Synthesis of Neutral SiO/TiO Hydrosol and Its Application as Antireflective Self-Cleaning Thin Film

A neutral SiO2/TiO2 composite hydrosol was prepared by a coprecipitation-peptization method using titanium tetrachloride and silicon dioxide hydrosol as precursors. It is not only an antireflective self-cleaning coating material but also an environmental-benign material. Even heated at 700°C for 5 minutes in the tempering process, the as-prepared SiO2/TiO2 thin film still demonstrated antireflection and photocatalytic self-cleaning effect. The SiO2/TiO2 thin film increased near 2% of transmittance; however, the TiO2 thin film decreased 5% of transmittance at least. In addition to antireflection, the SiO2/TiO2 thin film decomposed the surface coated oleic acid under ultraviolet light and showed superhydrophilicity under dark for two days. The SiO2/TiO2 thin film also showed good photocatalytic degradation of methylene blue. With these antireflection, persistent superhydrophilicity, and photocatalytic self-cleaning effects, this prepared neutral SiO2/TiO2 hydrosol would be a good coating material for tempered glass and other building materials

Building and experimenting with an agent-based model to study the population-level impact of CommunityRx, a clinic-based community resource referral intervention

CommunityRx (CRx), an information technology intervention, provides patients with a personalized list of healthful community resources (HealtheRx). In repeated clinical studies, nearly half of those who received clinical “doses” of the HealtheRx shared their information with others (“social doses”). Clinical trial design cannot fully capture the impact of information diffusion, which can act as a force multiplier for the intervention. Furthermore, experimentation is needed to understand how intervention delivery can optimize social spread under varying circumstances. To study information diffusion from CRx under varying conditions, we built an agent-based model (ABM). This study describes the model building process and illustrates how an ABM provides insight about information diffusion through in silico experimentation. To build the ABM, we constructed a synthetic population (“agents”) using publicly-available data sources. Using clinical trial data, we developed empirically-informed processes simulating agent activities, resource knowledge evolution and information sharing. Using RepastHPC and chiSIM software, we replicated the intervention in silico, simulated information diffusion processes, and generated emergent information diffusion networks. The CRx ABM was calibrated using empirical data to replicate the CRx intervention in silico. We used the ABM to quantify information spread via social versus clinical dosing then conducted information diffusion experiments, comparing the social dosing effect of the intervention when delivered by physicians, nurses or clinical clerks. The synthetic population (N = 802,191) exhibited diverse behavioral characteristics, including activity and knowledge evolution patterns. In silico delivery of the intervention was replicated with high fidelity. Large-scale information diffusion networks emerged among agents exchanging resource information. Varying the propensity for information exchange resulted in networks with different topological characteristics. Community resource information spread via social dosing was nearly 4 fold that from clinical dosing alone and did not vary by delivery mode. This study, using CRx as an example, demonstrates the process of building and experimenting with an ABM to study information diffusion from, and the population-level impact of, a clinical information-based intervention. While the focus of the CRx ABM is to recreate the CRx intervention in silico, the general process of model building, and computational experimentation presented is generalizable to other large-scale ABMs of information diffusion.</p