Class Of Materials Research Articles

Regioselective Copolymerization of Glucose-Derived Allopyranoside Epoxide with Cyclic Anhydrides: Developing Precise Sugar-Functionalized Polyesters with Unique Altrose Linkages.

Uniform sugar-functionalized polyesters combine the benefits of sugar's structural diversity, biocompatibility, and biodegradability with precise postfunctionalization capabilities, making them a highly valuable class of materials with extensive application potential. However, the irregular placement of hydroxyl groups has limited the synthesis of these polyesters. Here, we present the first platform for uniform sugar-functionalized polyesters via regioselective ring-opening copolymerizations (ROCOPs) of allopyranoside anhydrosugar epoxide (1, derived from d-glucose) with cyclic anhydrides, followed by complete selective deprotection. This method yields polyesters with controlled molecular weights, narrow molecular weight distributions (D̵ < 1.19), high glass transition temperatures (up to 188 °C), and uniform hydroxyl functionality. Furthermore, the degradation of the polyesters offers an efficient route for producing the highly valuable d-altrose. Mechanistic insights, supported by DFT calculations, as well as NMR and HPLC analyses, confirm the regioselective nucleophilic attack at the C2 position of the pyranose ring. Kinetic studies reveal a first-order dependence on 1 and a zero-order dependence on the cyclic anhydrides. Additionally, these uniform sugar-functionalized polyesters can be incorporated into triblock terpolymers through one-pot/one-step or one-pot/two-step procedures, forming uniform sugar-functionalized multiblock copolymers.

Advances in Magnetic Nanomaterials and Nanostructures

Magnetic nanomaterials, in which non-bulk magnetic properties emerge because of their low dimension, are a class of materials with huge application potential in several areas, providing, at the same time, an exciting field of fundamental research [...]

Molecular-scale kinetic Monte Carlo simulation of pattern formation in photoresist materials for EUV nanolithography

A kinetic Monte Carlo (KMC) simulation tool for modeling the pattern formation process in photoresist materials for extreme ultraviolet (photon energy 92 eV) nanolithography is presented. The availability of such a tool should support the progress toward novel materials and experimental procedures that lead to an improved pattern resolution. The molecular-scale simulations describe the process in a stochastic and mechanistic manner and include the excitation of high-energy electrons upon light absorption, the creation of a charged-particle cloud, electron-induced chemical degradation of the photoresist molecules, the resulting bond formation between neighboring degraded molecules, and a chemical development step after which a pattern of the remaining non-dissolved molecules is obtained. The method is applied to the application-relevant class of Sn-oxocore photoresist materials and uses their known electronic structure and optical electron energy loss function. The validity of the approach is tested by comparing measured and simulated total electron yield spectra and photoelectron spectra. A demonstration of the method is given by calculating the dose and pitch dependent average shape and stochastic variability (line edge roughness) of line patterns that are obtained for rectangular and sine-wave illumination, assuming various scenarios that determine how molecular-scale degradation will lead to bond creation. We show how from these simulations the ultimate pattern resolution can be deduced. The findings are analyzed systematically using results of KMC simulations that reveal the size of the cloud of degraded molecules around a point of absorption (blur length) and that further reveal the sensitivity to uniform illumination (contrast curves), and using percolation theory. We find that KMC modeling captures the consequences of the strong gradients in the density of degraded molecules and of the stochasticity of the patterning process that simplified models do not include, leading to a significantly improved view of the final pattern quality.

(RPh3P)[Mn(dca)3]: A Family of Glass-Forming Hybrid Organic-Inorganic Materials.

ABX3-type hybrid organic-inorganic structures have recently emerged as a new class of meltable materials. Here, by the use of phenylphosphonium derivatives as A cation, we study liquid- and glass-forming behavior of a new family of hybrid structures, (RPh3P)[Mn(dca)3] (R = Me, Et, Ph; dca = dicyanamide). These new compounds melt at 196-237 °C (Tm) and then vitrify upon cooling to room temperature, forming glasses. In situ glass formation of this new family of materials was probed on a large scale using a variable-temperature PXRD experiment. Structure analyses of the crystalline and the glasses were carried out by solid-state nuclear magnetic resonance spectroscopy and synchrotron X-ray total scattering techniques for using the pair distribution function. The mechanical properties of the glasses produced were evaluated showing promising durability. Thermal and electrical conductivities showed low thermal conductivities (κ ∼ 0.07-0.09 W m-1 K-1) and moderate electrical conductivities (σ ∼ 10-4-10-6 S m-1) at room temperature, suggesting that by the precise control of the A cation, we can tune meltable hybrid structures from moderate conductors to efficient thermal insulators. Our results raise attention on the practical use of this new hybrid material in applications including, e.g., photovoltaic devices to prevent light-deposited heat (owing to low κRT), energy harvesting thermoelectric, etc., and advance the structure-property understanding.

Water Electrooxidation Kinetics Clarified by Time‐Resolved X‐Ray Absorption and Electrochemical Impedance Spectroscopy for a Bulk‐Active Cobalt Material

AbstractWater oxidation, the oxygen evolution reaction (OER), is the anodic process in electrocatalytic production of hydrogen and further green fuels. Transition‐metal oxyhydroxides with bulk‐phase OER activity of the complete material or amorphized near‐surface regions are of prime application interest, but their basic electrochemical properties are insufficiently understood. Here the timescale of functional processes is clarified by time‐resolved X‐ray absorption spectroscopy and electrochemical impedance spectroscopy (EIS) for a thickness‐series of cobalt oxyhydroxides films (about 35–550 nm). At the outer material surface, an electric double‐layer is formed in microseconds followed by clearly cobalt‐centered redox‐state changes of the bulk material in the low millisecond domain and a slow chemical step of O2‐formation, within hundreds of milliseconds. Conceptually interesting, the electrode potential likely controls the OER rate indirectly by driving the catalyst material to an increasingly oxidized state which promotes the rate‐limiting chemical step. Rate constants are derived for redox chemistry and catalysis from EIS data of low‐thickness catalyst films; at higher thicknesses, catalyst‐internal charge transport limitations become increasingly relevant. Relations between electrochemically active surface area, double‐layer capacitance, and redox (pseudo‐)capacitance are discussed. These results can increase the power of EIS analyses and support knowledge‐guided optimization of a broader class of OER catalyst materials.

Wear Study on Various Conditions of AA7075 Metal Matrix Composite with Silicon Carbide (SiC), Boron Carbide (B4C) as Reinforcement for Aerospace Applications

This study aims to investigate the wear behavior of AA7075 alloy with the reinforcement of Silicon carbide (SiC) and Boron carbide (B4C) particles. Process parameters are crucial for component quality improvement, particularly in metal matrix composites (MMCs), a unique class of materials used in a variety of technical applications, such as but not limited to automobiles, marine, and aeronautics.These are frequently utilized in challenging applications due to their significantly better strength to weight ratios, stiffness, and then standard materials. However, it has numerous disadvantages, including high weight ratios, high deformation and stresses, poor fatigue life cycle, early wear and friction, and so on. Up till now, numerous reinforcements have been employed to address these crucial problems. Due to its superior properties, aluminum matrix composites (AMCs) have been used in many different applications. This work attempts to examine the wear behavior of AA7075 alloy reinforced with silicon (SiC) and boron (B4C) particles utilizing the stir casting process AA 7075-(SiC)-(B4C) composites were produced by employing AA 7075 as the matrix material with silicon carbide (SiC) and boron carbide (B4C) particles as reinforcement in various percentages of weight (5%, 10%, and 15%). Parameters of the composites, including wear behavior, coefficient of friction, frictional force, and pin temperature were assessed through graphical representation.

Optimization of selective powder deposition for multi-material powder bed fusion: process innovations and applications

AbstractAdditive manufacturing processes based on powder bed fusion offer a high degree of design flexibility and enable the processing of a wide range of materials, including metals, ceramics, and polymers, while maintaining minimal porosity. However, production of multi-material components with locally tailored properties to meet specific requirements by incorporating different materials with a high degree of spatial selectivity remains an elusive challenge. Essential prerequisites for achieving this selectivity are specialized selective powder deposition techniques, their development, characterization, and subsequent implementation. In order to investigate optimization potentials and to identify research gaps in the field of selective powder deposition techniques, an evaluation of the current literature is performed in this study, ultimately highlighting promising potentials for vibration-assisted approaches. Key considerations include the reduction of implementation complexity and the downscaling of associated devices to increase their applicability. To achieve implementation simplification, this study derives dimensionless quantities that facilitate a targeted calculation of control parameters by associating powder layer quality metrics with relevant input quantities. The validity of the derived dimensionless quantities is verified by discrete-element method simulations and physical experiments employing a novel miniaturized vibration-assisted device. Metal, ceramic and polymer powders are used as representative samples to demonstrate the versatility of the method for different classes of materials. Ultimately, the presented methods enable a significant improvement in the applicability of vibration-assisted devices and represent an integrative component that provides a suitable basis for further research efforts in the field of combined processing of multiple materials by additive manufacturing technologies that utilize powder beds.

Lung dECM matrikine-based hydrogel reverses bleomycin-induced pulmonary fibrosis by suppressing M2 macrophage polarization.

Recent studies have shown promising results using decellularized extracellular matrix (dECM) matrikines-based hydrogel as attractive strategies for preventing and alleviating fibrosis.&#xD;Methods & Results: Porcine lung decellularization and pepsin digestion were used to prepare the lung dECM hydrogel. Proteomic analysis revealed that the lung dECM hydrogel was enriched in glycoproteins, collagens, laminins, fibrinogen, held receptors, and bound growth factors. With porous structures and good mechanical properties and stability, the lung dECM hydrogel showed low cytotoxicity and good biocompatibility both in vitro and in vivo. The lung dECM hydrogel was further administered to verify the safety and effectiveness of reversing pulmonary fibrosis in a bleomycin induced rat model. The results revealed a relatively complete alveolar structure with less inflammatory infiltration and a reduced amount of collagen fiber deposition. TMT quantification proteomic analyses revealed significant downregulation of proteins, pathways, and interactions involved in the regulation of ECM components, tissue remodeling, inflammation, and the cytoskeleton and indicated that fibrosis-related proteins were obviously downregulated and inflammation-related proteins were significantly changed, particularly in macrophages, after administration of the lung dECM hydrogel. Multiplex immunohistochemical (mIHC) staining of lung tissue revealed that the inflammatory response was regulated by the lung dECM hydrogel, as indicated by a decrease in the number of CD3+ T cells and macrophages and the suppression of M2 macrophage polarization. Gene set enrichment analysis revealed that downregulated ficolin signaling was enriched in macrophages after lung dECM hydrogel administration, and the findings were verified in lung tissue by mIHC. Additionally, the effects of ficolin B proteins on macrophage polarization were proved in vitro.&#xD;Conclusion: This study suggested that the lung dECM hydrogel can reverse pulmonary fibrosis by suppressing M2 macrophage polarization through downregulation of the ficolin signaling pathway. Thus, the dECM hydrogel represent a promising class of biological materials for use in regenerative medicine.

Liquid Structure of Magnesium Aluminates

Magnesium aluminates (MgO)x(Al2O3)1−x belong to a class of refractory materials with important applications in glass and glass–ceramic technologies. Typically, these materials are fabricated from high-temperature molten phases. However, due to the difficulties in making measurements at very high temperatures, information on liquid-state structure and properties is limited. In this work, we employed the method of aerodynamic levitation with CO2 laser heating at large scale facilities to study the structure of liquid magnesium aluminates in the system (MgO)x(Al2O3)1−x, with x = 0.33, 0.5, and 0.75, using X-ray and neutron diffraction. We determined the structure factors and corresponding pair distribution functions, providing detailed information on the short-range structural order in the liquid state. The local structures were similar across the range of compositions studied, with average coordination numbers of n¯AlO∼4.5 and n¯MgO∼5.1 and interatomic distances of rAlO=1.76−1.78 Å and rMgO=1.93−1.95 Å. The results are in good agreement with previous molecular dynamics simulations. For the spinel endmember MgAl2O4 (x = 0.5), the average Mg-O and Al-O coordination numbers gave rise to conflicting values for the inversion coefficient χ, indicating that the structural formula used to describe the solid-state order-disorder transition is not applicable in the liquid state.

Does pre-existing differential pressure have an impact on poroelastic compressibilities?

The existing formulation of quasistatic poroelasticity for saturated porous materials relies on the assumption that differential pressure, defined to be the difference between the confining and liquid pressures, is zero at the reference state. This as- sumption can be problematic in problems involving swelling media, such as clay, and deep underground where pre-existing pore pressure may differ from the total pressure. Here, the quasistatic poroelastic equations are derived from only the conservation of mass for each phase and the Terzaghi effective stress principle for the case when there is a nonzero reference differential pressure. In the process, a dynamic equation for the porosity is derived, and one additional parameter representing a dimensionless reference differential pressure is introduced. Although the form of the quasistatic poroelastic equations remains the same, the poroelastic compressibilities change with the reference state’s nonzero differential pressure. The changes to these compressibil- ities are systematically outlined, and the impact on more specific classes of material are examined. The altered compressibilities imply, among other changes, that the compressional velocity is a function of the pre-existing differential pressure, which is useful to account for in dynamic measurements, but that the dependence is weak for materials with low compressibilities.

Multiphoton Excited Fluorescence Imaging over Metal-Organic Frameworks.

Multiphoton excited fluorescence (MPEF) imaging has emerged as a powerful tool for visualizing biological processes with high spatial and temporal resolution. Metal-organic frameworks (MOFs), a class of porous materials composed of metal ions or clusters coordinated with organic ligands, have recently gained attention for their unique optical properties and potential applications in MPEF imaging. This review provides a comprehensive overview of the design, synthesis, and applications of multiphoton excited fluorescence imaging using MOFs. We discuss the principles behind the fluorescence behavior of MOFs, explore strategies to enhance their photophysical properties, and showcase their applications in bioimaging. Additionally, we address the current challenges and future prospects in this rapidly evolving field, highlighting the potential of multiphoton excited fluorescence imaging by MOFs for advancing our understanding of complex biological processes.

Machine learning-based constitutive modelling for material non-linearity: A review

Machine learning (ML) models are widely used across numerous scientific and engineering disciplines due to their exceptional performance, flexibility, prediction quality, and ability to handle highly complex problems if appropriate data are available. One example of such areas which has attracted a lot of attentions in the last couple of years is the integration of data-driven approaches in material modeling. There has been several successful researches in implementing ML-based constitutive models instead of classical phenomenological models for various materials, particularly those with non-linear mechanical behaviors. This review paper aims to systematically investigate the literature on ML-based constitutive models for materials and classify these models based on their suitability for material non-linearity including Non-linear elasticity (hyperelasticity), plasticity, visco-elasticity, and visco-plasticity. Furthermore, we also reviewed and compared the ML-based approaches that have been applied for architectured materials as these groups of materials are designed to represent specific material behaviors that might not exist in classical and conventional material categories. The other goal of this review paper is to provide initial steps in understanding of various ML-based approaches for material modeling, including artificial neural networks (ANN), Gaussian processes, random forests (RF), generated adversarial networks (GANs), support vector machines (SVM), different regression models and physics-informed neural networks (PINN). This paper also outlines different data collection methods, types of data, data processing approaches, the theoretical background of the ML models, advantage and limitations of various models, and potential future research directions. This comprehensive review will provide researchers with the knowledge necessary to develop high-fidelity, robust, adaptable, flexible, and accurate data-driven constitutive models for advanced materials.

MXenes in Perovskite Solar Cells: Emerging Applications and Performance Enhancements

Perovskite solar cells (PSCs) have emerged as promising candidates for next-generation photovoltaic technology due to their remarkable power-conversion efficiencies (PCEs). Since their introduction, the PCE of PSCs has advanced from 3.8% to over 26%. Nonetheless, challenges pertaining to stability and reliability continue to impede their commercial viability. Recent progress in interface engineering and materials science has underscored the potential of two-dimensional (2D) materials, particularly MXenes, in mitigating these challenges. MXenes represent a class of two-dimensional materials with significant potential for application in PSCs, attributed to their exceptional electrical conductivity, high carrier mobility, remarkable optical transparency, chemical stability, and tunable surface chemical properties. When employed as electron transport layers, MXenes enhance charge transfer and extraction efficiency, leading to substantial improvements in PCEs. Furthermore, their integration into hole transport layers and use as interfacial modifiers contribute to the mitigation of degradation pathways, thereby enhancing device longevity. The unique structural and electronic characteristics of MXenes facilitate their application as transparent electrodes, presenting opportunities for cost reduction and improved optical properties. This review provides a comprehensive overview of the current advancements in MXene-based PSCs, emphasizing significant accomplishments and exploring future research directions aimed at enhancing the efficiency and stability of these devices.

Voltage Mining for (De)lithiation-Stabilized Cathodes and a Machine Learning Model for Li-Ion Cathode Voltage.

Advances in lithium-metal anodes have inspired interest in discovery of Li-free cathodes, most of which are natively found in their charged state. This is in contrast to today's commercial lithium-ion battery cathodes, which are more stable in their discharged state. In this study, we combine calculated cathode voltage information from both categories of cathode materials, covering 5577 and 2423 total unique structure pairs, respectively. The resulting voltage distributions with respect to the redox pairs and anion types for both classes of compounds emphasize design principles for high-voltage cathodes, which favor later Period 4 transition metals in their higher oxidation states and more electronegative anions like fluorine or polyanion groups. Generally, cathodes that are found in their charged, delithiated state are shown to exhibit voltages lower than those that are most stable in their lithiated state, in agreement with thermodynamic expectations. Deviations from this trend are found to originate from different anion distributions between redox pairs. In addition, a machine learning model for voltage prediction based on chemical formulas is trained and shows state-of-the-art performance when compared to two established composition-based ML models for material properties predictions, Roost and CrabNet.

On-surface synthesis of phthalocyanines with extended π-electron systems

Expanded phthalocyanines are a promising class of materials for optoelectronic applications, owing to their unique properties and versatile metal coordination reactivity. The expansion of their π-electron systems and resulting red-shifted absorption are of particular interest for achieving broader applications. Here, we report the on-surface synthesis of metallo-phthalocyanines with extended electron systems and an open-chain polycyanine from ortho-dicarbonitrile precursors on Ag(111) and Au(111), studied by scanning tunneling microscopy (STM) and X-ray photoelectron spectroscopy (XPS). The larger 6,7-di(2-naphthyl)-2,3-naphthalenedicarbonitrile (NND) undergoes spontaneous cyclotetramerization on the Ag(111) surface forming the corresponding silver naphthalocyanines (Ag-NPc), contrasting previous reports where a partially aliphatic ortho-dicarbonitrile precursor formed polycyanine chains. In contrast, monolayers of the smaller 6,7-diphenyl-2,3-naphthalenedicarbonitrile (PND) form the corresponding naphthalocyanine only in the presence of co-adsorbed iron atoms (Fe-NPc). In the absence of iron, PND multilayers form polycyanine chains and Ag-NPc. NND and PND further differ in their reactivity due to the supramolecular behavior of their products. While the larger Ag-NPc aggregates to non-covalent one-dimensional ribbons, the smaller Fe-NPc forms an extended non-covalent two-dimensional network. Our study demonstrates the versatility of on-surface dinitrile tetramerization for the synthesis of π-extended cyclic phthalocyanines and their open-chain polycyanine counterparts.

Eco Breakthroughs: Sustainable Materials Transforming the Future of Our Planet

Interest in the sustainable materials sector is growing and accelerated. These materials are designed to reduce the use of non-renewable resources, limit greenhouse gas emissions, and be recyclable or biodegradable, making them highly attractive to both academia and industry. Constantly updating on innovations in this field is essential to speed up the transition to a circular economy and significantly reduce environmental impact. The paper analyzes the current status and future trends of the scientific literature for seven sustainability-related materials categories, such as sustainable materials, green materials, biomaterials, eco-friendly materials, alternative materials, material recycling and material recovery from complex products, and sustainable applied materials. Next, it assesses the impacts, benefits, and challenges associated with sustainable materials from the scientific literature according to six research fields (impact on the environment, performance and durability, economic efficiency, health and safety, social sustainability, and implementation and use). Furthermore, the paper outlines recent advances in sustainable material design, including biomimicry, nanotechnology, additive manufacturing, 3D printing, and sustainable composite materials. Additionally, a bibliometric analysis of 545 studies on sustainable materials published between 1999 and 2023 was conducted based on eight criteria, namely trend, source, author, country, keywords, thematic, co-citation, and content. The findings show that the sustainability-related materials categories have a particular distribution among the domains. Also, the thematic map analysis outlines that biopolymers, nanocellulose, and biocomposites are critical research areas for developing sustainable materials.

Monolayer Magnetic Metal with Scalable Conductivity.

2D magnets have emerged as a class of materials highly promising for studies of quantum phenomena and applications in ultra-compact spintronics. Current research aims at design of 2D magnets with particular functional properties. A formidable challenge is to produce metallic monolayers: the material landscape of layered magnetic systems is strongly dominated by insulators; rare metallic magnets, such as Fe3GeTe2, become insulating as they approach the monolayer limit. Here, electron transport measurements demonstrate that the recently discovered 2D magnet GdAlSi - graphene-like AlSi layers coupled to layers of Gd atoms - remains metallic down to a single monolayer. Band structure analysis indicates the material to be an electride, which may stabilize the metallic state. Remarkably, the sheet conductance of 2D GdAlSi is proportional to the number of monolayers - a manifestation of scalable conductivity. The GdAlSi layers are epitaxially integrated with silicon, facilitating applications in electronics.

Application Of Problem Based Learning Model In Civics Learning On Central Government Structure Material In Grade IV Of Pabelan Kartasura State Elementary School

This research is entitled "Application of the Problem Based Learning Model in Civics Learning on Central Government Structure Material Class IV Sdn Pabelan Kartasura" This research aims to analyze the application of the Problem Based Learning (PBL) learning model in Civics Education (PKn) learning on Central Government Structure material in class IV SDN Pabelan, Kartasura. This research is motivated by the need to increase students' active participation and in-depth understanding of abstract material. The PBL model also encourages students to be more active in discussing, working together, and solving problems independently or in groups. The research results show that the application of the PBL model can increase student involvement in the learning process, critical thinking skills, and student learning outcomes. The research methods used are direct observation in class, interviews with teachers, and documentation. The observation results show that Civics learning in class IV at SDN Pabelan 03 has been implemented in accordance with the learning plan prepared. Teachers use lecture, question and answer and group discussion methods to improve students' understanding of the material. Learning evaluation is carried out through written tests and student attitude assessments. Obstacles found included limited time and lack of student involvement in several discussion activities. The conclusion from this observation is that Civics learning at SDN Pabelan 03 has gone well, but innovation is needed in learning methods and media to improve the quality of learning.

Inverse Size-Scaling Ferroelectricity in Centrosymmetric Insulating Perovskite Oxide DyScO3.

The breaking of inversion symmetry dictates the emergence of electric polarization, whose topological states in superlattices and bulks have received tremendous attention for their intriguing physics brought for novel device design. However, as for substrate oxides such as LaAlO3, KTaO3, RScO3 (R = rare earth element), their centrosymmetric trivial attributes make their functionality poorly explored. Here, the discovery of nanoscale thickness gradient-induced nonpolar-to-polar phase transition in band insulator DyScO3 is reported by using atomic resolution transmission electron microscopy. As the free-standing specimen reduces to a critical thickness ≈5 nm, its inversion symmetry is spontaneously broken by surface charge transfer, which gives rise to asymmetric Dy atomic displacements and ferrodistortive octahedral order, as substantiated by the first-principles calculations. Apart from the observation of migratable polar vortex structures, the switchable electric polarization by applied electric field is demonstrated by the piezoresponse force microscopy experiments. Given the decisive role of critical size in generating ferroelectricity, a concept of "inverse size-scaling ferroelectric" is proposed to define a class of such materials. Distinct from the proper and improper ferroelectrics, the findings offer a new platform to explore novel low-dimensional ferroelectrics and device applications in the future.

Anisotropic Thermal Transport in Tunable Self-Assembled Nanocrystal Supercrystals.

Realizing tunable functional materials with built-in nanoscale heat flow directionality represents a significant challenge that could advance thermal management strategies. Here we use spatiotemporally resolved thermoreflectance to visualize lateral thermal transport anisotropy in self-assembled supercrystals of anisotropic Au nanocrystals. Correlative electron and thermoreflectance microscopy reveal that nano- to mesoscale heat predominantly flows along the long-axis of the anisotropic nanocrystals, and does so across grain boundaries and curved assemblies while voids disrupt heat flow. We finely control the anisotropy via the aspect ratio of constituent nanorods, and it exceeds the aspect ratio for nanobipyramid supercrystals and certain nanorod arrangements. Finite element simulations and effective medium modeling rationalize the emergent anisotropic behavior in terms of a simple series resistance model, further providing a framework for estimating thermal anisotropy as a function of material and structural parameters. Self-assembly of colloidal nanocrystals promises an interesting route to direct heat flow in a wide range of applications that utilize this important class of materials.