Preparation and Machine-Learning Methods of Nacre-like Composites from the Self-Assembly of Magnetic Colloids Exposed to Rotating Magnetic Fields

Guidelines derived from biomineralized tissues for design and construction of high-performance biomimetic materials: from weak to strong

Living organisms in nature have undergone continuous evolution over billions of years, resulting in the formation of high-performance fracture-resistant biomineralized tissues such as bones and teeth to fulfill mechanical and biological functions, despite the fact that most inorganic biominerals that constitute biomineralized tissues are weak and brittle. During the long-period evolution process, nature has evolved a number of highly effective and smart strategies to design chemical compositions and structures of biomineralized tissues to enable superior properties and to adapt to surrounding environments. Most biomineralized tissues have hierarchically ordered structures consisting of very small building blocks on the nanometer scale (nanoparticles, nanofibers or nanoflakes) to reduce the inherent weaknesses and brittleness of corresponding inorganic biominerals, to prevent crack initiation and propagation, and to allow high defect tolerance. The bioinspired principles derived from biomineralized tissues are indispensable for designing and constructing high-performance biomimetic materials. In recent years, a large number of high-performance biomimetic materials have been prepared based on these bioinspired principles with a large volume of literature covering this topic. Therefore, a timely and comprehensive review on this hot topic is highly important and contributes to the future development of this rapidly evolving research field. This review article aims to be comprehensive, authoritative, and critical with wide general interest to the science community, summarizing recent advances in revealing the formation processes, composition, and structures of biomineralized tissues, providing in-depth insights into guidelines derived from biomineralized tissues for the design and construction of high-performance biomimetic materials, and discussing recent progress, current research trends, key problems, future main research directions and challenges, and future perspectives in this exciting and rapidly evolving research field.

Magnetically Guided Synthesis of Anisotropic Porous Carbons toward Efficient CO2 Capture and Magnetic Separation of Oil

Conventional synthetic strategies do not allow one to impart structural anisotropy into porous carbons, thus leading to limited control over their textural properties. While structural anisotropy alters the mechanical properties of materials, it also introduces an additional degree of directionality to increase the pore connectivity and thus the flux in the designed direction. Accordingly, in this work the structure of porous carbons prepared from resorcinol-formaldehyde gels has been rendered anisotropic by integrating superparamagnetic colloids to the sol-gel precursor solution and by applying a uniform magnetic field during the sol-gel transition, which enables the self-assembly of magnetic colloids into chainlike structures to template the growth of the gel phase. Notably, the anisotropic pore structure is maintained upon pyrolysis of the gel, leading to hierarchically porous carbon monoliths with tunable structure and porosities. With an advantage granted to anisotropic materials, these porous carbons showed higher porosity, a higher CO₂ uptake capacity of 3.45 mmol g^-1 at 273 K at 1.1 bar, and faster adsorption kinetics compared to the ones synthesized in the absence of magnetic field. Moreover, these materials were also used as magnetic sorbents with fast adsorption kinetics for efficient oil-spill cleanup and retrieved easily by using an external magnetic field.

Pistachio-Inspired Bulk Graphene Oxide-Based Materials with Shapeability and Recyclability

Nowadays, despite the fact that recent progress has been reported to mimic natural structural materials (especially nacre), designing bioinspired ultrastrong composites in a universal, viable, and scalable manner still remains a long-standing challenge. In particular, pistachio shells show high tissue strength attributed to the cellulose sheet laminated microstructures. Compared with nacre, pistachio shells own interlocking mortise-tenon joints in their structure, which offer higher energy dissipation and deformability. Here we present a strategy to produce nanocomposites with pistachio-mimetic structures through repeated kneading of graphene oxide (GO) in a dynamic covalent and supramolecular poly(sodium thioctic) (pST) system. The dynamic nature of the polymeric backbones endows the resultant GO-based composite with full recyclability and three-dimensional shapeability. The superior mechanical properties of the pistachio-mimetic composite can be attributed to the mortise-tenon joints design in the structure, which has not been achieved in the nacre-mimetic composite. The resulting composite also exhibits high thermal conductivity (15.6 W/(m·K)), yielding an alternative approach to design in engineered and thermal management materials.

Multivariate Threshold Regression Models with Cure Rates: Identification and Estimation in the Presence of the Esscher Property

The first hitting time of a boundary or threshold by the sample path of a stochastic process is the central concept of threshold regression models for survival data analysis. Regression functions for the process and threshold parameters in these models are multivariate combinations of explanatory variates. The stochastic process under investigation may be a univariate stochastic process or a multivariate stochastic process. The stochastic processes of interest to us in this report are those that possess stationary independent increments (i.e., Lévy processes) as well as the Esscher property. The Esscher transform is a transformation of probability density functions that has applications in actuarial science, financial engineering, and other fields. Lévy processes with this property are often encountered in practical applications. Frequently, these applications also involve a ‘cure rate’ fraction because some individuals are susceptible to failure and others not. Cure rates may arise endogenously from the model alone or exogenously from mixing of distinct statistical populations in the data set. We show, using both theoretical analysis and case demonstrations, that model estimates derived from typical survival data may not be able to distinguish between individuals in the cure rate fraction who are not susceptible to failure and those who may be susceptible to failure but escape the fate by chance. The ambiguity is aggravated by right censoring of survival times and by minor misspecifications of the model. Slightly incorrect specifications for regression functions or for the stochastic process can lead to problems with model identification and estimation. In this situation, additional guidance for estimating the fraction of non-susceptibles must come from subject matter expertise or from data types other than survival times, censored or otherwise. The identifiability issue is confronted directly in threshold regression but is also present when applying other kinds of models commonly used for survival data analysis. Other methods, however, usually do not provide a framework for recognizing or dealing with the issue and so the issue is often unintentionally ignored. The theoretical foundations of this work are set out, which presents new and somewhat surprising results for the first hitting time distributions of Lévy processes that have the Esscher property.