Mrs Bulletin最新文献

The phase-field method enables simulating the spatiotemporal evolution of the coupled physical-order parameters under externally applied fields in a wide range of materials and devices. Leveraging advanced numerical algorithms for solving the nonlinear partial differential equations and scalable parallelization techniques, the phase-field method is becoming a powerful computational tool to model and design devices operating based on multiple-coupled physical processes. This article will highlight examples of applying phase-field simulations to predict new mesoscale physical phenomena and design new-concept magnetomechanical devices by identifying the desirable combination of the composition, size, and geometry of monolithic materials as well as the device structure. A brief outlook of the opportunities and challenges for modeling and designing magnetomechanical devices with phase-field modeling is also provided.

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Fuel cells are highly efficient electrochemical energy-conversion devices with a wide application potential, spanning from portable power sources to stationary power generation. They are typically categorized according to their operating temperature, for example, low temperature (<100°C), intermediate temperature (450‒800°C) and high temperature (>800°C). Recently, reduced temperature fuel cells operating at 200‒400°C have also received considerable attention for their multiple benefits. A single fuel cell is composed of a porous anode for fuel oxidation, a dense electrolyte for ion transportation, and a porous cathode for oxygen reduction. Due to their different functions and operating environments, each layer of the cell faces unique materials requirements in terms of ionic and electronic conductivity, chemical and mechanical stability, thermal expansion, etc. This article gives a thorough perspective on the challenges and recent advances in anode, electrolyte, and cathode materials for the various types of fuel cells. Emerging fuel cells operating at 200‒400°C are also discussed and commented. Finally, the key areas of need and major opportunities for further research in the field are outlined.

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Emulsions are omnipresent in our everyday life; for example, in food, certain drug and cosmetic formulations, agriculture, and as paints. Moreover, they are frequently used to perform high-throughput screening assays with minimum sample volumes. Key to the successful use of emulsions is a good drop stability. Most frequently, drops are stabilized with surfactants composed of hydrophilic and hydrophobic parts. Appropriate surfactants are often selected based on the ratio of their hydrophilic to the hydrophobic parts, their hydrophilic–lipophilic balance (HLB), which determines their solubility. However, how the HLB value of perfluorinated surfactants influences the emulsion stability remains to be determined. To address this question, we report a benign and cost-effective synthesis of diblock-copolymer surfactants that consist of a perfluorinated block covalently linked to a hydrophilic poly(ethylene glycol) (PEG)-encompassing block. The compositions of the fluorophilic and hydrophilic blocks are very similar to those of commercially available triblock-copolymer surfactants commonly used within the microfluidic community that employs poly(dimethylsiloxane) (PDMS)-based devices. By deliberately tuning the ratio of the hydrophobic to the hydrophilic blocks of our diblock-copolymer surfactants, we obtain HLB values varying between 0.9 and 3.3. We demonstrate that the best emulsion stability is obtained if the molecular weight ratio of the hydrophobic to the hydrophilic blocks is between 5 and 7, corresponding to HLB values between 2.5 and 3.3. Importantly, our cost-effective surfactant displays a similar performance to that of the rather costly commercially available Pico-Surf surfactant. Thereby, this study presents guidelines for a cheap, benign, and targeted synthesis of appropriate perfluorinated surfactants that efficiently stabilize water-in-perfluorinated oil emulsions.

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Abstract

We report atomistic mechanisms that directly correlate the time-dependent optical responses of bulk Ge₂₃Sb₇S₇₀ chalcogenide glasses to their metastable structural defects created and subsequently annihilated following gamma irradiation. These defects are characterized by an irradiation-induced increase in the concentration of edge-shared GeS_4/2 tetrahedra bonding units, which gradually decreases to a pre-irradiation level during recovery, thus illustrating the glass’ metastable behavior. This time-dependent structural change gives rise to the evolution of the glass’s mass density that correspondingly induces a change and subsequent relaxation of linear refractive index and bandgap energy. Concurrent with this evolution in linear optical properties, the glass’ nonlinear response is found to be unaffected, likely due to a counter effect associated with the glass network’s free electrons.

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Impact statement

Our work is the first study to employ a combined theoretical-experimental approach to the quantitative processing–structure–property relationship correlating the time-dependent structural and linear/nonlinear optical responses of chalcogenide Ge–Sb–S bulk glasses to their metastable topological coordination defects. These defects are created upon gamma-ray exposure and subsequently undergo relaxation at room temperature. The novelty of our study is that multifaceted aspects of such a key infrared chalcogenide glass, including optical, electronic, morphological, chemical, and microstructural properties, were monitored and cross-correlated as a function of time following gamma irradiation in order to identify origins behind the material system’s behavior as compared to base unirradiated material. This is, to our knowledge, the first-ever integrated approach (summarizing pre- and postexposure properties on the same samples) to the phenomenon. The behavior in metastable bulk chalcogenide glasses serves as a key cornerstone that will enable the material system to be deployed as robust, reversible radiation sensors in extreme environments such as space and ground-based radioactive facilities where gamma ray is characteristically abundant. Findings in our paper may shed light on the lingering question on the microscopic origin behind the self-healing process in chalcogenide glasses.

The world of biology created a wealth of complex materials intertwining order, disorder, and hierarchy. They are produced with minimal energy expenditures and display combinations of properties that surpass materials aimed to be perfectly ordered crystals or perfectly disordered glasses. De novo engineering of biomimetic materials with “impossible” combination of properties necessary for multiple technologies becomes possible considering complexity as a design parameter but this methodology lacks foundational principles. This article delineates the concept of complexity in the context of materials science. It examines the pathway to quantitative complexity–functionality relations and explores pragmatic approaches to scalable complex materials guided by discrete mathematics of nanoassemblies from imperfect components.

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Thanks to decades of tireless efforts, nanoparticle assemblies have reached an extremely high level of controllability, sophistication, and complexity, with new insights provided by integration with graph theory, cutting-edge characterization, and machine learning (ML)-based computation and modeling, as well as with ever-diversifying applications in energy, catalysis, biomedicine, optics, electronics, magnetics, organic biosynthesis, and quantum technology. Nanoparticle assemblies can be crystalline, known as superlattices or supracrystals. Their assembly entails a transition from disorder—dispersed nanoparticles—to order, which can be achieved through classical nucleation pathways or nonclassical pathways via prenucleation precursors or particle aggregation. The periodic lattices allow facile manipulations of electrons, phonons, photons, and even spins, leading to advanced device components and metamaterials. Meanwhile, aperiodic assemblies out of nanoparticles, such as gels, networks, and amorphous solids, also start to attract attention. Despite the loss of periodicity, symmetry-lowering or symmetry-breaking three-dimensional (3D) structures emerge with unique properties, such as chiroptical activity, topological mechanical strength, and quantum entanglement. Real-space imaging such as electron microscopy and x-ray-based tomography methods are utilized to characterize these complex structures, whereas mathematical tools such as graph theories are in need to describe such complex structures. This issue aims to provide a timely review of the efforts in this greatly broadened materials design space, including experiment, simulation, theory, and applications. Nine top experts (and their teams) from four countries deliver six articles summarizing fundamental mechanistic understandings of nanoparticle assemblies, highlighted with the developments of state-of-the-art in situ characterization tools and ML-assisted reverse engineering, and newly emergent applications of nanoarchitectures.

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Over the last several decades, colloidal nanoparticles have evolved into a prominent class of building blocks for materials design. Important advances include the synthesis of uniform nanoparticles with tailored compositions and properties, and the precision construction of intricate, higher-level structures from nanoparticles via self-assembly. Grasping the modern complexity of nanoparticles and their superstructures requires fundamental understandings of the processes of nanoparticle growth and self-assembly. In situ liquid phase transmission electron microscopy (TEM) has significantly advanced our understanding of these dynamic processes by allowing direct observation of how individual atoms and nanoparticles interact in real time, in their native phases. In this article, we highlight diverse nucleation and growth pathways of nanoparticles in solution that could be elucidated by the in situ liquid phase TEM. Furthermore, we showcase in situ liquid phase TEM studies of nanoparticle self-assembly pathways, highlighting the complex interplay among nanoparticles, ligands, and solvents. The mechanistic insights gained from in situ liquid phase TEM investigation could inform the design and synthesis of novel nanomaterials for various applications such as catalysis, energy conversion, and optoelectronic devices.

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