis experiments require studying several parameters to evaluate performance, including temperature, gas flow rate and composition, illumination power, and spectral profile. Catalight orchestrates measurements over this complicated parameter space and systematically stores, analyzes, and visualizes the resulting data. To showcase the capabilities of Catalight, we perform an automated apparent activation barrier measurement of acetylene hydrogenation over a plasmonic AuPd catalyst on Al2O3 support, simultaneously varying laser power, wavelength, and temperature in a multi-day experiment controlled by a simple Python script. Our chemical results unexpectedly show an increased activation barrier upon light excitation, contrary to previous findings for other plasmonic reactions and catalysts. We show that the reaction rate order with respect to both acetylene and hydrogen is unchanged upon illumination, suggesting that molecular surface coverage is not changing under light excitation. By analyzing the inhomogeneity of the laser induced heating, we attribute these results to a partial photothermal effect combined with a photochemical/hot electron driven mechanism. Our findings highlight the capabilities of a new experiment automation tool; explore the photocatalytic mechanism for an industrially relevant reaction; and identify systematic sources of error in canon photocatalysis experimental procedures.