A chiral C3-symmetric cubane cluster, [Cu4I4(TMP)4], with enough long Cu-Cu distances to eliminate the presence of Cu-Cu interaction has been synthesized and characterized, which shows simultaneous luminescent thermochromism, solvatochromism, vapochromism, and mechanochromism and is a multiply stimuli-responsive chromic luminescent material. This complex could partly transform into a yellow-emissive bicapped cubane cluster, [Cu6I6(TMP)4(MeCN)2], in acetonitrile (MeCN) vapor and solution, which provides some insight into vapochromism and solvatiochromism. This work challenges and makes us reconsider the conventional viewpoint that Cu-Cu interaction is involved in thermochromism and mechanochromism of copper complexes.

This study presents an investigation of the acoustical properties of multi-component polyester nonwovens with experimental and numerical methods. Fifteen types of nonwoven samples made with staple, hollow and bi-component polyester fibers were chosen to carry out this study. The AFD300 AcoustiFlow device was employed to measure airflow resistivity. Several models were grouped in theoretical and empirical model categories and used to predict the airflow resistivity. A simple empirical model based on fiber diameter and fabric bulk density was obtained through the power-fitting method. The difference between measured and predicted airflow resistivity was analyzed. The surface impedance and sound absorption coefficient were determined by using a 45 mm Materiacustica impedance tube. Some widely used impedance models were used to predict the acoustical properties. A comparison between measured and predicted values was carried out to determine the most accurate model for multi-component polyester nonwovens. The results show that one of the Tarnow model provides the closest prediction to the measured value, with an error of 12%. The proposed power-fitted empirical model exhibits a very small error of 6.8%. It is shown that the Delany–Bazley and Miki models can accurately predict surface impedance of multi-component polyester nonwovens, but the Komatsu model is less accurate, especially at the low-frequency range. The results indicate that the Miki model is the most accurate method to predict the sound absorption coefficient, with a mean error of 8.39%.

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