A single-structured multifunctional device capable of energy harvesting and sensing multiple physical signals has significant potential for a wide range of applications in the Internet of Things (IoT). In this study, the fabricated single-structured device based on methylammonium lead iodide–polyvinylidene fluoride (MAPbI3–PVDF) composite can harvest mechanical energy and simultaneously operate as a self-powered light and pressure sensor because of the combined photoelectric and piezoelectric/triboelectric properties of the MAPbI3–PVDF composite. Light-dependent dielectric and piezoelectric properties of composite films are thoroughly investigated. Light and contact electrification effect on device performance in both piezoelectric and triboelectric modes is also systematically investigated. When the device is operated as a harvester in both piezoelectric and triboelectric modes, remarkable light-driven outputs were observed under illumination; the outputs decreased in the piezoelectric mode, while they increased in the triboelectric mode. Such light-controlled properties enabled the device to operate as a self-powered photodetector with outstanding responsivity (∼129.2 V/mW), rapid response time (∼50 ms), and satisfactory detectivity (∼1.4 × 1010 Jones) in the piezoelectric mode. The same device could also operate as a pressure sensor that exhibited excellent pressure sensitivity values of 0.107 and 0.194 V/kPa in the piezoelectric and triboelectric modes, respectively. In addition, the device exhibits a fast response time with long-term on–off switching properties, excellent mechanical durability, and long-term stability.

Multiscale and multimodal imaging of material structures and properties provides solid ground on which materials theory and design can flourish. Recently, KAIST announced 10 flagship research fields, which include KAIST Materials Revolution: Materials and Molecular Modeling, Imaging, Informatics and Integration (M3I3). The M3I3 initiative aims to reduce the time for the discovery, design and development of materials based on elucidating multiscale processing–structure–property relationship and materials hierarchy, which are to be quantified and understood through a combination of machine learning and scientific insights. In this review, we begin by introducing recent progress on related initiatives around the globe, such as the Materials Genome Initiative (U.S.), Materials Informatics (U.S.), the Materials Project (U.S.), the Open Quantum Materials Database (U.S.), Materials Research by Information Integration Initiative (Japan), Novel Materials Discovery (E.U.), the NOMAD repository (E.U.), Materials Scientific Data Sharing Network (China), Vom Materials Zur Innovation (Germany), and Creative Materials Discovery (Korea), and discuss the role of multiscale materials and molecular imaging combined with machine learning in realizing the vision of M3I3. Specifically, microscopies using photons, electrons, and physical probes will be revisited with a focus on the multiscale structural hierarchy, as well as structure–property relationships. Additionally, data mining from the literature combined with machine learning will be shown to be more efficient in finding the future direction of materials structures with improved properties than the classical approach. Examples of materials for applications in energy and information will be reviewed and discussed. A case study on the development of a Ni–Co–Mn cathode materials illustrates M3I3’s approach to creating libraries of multiscale structure–property–processing relationships. We end with a future outlook toward recent developments in the field of M3I3.

This chapter deals with the development of ferroelectric polymer polyvinylidene fluoride (PVDF)-based nanogenerators. Due to its inherent flexibility, PVDF has been studied for application in nanogenerators. We first introduce PVDF and its copolymers, and briefly discuss their properties. Then, we discuss fabrication methods, including solution casting, spin coating, template-assisted method, electrospinning, thermal drawing, and dip coating. Using these methods, a wide variety of ferroelectric polymer structures can be fabricated. In addition to the performance enhancements provided by fabrication methods, the performance of PVDF-based nanogenerators has been improved by incorporating fillers that can alter the factors affecting the performance. Next, we review energy sources that can be exploited by PVDF-based nanogenerators to harvest electricity. The abundant energy sources in the environment include sound, wind flow, and thermal fluctuation. Finally, we discuss implantable PVDF-based nanogenerators. Another advantage of PVDF is its biocompatibility, which enables implantable nanogenerators. We believe that this chapter can also be helpful to researchers who study sensors and actuators as well as nanogenerators.