Roadmap on multifunctional materials for drug delivery
This Roadmap on drug delivery aims to cover some of the most recent advances in the field of materials for drug delivery systems (DDSs) and emphasizes the role that multifunctional materials play in advancing the performance of modern DDS in the context of the most current challenges presented. The Roadmap is comprised of multiple sections, each of which introduces the status of the field, the current and future challenges faced, and a perspective of the required advances necessary for biomaterial science to tackle these challenges. It is our hope that this collective vision will contribute to the initiation of conversation and collaboration across all areas of multifunctional materials for DDSs. We stress that this article is not meant to be a fully comprehensive review but rather an up-to-date snapshot of different areas of research, with a minimal number of references that focus upon the very latest research developments.
Machine learning (ML)-assisted surface tension and oscillation-induced elastic modulus studies of oxide-coated liquid metal (LM) alloys
Pendant drops of oxide-coated high-surface tension fluids frequently produce perturbed shapes that impede interfacial studies. Eutectic gallium indium or Galinstan are high-surface tension fluids coated with a ∼5 nm gallium oxide (GaO) film and falls under this fluid classification, also known as liquid metals (LMs). The recent emergence of LM-based applications often cannot proceed without analyzing interfacial energetics in different environments. While numerous techniques are available in the literature for interfacial studies- pendant droplet-based analyses are the simplest. However, the perturbed shape of the pendant drops due to the presence of surface oxide has been ignored frequently as a source of error. Also, exploratory investigations of surface oxide leveraging oscillatory pendant droplets have remained untapped. We address both challenges and present two contributing novelties- (a) by utilizing the machine learning (ML) technique, we predict the approximate surface tension value of perturbed pendant droplets, (ii) by leveraging the oscillation-induced bubble tensiometry method, we study the dynamic elastic modulus of the oxide-coated LM droplets. We have created our dataset from LM's pendant drop shape parameters and trained different models for comparison. We have achieved >99% accuracy with all models and added versatility to work with other fluids. The best-performing model was leveraged further to predict the approximate values of the nonaxisymmetric LM droplets. Then, we analyzed LM's elastic and viscous moduli in air, harnessing oscillation-induced pendant droplets, which provides complementary opportunities for interfacial studies alternative to expensive rheometers. We believe it will enable more fundamental studies of the oxide layer on LM, leveraging both symmetric and perturbed droplets. Our study broadens the materials science horizon, where researchers from ML and artificial intelligence domains can work synergistically to solve more complex problems related to surface science, interfacial studies, and other studies relevant to LM-based systems.
Large area few-layer TMD film growths and their applications
Research on 2D materials is one of the core themes of modern condensed matter physics. Prompted by the experimental isolation of graphene, much attention has been given to the unique optical, electronic, and structural properties of these materials. In the past few years, semiconducting transition metal dichalcogenides (TMDs) have attracted increasing interest due to properties such as direct band gaps and intrinsically broken inversion symmetry. Practical utilization of these properties demands large-area synthesis. While films of graphene have been by now synthesized on the order of square meters, analogous achievements are difficult for TMDs given the complexity of their growth kinetics. This article provides an overview of methods used to synthesize films of mono- and few-layer TMDs, comparing spatial and time scales for the different growth strategies. A special emphasis is placed on the unique applications enabled by such large-scale realization, in fields such as electronics and optics.
Turn of the decade: versatility of 2D hexagonal boron nitride
The era of two-dimensional (2D) materials, in its current form, truly began at the time that graphene was first isolated just over 15 years ago. Shortly thereafter, the use of 2D hexagonal boron nitride (BN) had expanded in popularity, with use of the thin isolator permeating a significant number of fields in condensed matter and beyond. Due to the impractical nature of cataloguing every use or research pursuit, this review will cover ground in the following three subtopics relevant to this versatile material: growth, electrical measurements, and applications in optics and photonics. Through understanding how the material has been utilized, one may anticipate some of the exciting directions made possible by the research conducted up through the turn of this decade.
2.11 - Accurate characterization of indoor photovoltaic performance