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In order to improve the flame retardancy and smoke suppression of silicone rubber foam (SRF), the CoFe‐LDH was fabricated by coprecipitation method and used as flame‐retardant ingredient in SRF. The influence of CoFe‐LDH on the flame retardancy, combustion behavior, and thermal stability of SRF was investigated. The results demonstrate that SRF containing only 1.0 phr CoFe‐LDH can pass V‐0 rating in the vertical combustion test, with a limiting oxygen index of 28.6%. The total heat release and total smoke production are 22.2% and 61.1% lower than that of SRF, respectively. Moreover, CoFe‐LDH can improve the thermal stability of SRF in the high temperature range, and the char residue at 900°C of SRF/LDH composite is obviously higher than that of pure SRF. In addition, to further understand the flame‐retardant mechanism of CoFe‐LDH, the micromorphology of the char residue and the gaseous products during heating for SRF and SRF/LDH composite were analyzed. The results indicate that CoFe‐LDH exhibits excellent flame‐retardant effects in both condensed and gaseous phases for its functions of catalysis, carbonization, and nonflammable gas release. This study provides a more efficient and convenient strategy for the flame retardant and smoke suppression research of SRF. [ABSTRACT FROM AUTHOR]

In the pricing of customized products, it is challenging to accurately predict the purchase likelihood of potential clients for each personalized request. The heterogeneity of customers and their responses to the personalized products leads to very different purchase behavior. Thus, it is often not appropriate to use a single model to analyze all the pricing data. There is a great need to construct distinctive models for different data segments. In this work, we propose an adaptive convex clustering method to perform data segmentation and model fitting simultaneously for generalized linear models. The proposed method segments data points using the fused penalty to account for the similarity in model structures. It ensures that the data points sharing the same model structure are grouped into the same segment. Accordingly, we develop an efficient algorithm for parameter estimation and study its consistency properties in estimation and clustering. The performance of our approach is evaluated by both numerical examples and case studies of real business data. [ABSTRACT FROM AUTHOR]

When it passed over the surface of Fe2O3, H2S was catalytically oxidized by O2 in air that resulted in intensive chemiluminescence (CL). A novel H2S sensor based on this kind of CL was developed. Six catalysts were examined and the results showed that the CL intensity based on Fe2O3 was almost 10 times higher than that of the other five. An important advantage of the novel CL H2S sensor was its high selectivity to H2S without the response to other 12 kinds of gases such as hydrocarbon, alcohol, NO2, etc. The response time of the CL sensor to H2S was within 15 s and the recovery time was within 120 s. The linear range of the CL sensor under the optimal conditions was in the range from 8 to 2000 ppm over two orders of magnitude with the detection limit of 3 ppm. The stability of the sensor was examined for 100 h by introduction of 100 ppm H2S into the sensor. No significant decrease of CL signals has been recorded during the time. [Copyright &y& Elsevier]