Multi-Objective Robust Design Optimization for Crashworthiness Enhancement of Hybrid 2D Triaxially Braided Composite Tube Using Evolutionary Algorithms.

An innovative optimal design framework is developed aiming at enhancing the crashworthiness while ensuring the lightweight design of a hybrid two-dimensional triaxial braided composite (2DTBC) tube, drawing insights from the mesostructure of the composite material. To achieve these goals, we first compile the essential mechanical properties of the 2DTBC using a concentric cylinder model (CCM) and an analytical laminate model. Subsequently, a kriging surrogate model to elucidate the intricate relationship between design variables and macroscopic crashworthiness is developed and validated. Finally, employing multi-objective evolutionary optimization, we identify Pareto optimal solutions, highlighting that reducing the total fiber volume and increasing the glass fiber content in the total fiber volume are crucial for optimal crashworthiness and the lightweight design of the hybrid 2DTBC tube. By integrating advanced predictive modeling techniques with multi-objective evolutionary optimization, the proposed approach not only sheds light on the fundamental principles governing the crashworthiness of hybrid 2DTBC but also provides valuable insights for the design of robust and lightweight composite structures.

Flexible and Multifunctional Composites with Highly Strain Sensing and Impact Resistance Properties.

The development of smart protective clothing will help detect injuries from contact sports, traffic collisions, and other accidents. The combination of ecoflex, spacer fabric, and graphene-based aerogel provides a multifunctional composite. It shows a strain sensitivity of 17.71 at the strain range of 40~55%, a pressure sensitivity of 0.125 kPa-1 at the pressure range of 0~15 kPa, and a temperature sensitivity of -0.648 °C-1. After 50 impact tests, its protection coefficient only dropped from 60% to 55%. Additionally, it shows thermal insulation properties. The compression and impact process results of finite element numerical simulation analysis are in good agreement with the experimental results. The ecoflex/aerogel/spacer fabric sensor exhibits a simple structure, large pressure strain, high sensitivity, flexibility, and ease of fabrication, making it a candidate for smart protective clothing resistant to impact loads.

Strong, tough and anisotropic bioinspired hydrogels.

Soft materials are widely used in tissue engineering, soft robots, wearable electronics, etc. However, it remains a challenge to fabricate soft materials, such as hydrogels, with both high strength and toughness that are comparable to biological tissues. Inspired by the anisotropic structure of biological tissues, a novel solvent-exchange-assisted wet-stretching strategy is proposed to prepare anisotropic polyvinyl alcohol (PVA) hydrogels by tuning the macromolecular chain movement and optimizing the polymer network. The reinforcing and toughening mechanisms are found to be "macromolecule crystallization and nanofibril formation". These hydrogels exhibit excellent mechanical properties, such as extremely high fracture stress (12.8 ± 0.7 MPa) and fracture strain (1719 ± 77%), excellent modulus (4.51 ± 0.76 MPa), high work of fracture (134.47 ± 9.29 MJ m-3), and fracture toughness (305.04 kJ m-2) compared with other strong hydrogels and even natural tendons. In addition, excellent conductivity, strain sensing capability, water retention, freezing resistance, swelling resistance, and biocompatibility can also be achieved. This work provides a new and effective method to fabricate multifunctional anisotropic hydrogels with high tunable strength and toughness with potential applications in the fields of regenerative medicine, flexible sensors, and soft robotics.

Corporate Social Responsibility and Consumer Emotional Marketing in Big Data Era: A Mini Literature Review.

In the digital era, big data can strengthen the awareness of corporate social responsibility (CSR) and make CSR more transparent to consumers. While big data continues to deepen the business transformation of enterprises, it is also a process of constantly understanding consumption and public expectations. In this process, the cognitive structure of enterprises is constantly adjusted, no longer simply pursuing performance but constantly realizing the expectations of users and society in order to maintain performance. Through mass media, corporate media, and other platforms, CSR is easier to affect consumers' emotions. By reviewing the theory of emotional marketing and related research, this paper focuses on the different emotional ties between CSR and consumers and their different effects on consumers. This paper further emphasizes the profound significance of emotional marketing theory for understanding CSR in the era of big data. In addition, this paper also calls for more research based on big data technology, broken down by consumer needs - more specific attention to the different impacts of CSR on different consumers.