The directional design of functional materials with multi-objective constraints is a big challenge, in which performance and stability are determined by a complicated interconnection of different physical factors. We apply multi-objective optimization, based on the Pareto Efficiency and Particle-Swarm Optimization methods, to design new functional materials directionally. As a demonstration, we achieve the thermoelectric design of 2D SnSe materials via the above methods. We identify several novel metastable 2D SnSe structures with simultaneously lower free energy and better thermoelectric performance in their experimentally reported monolayer structures. We hope that the results of our work on the multi-objective Pareto Optimization method will represent a step forward in the integrative design of future multi-objective and multi-functional materials.

Aberrant expression of the chemokine CXC receptor 4 (CXCR4) is closely associated with cancer progression and drug-resistance in multiple cancers, and we first investigated the role of CXCR4 in regulating cancer pathogenesis and cisplatin (DDP)-resistance in clear cell renal cell carcinoma (ccRCC) in the present study. Here, we identified that CXCR4 acted as an oncogene to promote cancer progression and genetically silencing of CXCR4 increased cisplatin (DDP)-sensitivity in ccRCC in vitro and in vivo. Functionally, analysis from the clinical and cellular data indicated that CXCR4 was significantly upregulated in ccRCC tissues and cells, compared to their normal counterparts. Next, the loss-of-function experiments validated that knock-down of CXCR4 suppressed cell proliferation, invasion, migration and epithelial-mesenchymal transition (EMT) in ccRCC cells, while CXCR4 overexpression had opposite effects on the above cellular functions. Consistently, the xenograft tumor-bearing mice models were established, and the results supported that knockdown of CXCR4 inhibited tumor growth and the expression levels of Ki67 protein in vivo. In addition, the ccRCC cells were exposed to DDP treatment, and we surprisingly found that upregulation of CXCR4 increased DDP-resistance in ccRCC cells, and conversely, CXCR4 ablation sensitized ccRCC cells to DDP stimulation. Taken together, we concluded that CXCR4 ablation hindered cancer progression and enhanced DDP-sensitivity in ccRCC, and the present study identified a novel therapeutic biomarker for ccRCC.

Thermal conductivity is a crucial property for thermal management of modern electronics, thermal energy conversion, and energy sustainable development. However, it is very expensive and timeconsuming to calculate the phonon thermal conductivity of materials through the fully ab initio calculations or molecular dynamics simulations. Exploiting the fundamental correlation between elastic properties (bulk and shear modulus) and phonon thermal conductivity of crystalline materials, we develop an efficient method, phonon−elasticity−thermal (PET) model to rapidly and accurately estimate the phonon thermal conductivity at the high-temperature limit based on the Born−von Karman periodic boundary condition and Umklapp phonon−phonon scattering relaxation time approximation. As a demonstration, we calculate the phonon thermal conductivities of 226 inorganic solid materials covering the whole 7 crystalline systems within a high-throughput calculation framework on account of our PET model. The highthroughput prediced phonon thermal conductivities is in good agreement with experimental measurements. Our results imply the potential application of the elasticity-based phonon thermal conductivity estimation to screen or guide the material discovery of target phonon thermal conductivity and also provide a reference for the study of phonon−elasticity−thermal relationship.

The passive radiative cooling technology shows a great potential application on reducing the enormous global energy consumption. The multilayer metamaterials could enhance the radiative cooling performance. However, it is a challenge to design the radiative cooler. In this work, based on the particle swarm optimization (PSO) evolutionary algorithm, we develop an intelligent workflow in designing photonic radiative cooling metamaterials. Specifically, we design two 10-layer SiO2 radiative coolers doped by cylindrical MgF2 or Air impurities, possessing high emissivity within the selective (8-13 µm) and broadband (8-25 µm) atmospheric transparency window, respectively. Our two kinds of coolers demonstrate power density as high as 119 W/m2 and 132 W/m2 at the room temperature (300 K). Our scheme does not rely on the usage of special materials, forming high-performing metamaterials with conventional poor-performing components. This significant improvement of the emission spectra proves the effectiveness of our inverse design algorithm in boosting the discovery of high-performing functional metamaterials.