{'fraction_non_alphanumeric': 0.027761711972238288, 'fraction_numerical': 0.024291497975708502, 'mean_word_length': 6.723214285714286, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Nonlinear sensors for biomaterials—Principles and applications

It is essential that composition–structure–property relationships for biomaterials be understood in order to assure optimum clinical performance, and there has been a continuing quest to develop characterization modalities that replicate usage conditions in an acceptable manner. Biomaterials characterization originally involved the linear methods of tension, compression, bending and torsion tests to evaluate mechanical properties (Dowling, 1993), linear polarization to study corrosion (Fontana, 1986) and linear differential thermal analysis to determine structural transitions (Wendlandt, 1986). It was evident from these textbooks that investigators had appreciated that the linear techniques provided incomplete information, as time-dependent nonlinear responses to physical inputs occurred for many materials, notably metals and polymers. As experimental approaches and laboratory instrumentation have evolved and become more sophisticated in recent decades, the foregoing traditional characterization methodologies have been supplemented by the nonlinear techniques of dynamic mechanical analysis (DMA), electrochemical impedance spectroscopy (EIS) and temperature-modulated differential scanning calorimetry (TMDSC). These nonlinear techniques, which are essentially advanced laboratory sensors, have remarkably similar scientific foundations, in which both the nonlinear and linear responses to an alternating input (mechanical stress, electrical potential or temperature change) to a material are analysed mathematically. The nonlinear response component Received: 22 December 2019 | Revised: 11 May 2020 | Accepted: 11 May 2020 DOI: 10.1002/mds3.10101