Engineered protein-based functional nanopatterned materials for bio-optical devices.

From Responsive Molecules to Interactive Materials.

Polydimethylsiloxane (PDMS)-based flexible films have substantiated advantages in various sensing applications. Here, we demonstrate the highly sensitive and programmable thermal-sensing capability (thermal index, B, up to 126 × 103 K) of flexible films with tunable sandwiched microstructures (PDMS/cracked single-walled carbon nanotube (SWCNT) film/PDMS) when a thermal stimulus is applied. We found that this excellent performance results from the following features of the film's structural and material design: (1) the sandwiched structure allows the film to switch from a three-dimensional to a two-dimensional in-plane deformation and (2) the stiffness of the SWCNT film is decreased by introducing microcracks that make deformation easy and that promote the macroscopic piezoresistive behavior of SWCNT crack islands and the microscopic piezoresistive behavior of SWCNT bundles. The PDMS layer is characterized by a high coefficient of thermal expansion (α = 310 × 10-6 K-1) and low stiffness (∼2 MPa) that allow for greater flexibility and higher temperature sensitivity. We determined the efficacy of our sandwiched, cracked, flexible films in monitoring and switching flexible devices when subjected to various stimuli, including thermal conduction, thermal radiation, and light radiation.

Fast development of portable electronic devices (such as a smart phone, iPad, and Galaxy Note) and electrified vehicles (such as EVs and HEVs) require better and smaller lithium ion batteries as their energy storages. What is needed for the cathode of the lithium ion battery is a material capable of a higher volumetric energy density as well as gravimetric energy density. However, not only the development of cathode material but also the commercialization of high energy density anode material has been limited due to cathode material’s much lower energy density compared to anode material. In this regard, Li-rich material (Li2MnO3-LiMO2, M=Ni, Mn and Co) that has 150 % higher energy density than commercialized LiCoO2 is the unique next generation cathode material to solve the problem of cathode material’s low energy density. In the past decade, many researches have focused on the surface stabilization method of this material to improve its intrinsic problems of poor cycle/ rate capability and such surface treatment methods have been demonstrated in a few examples, including AlF3 coating and spinel heterostructures, yielding noticeable improvements in rate and cycle ability. Although such surface treatments showed improved rate and cycle performances, achieving the high volumetric energy density and long-term cycle life which are more critical factors for the commercialization of Li-rich material still remained unsatisfied. In general, Li-rich material’s reversible capacity is related with its particle size since the Li2MnO3 phase in large Li-rich material, which is a major component to realize high energy density, is not fully activated in low voltage range below 4.6 V. For this reason, many previous papers reported their results with only small primary particle size below 100nm. The high surface area induced by the small particle size increases side reactions with electrolyte resulting poor long-term cycle life as well as lowers the volumetric energy density. Note that Li-rich material’s deteriorations are generated from its surface and continue to affect its cycling capability and the deteriorations can be divided into two mechanisms: one is side reactions with electrolyte, and another is the phase collapse. The side reactions with electrolyte at its high working voltage yield active material attack speiceses such as HF and electrolyte exhaustion causing Li-rich material’s fast discharge capacity decay during cycles. Furthurmore, it is hardly show long-term cycle life with over 200 cycles since the phase transition from layered structure to spinel-like and NiO rock salt is generated on the surface of active material, and followed by expention of this transition into the bulk. For instance, AlF3 coated Li-rich LNCMO has abrupt capacity fade after 100 cycles, although it showed good rate and cycle capability within 100 cycles. Hence, new active material design, rather than simple surface modification methods such as coating or doping, is required to solve above previous limits.The new material design needs to start with a simple question: how to minimize the damages of surface deteriorations such as side reasction with electrolyte and phase trasnsition on bulk material and maximize volumetric energy density. The most effective solution for the question is increasing the primary particle size with the stable activation method, since the volumetric energy density of cathode material is maximized from synthesis of micron secondary particles consisted of primary particles by using co-precipitation method in industry. Here we demonstrate a novel approach for lithium storage, which is a material design of a secondary structure which consists of large flake shaped primary particle (hundred nanometers x mictrometers) with a novel activation method using simple chemical treatment to achieve superior long-term cycle life with high volumetric energy density. In this design, the large primary particle effectively reduced its surface area producing markedly decreased surface instability reaction as well as high tap density. Interstingly, the chemical approach activated only surface Li2MnO3 phase of large primary particle and the very surface activation effectively overcame the activation problem, which is limit of large primary particle have. This novel concept is very meaningful in that it is the first and unique method to achieve cathode material’s high volumetric energy density with long-term cycle life. As a result, this novel designed material affords remarkable battery performance with extremely high cycle retention during 400 cycles and high volumetric energy density ever reported before.

One of the most challenging issues in developing supercapacitor technology is the rational design and synthesis of active electrode materials, at the nanoscale, with favorable morphologies, reasonable porous structure, and excellent conductivity. By transforming a two-dimensional (2D) graphene sheet into a crumpled ball shape, a novel three-dimensional (3D) graphene structure with a large surface area and aggregation-resistant properties has been proposed as an active material in supercapacitors to address the issues associated with the restacking of 2D graphene sheets. To further improve the mass transport/electron transfer and address the issue of limited contact spots between the crumpled graphene balls (CGBs) or between the CGBs and the current collector, we report here a unique hierarchical nanohybrid with porous carbon nanotube (CNT)-networks decorated CGBs (p-CNTn/CGBs), which not only greatly improves the affinity for bridging the active material and the current collector but also maintains favorable features for supercapacitor applications, such as a large surface area, 3D hierarchical nanostructure, excellent electrical conductivity, and outstanding aggregation-resistance. The performance established on the p-CNTn/CGBs far exceeded the bare CGB and reduced graphene oxide (RGO) counterparts in terms of specific capacitance and rate capabilities.

Over the past few decades, molecular machines have been extensively studied, since they are composed of single molecules for functional materials capable of responding to external stimuli, enabling motion at scales ranging from the microscopic to the macroscopic level within molecular aggregates. This advancement holds the potential to efficiently transform external resources into mechanical movement, achieved through precise control of conformational changes in stimuli-responsive materials. However, the underlying mechanism that links microscopic and macroscopic motions remains unclear, demanding computational development associated with simulating the construction of molecular machines from single molecules. This bottleneck has impeded the design of more efficient functional materials. Advancements in theoretical simulations have successfully been developed in various computational models to unveil the operational mechanisms of stimulus-responsive molecular machines, which could help us reduce the costs in experimental trial-and-error procedures. It opens doors to the computer-aided design of innovative functional materials. In this perspective, we have reviewed theoretical approaches employed in simulating dynamic processes involving conformational changes in molecular machines, spanning different scales and environmental conditions. In addition, we have highlighted current challenges and anticipated future trends in the collective control of aggregates within molecular machines. Our goal is to provide a comprehensive overview of recent theoretical advancements in the field of molecular machines, offering valuable insights for the design of novel smart materials.

Nano-patterned polyelectrolyte multilayers assembled using block copolymer templates: The combined effect of ionic strength and nano-confinement

This brief perspective focuses on recent advances in the design of functional soft materials that are based on confinement of low molecular weight liquid crystals (LCs) within micrometer-sized droplets. While the ordering of LCs within micrometer-sized domains has been explored extensively in polymer-dispersed LC materials, recent studies performed with LC domains with precisely defined size and interfacial chemistry have unmasked observations of confinement-induced ordering of LCs that do not follow previously reported theoretical predictions. These new findings, which are enabled in part by advances in the preparation of LCs encapsulated in polymeric shells, are opening up new opportunities for the design of soft responsive materials based on surface-induced ordering transitions. These materials are also providing new insights into the self-assembly of biomolecular and colloidal species at defects formed by LCs confined to micrometer-sized domains. The studies presented in this perspective serve additionally to highlight gaps in knowledge regarding the ordering of LCs in confined systems.

More than 20 000 MOFs have been reported to date, with different combinations of metal ions/centers and organic linkers, and they can be grown into various 3D, 2D, 1D and 0D morphologies. The flexibility in control over varying length scales from atomic scale up to bulk structure allows access to an almost endless variety of MOF-based and MOF-derived materials. Indeed, MOFs themselves have been studied as a class of useful functional materials. More remarkably, extensive research conducted in recent years has shown that MOFs are exceptionally good precursors for a large variety of nanohybrids as active materials in both electrocatalysis and energy storage. As they already contain both carbon and well-dispersed metal atoms, MOFs can be converted to conductive carbons decorated with active metal species and doping elements through appropriate pyrolysis. Due to the great diversity accessible in the composition, structure, and morphology of MOFs, several types of MOF-derived nanohybrids are now among the best performing materials both for electrocatalysts and electrodes in various energy conversion and storage devices. In addition to mesoporous nano-carbons, both doped and undoped, carbon-metal nanohybrids, and carbon-compound nanohybrids, there are several types of core@shell, encapsulated nanostructures, embedded nanosystems and heterostructures that have been developed from MOFs recently. They can be made in either free-standing forms, nano- or micro-powders, grown on appropriate conducting substrates, or assembled together with other active materials. During the MOF to active material conversion, other active species or precursors can be inserted into the MOF-derived nanostructures or assembled on surfaces, leading to uniquely new porous nanostructures. These MOF-derived active materials for electrocatalysis and energy storage are nanohybrids consisting of more than functional components that are purposely integrated together at desired length scales for much-improved performance. This article reviews the current status of these nanohybrids and concludes with a brief perspective on the future of MOF-derived functional materials.

ConspectusLithium-ion batteries (LIBs) are nearly ubiquitous energy storage solutions, powering devices ranging from consumer electronics to electric vehicles. To advance these applications, current LIB research efforts are directed toward improving energy and power densities, cyclic lifetimes, charging speeds, and safety. These parameters are intrinsically tied to properties of the active electrode materials, such as the redox mechanism, chemical composition, and crystal structure. One particularly challenging issue is that the active electrode materials that possess higher theoretical energy densities are generally more susceptible to degradation during cycling. A notable example is the family of layered multicomponent transition metal oxides, which is the incumbent class of active LIB cathode materials for electric vehicles. To increase their theoretical capacities, the transition metal fraction in these materials is trending toward higher Ni content. However, Ni-rich chemistries suffer from electrochemical, crystallographic, and mechanical degradation that increase in severity with increasing Ni content. Furthermore, alternative high-energy cathode materials, including overlithiated layered oxides and disordered rock salt materials, present additional stability challenges that must be overcome before they can be realistically incorporated into LIB technology.The chemomechanical degradation in high-energy LIB cathode materials occurs at multiple length scales. Point defects, such as antisite defects or vacancies, are commonly generated during electrochemical cycling and can contribute to the loss of cyclable active material. At both the primary and secondary particle level, electrochemical cycling also induces significant volumetric changes and state-of-charge heterogeneity, generating regions of high stress and strain that are precursors to mechanical fracture. Finally, at the electrode level, nonuniform charge transfer reactions throughout the electrode can lead to locally overcharged regions that become sites of enhanced degradation. To address these issues, active cathode material design and electrode engineering are being heavily pursued to accelerate improvements in LIB energy density. To consolidate the current understanding of chemomechanical degradation and provide guidance on mitigation strategies, a comprehensive overview of degradation mechanisms across multiple length scales is critically needed.In this Account, we first outline the origins of chemomechanical degradation for high-energy LIB cathodes, including layered oxides, overlithiated layered oxides, and disordered rock salt structures. Specifically, we delineate the thermodynamic and kinetic origins of defect generation at the atomic level and then progress to the kinetic origins of broader degradation mechanisms at the particle level and electrode level. Next, we discuss strategies for minimizing chemomechanical degradation in high-energy LIB cathodes at multiple length scales. Finally, we provide a forward-looking perspective on how to accelerate progress toward practical high-energy LIB cathodes, including emerging methods to map state-of-charge heterogeneity, efficient data processing techniques, and improved strategies for spatially identifying chemomechanical degradation. We also propose engineering solutions for mitigating chemomechanical degradation, such as grain boundary engineering, modifying the active material particle morphology, and electrode architecture design. Since many of these suggestions can be applied irrespective of cathode chemistry, this Account is likely to be broadly applicable to the diverse set of ongoing efforts to realize high-energy LIBs.

Click chemistry has become one of the most innovative methods in modern chemical research, largely due to its unparalleled efficiency, modularity, and ease of use. It enables the rapid synthesis of complex molecules and functional materials under mild conditions, is environmentally friendly, and offers high yields and excellent functional group tolerance. Over the past two decades, click chemistry has evolved from classic copper(I)-catalyzed azido-yne cycloaddition reactions to a range of bioorthogonal, ultrafast, metal-free reactions, as well as strain-induced cycloaddition reactions, tetrazine-based reverse Diels-Alder linkages, and sulfur-fluorine exchange reactions. These advances have enabled precise molecular manipulation in biological systems and supported advanced applications in areas such as real-time imaging, targeted drug delivery, metabolic labeling, and pre-targeted radiochemistry. …Beyond the fields of chemistry and biology, click chemistry is now also fundamental to the work of materials scientists, polymer engineers, and especially nanoparticle experts. Its modular and predictable nature allows for easy transformation into gels, smart materials capable of detecting stimulus-induced shape or functional changes, surface coatings with on-demand integrated electronics, and controllable nanocarriers with diverse structures. Advances in catalyst design optimization, ligand acceleration, and computer technology have not only improved reaction rates but also enhanced stability and biocompatibility. This has enabled the widespread application of this powerful new chemical synthesis tool in industrial and clinical fields. For example, flow chemistry and fluidized bed catalysis have shortened reaction times, significantly increased product yields, and reduced the amount of toxic waste flowing into rivers. Despite the numerous successes of click chemistry, it still faces challenges such as reagent stability, side reactions, cost, and the development of more environmentally friendly and sustainable processes. Machine learning, computer modeling, and reaction design promise to help address these issues in the future. Therefore, researchers can expect the emergence of next-generation click reagents with customizable reactivity, selectivity for planar structures and spatial orientation, and compatibility in complex biological or material environments. This will make click chemistry a versatile, reliable, and powerful method for molecular construction, opening up unprecedented possibilities for the future of synthetic chemistry, biomedical research, and materials design—a truly new era.

Data-driven design shows the promise of accelerating materials discovery but is challenging due to the prohibitive cost of searching the vast design space of chemistry, structure, and synthesis methods. Bayesian Optimization (BO) employs uncertainty-aware machine learning models to select promising designs to evaluate, hence reducing the cost. However, BO with mixed numerical and categorical variables, which is of particular interest in materials design, has not been well studied. In this work, we survey frequentist and Bayesian approaches to uncertainty quantification of machine learning with mixed variables. We then conduct a systematic comparative study of their performances in BO using a popular representative model from each group, the random forest-based Lolo model (frequentist) and the latent variable Gaussian process model (Bayesian). We examine the efficacy of the two models in the optimization of mathematical functions, as well as properties of structural and functional materials, where we observe performance differences as related to problem dimensionality and complexity. By investigating the machine learning models' predictive and uncertainty estimation capabilities, we provide interpretations of the observed performance differences. Our results provide practical guidance on choosing between frequentist and Bayesian uncertainty-aware machine learning models for mixed-variable BO in materials design.

Optical neural networks are considered a promising alternative for mitigating the computational bottlenecks and energy constraints of electronic neural networks. However, their widespread adoption is limited by the absence of efficient optical nonlinear activation units. In this work, we leverage the mature optical component Mach–Zehnder interferometer (MZI) used for constructing optical neural networks and integrate magneto-optical (MO) functional materials into its waveguide arms, achieving a magnetically tunable optical nonlinear activation function. Utilizing finite element simulation software COMSOL Multiphysics, we established a model of the MZI modulator with MO material and optimized the critical structural parameters, such as the radius of the S-bend waveguide, the coupling length of the directional coupler, and the length of the MO waveguide. By adjusting the magnetic field intensity applied to the MO waveguide, the phase difference between the two interfering arms of the MZI can be precisely controlled, thereby enabling the output light intensity to demonstrate the traits of an optical nonlinear activation function. The utilization of MO modulation for achieving optical nonlinear activation function represents a significant advancement over electro-optical and thermo-optical techniques. This method boasts a faster response speed and superior modulation efficiency, coupled with seamless integration and tunability. It holds significant application value in the optical neural networks capable of managing high-speed data processing tasks.

Living organisms and, in general, bio-materials respond to external stimuli exhibiting specific functionalities (such as shape-morphing, color change, tissue growth and remodeling, programmed mechanical responses, adaptation of material properties, etc.) required for different needs (camouflage, locomotion, defense, food supply, biological processes, etc.). Functionalities in nature come from bio-chemo-physical-mechanical responsiveness of the complex architectures in which natural structures are organized across the nano-, micro- and meso-scales. Often inspired by natural structures and bio-functionalities, in recent years the development of synthetic responsive materials has attracted a huge interest, and increasingly still attracts the efforts of scientists to synthesize new smart materials and devices.The paper illustrates the most compelling morphing and functional responses observable in nature – displayed by biological matter, living individuals or by the collective behavior of large groups of organisms – developed for different functional purposes, and discusses the related underlying mechanisms. In parallel, the most relevant functional materials being developed in the last decades are presented with the related mathematical models, and their underlying driving mechanisms are compared with those observable in nature. The study is aimed at providing a broad overview and to explain the strategies used in nature to obtain functionalities; the analogies with those shown by artificial functional materials, with a particular emphasis on polymer-based or polymer-like materials, are investigated. Some multi-physics models, describing the response and enabling the systematic design, optimization and synthesis of functional materials suitable to the development of new advanced applications, are also illustrated. The knowledge of natural cunning can push forward the research in the field, offers new possibilities worth of investigation by materials scientists, physicists and engineers, and opens unexplored scenarios not yet fully considered in the existing literature.

With the deep integration of pharmacy and materials science, functional materials are increasingly applied in drug development, environmental remediation of pharmaceutical pollutants, and clinical diagnosis and treatment. This article focuses on multiple application scenarios of functional materials, including drug degradation, drug adsorption, drug analysis and detection, electrochemical detection, and bioimaging. It systematically reviews the structural characteristics, modification strategies, and latest research progress of typical functional materials such as metal–organic framework materials, nanocomposites and bio-based materials in various application fields. The article also analyzes key challenges faced by functional materials in multi-scenario applications, such as biocompatibility, stability, and large-scale preparation. In light of the trends in precision medicine, it outlines future directions for the application of functional materials in the field of pharmacy, aiming to provide references for the design and development of multifunctional materials and innovative applications in pharmaceuticals.

Chapter 15 - A short account of the role of interfaces in Integrated Circuits manufacturing