Machine learning (ML) has been perceived as a promising tool for the design and discovery of novel materials for a broad range of applications. In this prospective paper, we summarize recent progress in the applications of ML to composite materials modeling and design. An overview of how different types of ML algorithms can be applied to accelerate composite research is presented. This framework is envisioned to revolutionize approaches to design and optimize composites for the next generation of materials with unprecedented properties.

The ferroelectricity in fluorite-structure oxides such as hafnia and zirconia has attracted increasing interest since 2011. They have various advantages such as Si-based complementary metal oxide semiconductor-compatibility, matured deposition techniques, a low dielectric constant and the resulting decreased depolarization field, and stronger resistance to hydrogen annealing. However, the wake-up effect, imprint, and insufficient endurance are remaining reliability issues. Therefore, this paper reviews two major aspects: the advantages of fluorite-structure ferroelectrics for memory applications are reviewed from a material's point of view, and the critical issues of wake-up effect and insufficient endurance are examined, and potential solutions are subsequently discussed.

The growing application of data-driven analytics in materials science has led to the rise of materials informatics. Within the arena of data analytics, deep learning has emerged as a game-changing technique in the last few years, enabling numerous real-world applications, such as self-driving cars. In this paper, the authors present an overview of deep learning, its advantages, challenges, and recent applications on different types of materials data. The increasingly availability of materials databases and big data in general, along with groundbreaking advances in deep learning offers a lot of promise to accelerate the discovery, design, and deployment of next-generation materials.

Gelatin-based hydrogels derived from hydrolysis of collagen have been extensively used in pharmaceutical and medical applications because of their biocompatibility and biodegradability. For example, gelatin-based hydrogels are finding use in drug delivery and tissue engineering because they are able to promote cell adhesion and proliferation. In addition, these hydrogels can be used as wound dressings due to their attractive fluid absorbance properties. Manufacturing technologies such as ultraviolet stereolithography and two-photon polymerization can be used to prepare structures containing photosensitive gelatin-based hydrogels. This review describes the preparation of gelatin-based hydrogels and use of these materials for biomedical applications.

Unconventional techniques to benefit from the low-cost and high-efficiency monocrystalline silicon solar cells can lead to new device capabilities and engineering prospects. Here, a nature-inspired spherical solar cell is demonstrated, which is capable of capturing light three-dimensionally. The proposed cell architecture is based on monocrystalline silicon and is fabricated using a corrugation technique. The spherical cell shows an increase in power output by up to 101% with respect to a traditional flat cell with the same projection area using different reflective materials. Finally, the spherical cell shows advantages in terms of enhanced heat dissipation and reduced dust accumulation over conventional cells.

Materials design and discovery can be represented as selecting the optimal structure from a space of candidates that optimizes a target property. Since the number of candidates can be exponentially proportional to the structure determination variables, the optimal structure must be obtained efficiently. Recently, inspired by its success in the Go computer game, several approaches have applied Monte Carlo tree search (MCTS) to solve optimization problems in natural sciences including materials science. In this paper, we briefly reviewed applications of MCTS in materials design and discovery, and analyzed its future potential.

The current COVID-19 pandemic has caused the shortage of personal protective equipment (PPE) where improvised manufacturing in particular 3D printing has addressed many needs. This prospective discusses the current global crisis, then follows the wide interest in addressing the shortage of medical devices and PPEs used for treatment and protection against pathogens. An overview of the 3D printing process with polymer materials is given followed by the different 3D printing projects of PPEs and medical devices that emerged for the pandemic (including validation/testing). The potential for rapid prototyping with different polymer materials and eventual high-throughput production is emphasized.

Melanin (from the Greek μέλας, mélas, black) is a biopigment ubiquitous in flora and fauna, featuring broadband optical absorption, hydration-dependent electrical response, ion-binding affinity as well as antioxidative and radical-scavenging properties. In the human body, photoprotection in the skin and ion flux regulation in the brain are some biofunctional roles played by melanin. Here we discuss the progress in melanin research that underpins emerging technologies in energy storage/conversion, ion separation/water treatment, sunscreens, and bioelectronics. The melanin research aims at developing approaches to explore natural materials, well beyond melanin, which might serve as a prototype benign material for sustainable technologies.

Periodic lattice materials have been studied extensively in numerous science and engineering fields. Despite the vast knowledge that has emerged, the activities have been stove-piped within individual research communities, often in isolation from those in related fields. To bring this work into a holistic framework, the present article considers the elements needed to integrate the study of lattice materials into the processing–structure–properties paradigm that underpins materials science as an academic discipline. The emphasis is on concepts of structure involving topology, morphology, and defects of lattice materials, with illustrations of structure–property relations in the context of lattice strength.

The diverse and fascinating properties of transition metal oxides stem from the strongly correlated electronic degrees of freedom; the scientific challenge and range of possible applications of these materials have caused fascination among physicists and materials scientists, thus capturing research efforts for nearly a century. Here, we focus on the binary V x O y and the ternary perovskite AVO3 and review the key aspects from the underlying physical framework and their basic properties, recent strides made in thin-film synthesis, to recent efforts to implement vanadium-based oxides for practical applications that augment existing technologies, which surpass limitations of conventional materials.