The field of quantum materials has experienced rapid growth over the past decade, driven by exciting new discoveries with immense transformative potential. Traditional synthetic methods to quantum materials have, however, limited the exploration of architectural control beyond the atomic scale. By contrast, soft matter self‐assembly can be used to tailor material structure over a large range of length scales, with a vast array of possible form factors, promising emerging quantum material properties at the mesoscale. This review explores opportunities for soft matter science to impact the synthesis of quantum materials with advanced properties. Existing work at the interface of these two fields is highlighted, and perspectives are provided on possible future directions by discussing the potential benefits and challenges which can arise from their bridging.
This content will become publicly available on December 12, 2024
- NSF-PAR ID:
- 10480906
- Author(s) / Creator(s):
- ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; more »
- Publisher / Repository:
- IOP Science
- Date Published:
- Journal Name:
- Journal of Physics: Materials
- Volume:
- 7
- Issue:
- 1
- ISSN:
- 2515-7639
- Page Range / eLocation ID:
- 012501
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
more » « less
Abstract -
Chu, Wilson (Ed.)Two-dimensional materials (e.g., graphene and transition metal dichalcogenides) and their heterostructures have enormous applications in electrochemical energy storage systems such as batteries. A comprehensive and solid understanding of these materials’ thermal transport and mechanism is essential for practical device design. Several advanced experimental techniques have been developed to measure the intrinsic thermal conductivity of materials. However, experiments have challenges in providing improved control and characterization of complex structures, especially for low-dimensional materials. Theoretical and simulation tools, such as first-principles calculations, Boltzmann transport equations, molecular dynamics simulations, lattice dynamics simulation, and nonequilibrium Green’s function, provide reliable predictions of thermal conductivity and physical insights to understand the underlying thermal transport mechanism in materials. However, doing these calculations requires high computational resources. The development of new materials synthesis technology and fast-growing demand for rapid and accurate prediction of physical properties requires novel computational approaches. The machine learning method provides a promising solution to address such needs. This review details the recent development in atomistic/molecular studies and machine learning of thermal transport in two-dimensional materials. The paper also addresses the latest significant experimental advances. However, designing the best two-dimensional materials-based heterostructures is like a multivariate optimization problem. For example, a particular heterostructure may be suitable for thermal transport but can have lower mechanical strength/stability. For bilayer and multilayer structures, the interlayer distance may influence the thermal transport properties and interlayer strength. Therefore, the last part of this review addresses the future research direction in two-dimensional materials-based heterostructure design for thermal transport in energy storage systems.more » « less
-
more » « less
Abstract Since the isolation of graphene and numerous demonstrations of its unique properties, the expectations for this material to be implemented in many future commercial applications have been enormous. However, to date, challenges still remain. One of the key challenges is the fabrication of graphene in a manner that satisfies processing requirements. While transfer of graphene can be used, this tends to damage or contaminate it, which degrades its performance. Hence, there is an important drive to grow graphene directly over a number of technologically important materials, viz., different substrate materials, so as to avoid the need for transfer. One of the more successful approaches to synthesis graphene is chemical vapor deposition (CVD), which is well established. Historically, transition metal substrates are used due to their catalytic properties. However, in recent years this has developed to include many nonmetal substrate systems. Moreover, both solid and molten substrate forms have also been demonstrated. In addition, the current trend to progress flexible devices has spurred interest in graphene growth directly over flexible materials surfaces. All these aspects are presented in this review which presents the developments in available substrates for graphene fabrication by CVD, with a focus primarily on large area graphene.
-
Three-dimensional (3D) printing has expanded beyond the mere patterned deposition of melted solids, moving into areas requiring spatially structured soft matter—typically materials composed of polymers, colloids, surfactants, or living cells. The tunable and dynamically variable rheological properties of soft matter enable the high-resolution manufacture of soft structures. These rheological properties are leveraged in 3D printing techniques that employ sacrificial inks and sacrificial support materials, which go through reversible solid–fluid transitions under modest forces or other small perturbations. Thus, a sacrificial material can be used to shape a second material into a complex 3D structure, and then discarded. Here, we review the sacrificial materials and related methods used to print soft structures. We analyze data from the literature to establish manufacturing principles of soft matter printing, and we explore printing performance within the context of instabilities controlled by the rheology of soft matter materials.more » « less
-
more » « less
Abstract Advancements in electronics and energy storage and conversion technologies brings with it myriads of exciting material design challenges. Charge‐containing block polymers (BPs) offer unique features which can overcome some of these challenges and have thus aroused substantial interest within the field of designer soft materials. The properties of BPs are intricately coupled to the dynamic and rich nature of the nanostructured assemblies, which result from the phase separation between blocks. The introduction of strong secondary forces, such as electrostatics and hydrogen bonding (H‐bonding), into BPs greatly influences their self‐assembly behavior, and therefore affects their physical and electrochemical properties often in nontrivial ways. In this review, some of the prevailing research, which has expanded the understanding of structure–property relationships to include several design strategies for improving ionic conductivity and modulus in charged block polymers, is presented. The profound extent to which electrostatics and hydrogen bonding impact block polymer thermodynamics, an extent which is demonstrated by recent theoretical and experimental work, is also highlight. Insights gained from the research presented here help to lay the groundwork for a long and bright future in the field of advanced soft materials.
