Layered Titanium Carbides Mediated Fast Shape?Switching, and Excellent Thermal and Electrical Transport in Shape?Memory?Polymer?Composites for Smart Technologies: MAX versus MXene

Stimuli?responsive materials can frequently tune between their temporary and original shapes, and have the potential for artificial intelligence?based technologies in robotics, aerospace, biomedical, engineering, security, etc. Shape memory polymers (SMPs) are promising materials for these technologies but their inadequate thermal and electrical characteristics causing slow shape?recovery limit their practical applications. Here we, for the first time, comprehensively and precisely engineer the shape memory polyurethane (PU), a promising SMP, via a variety of novel layered titanium carbides fillers, namely, Ti2AlC (MAX1), Ti3AlC2 (MAX2), and Ti3C2 (MXene). The resultant PU?MAX1, PU?MAX2, and PU?MXene composites show ?30?50% faster shape recovery in different environments, ?20?25% greater extent of shape recovery in the load?constrained environment, ?100?125% higher thermal conductivity, and ?700?16000x higher electrical current (or conduction). Importantly, the reinforcement of even a small amount of MAX and MXene (such as 0.25 wt. %) has largely boosted the performance of PU. Importantly, when comparing the extent of enhancement of properties, the MAX?phase fillers could be preferred over MXene?phase fillers for composites due to their ease of production. Employing PU?composite component as both heat?sensor and actuator, we demonstrate a unique heat detector/fire alarm device that works successfully in simulated heat and fire environments. This work is crucial for enabling futuristic?technologies.This article is protected by copyright. All rights reserved.

» Author: Shubham Jaiswal, Jeet Vishwakarma, Shubham Bhatt, Saheb Karak, Pankaj Bharti, Chetna Dhand, Rajeev Kumar, Pradip Kumar, Mohammad S. M. Saifullah, Surajit Saha, Rahul Mishra, Neeraj Dwivedi

» Publication Date: 09/06/2023

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This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement Nº 768737


                   




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