Li-ion battery materials: present and future

https://dc.engconfintl.org/cgi/viewcontent.cgi?article=1032&context=superalloys_ii

A critical review of high entropy alloys and related concepts

Here we summarize recent progress in machine learning for the chemical sciences. We outline machine-learning techniques that are suitable for addressing research questions in this domain, as well as future directions for the field. We envisage a future in which the design, synthesis, characterization and application of molecules and materials is accelerated by artificial intelligence.

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Machine learning for molecular and materials science.

Alloy negative electrodes for Li-ion batteries.

Garnet-type solid-state electrolytes have attracted extensive attention due to their high ionic conductivity, approaching 1 mS cm-1, excellent environmental stability, and wide electrochemical stability window, from lithium metal to ∼6 V. However, to date, there has been little success in the development of high-performance solid-state batteries using these exceptional materials, the major challenge being the high solid-solid interfacial impedance between the garnet electrolyte and electrode materials. In this work, we effectively address the large interfacial impedance between a lithium metal anode and the garnet electrolyte using ultrathin aluminium oxide (Al2O3) by atomic layer deposition. Li7La2.75Ca0.25Zr1.75Nb0.25O12 (LLCZN) is the garnet composition of choice in this work due to its reduced sintering temperature and increased lithium ion conductivity. A significant decrease of interfacial impedance, from 1,710 Ω cm2 to 1 Ω cm2, was observed at room temperature, effectively negating the lithium metal/garnet interfacial impedance. Experimental and computational results reveal that the oxide coating enables wetting of metallic lithium in contact with the garnet electrolyte surface and the lithiated-alumina interface allows effective lithium ion transport between the lithium metal anode and garnet electrolyte. We also demonstrate a working cell with a lithium metal anode, garnet electrolyte and a high-voltage cathode by applying the newly developed interface chemistry.

Negating interfacial impedance in garnet-based solid-state Li metal batteries

Accelerating the discovery of advanced materials is essential for human welfare and sustainable, clean energy. In this paper, we introduce the Materials Project (www.materialsproject.org), a core program of the Materials Genome Initiative that uses high-throughput computing to uncover the properties of all known inorganic materials. This open dataset can be accessed through multiple channels for both interactive exploration and data mining. The Materials Project also seeks to create open-source platforms for developing robust, sophisticated materials analyses. Future efforts will enable users to perform ‘‘rapid-prototyping’’ of new materials in silico, and provide researchers with new avenues for cost-effective, data-driven materials design. © 2013 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 Unported License.

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Commentary: The Materials Project: A materials genome approach to accelerating materials innovation

Abstract Objective The aim was to develop a nanoscale drug delivery system with enzyme responsive and acid sensitive particle size and intelligent degradation aiming to research the inhibitory effect on breast cancer. Significance The delivery system addressed the problems of tissue targeting, cellular internalization, and slow drug release at the target site, which could improve the efficiency of drug delivery and provide a feasible therapeutic approach for breast cancer. Methods The acid sensitive functional material DSPE-PEG2000-dyn-PEG-R9 was synthesized by Michael addition reaction. Then, the berberine plus baicalin intelligent micelles were prepared by thin-film hydration. Subsequently, we characterized the physical and chemical properties of berberine plus baicalin intelligent micelles, evaluated its anti-tumor effects in vivo and in vitro. Results The target molecule was successfully synthesized, and the intelligent micelles showed excellent chemical and physical properties, delayed drug release and high encapsulation efficiency. In vitro and in vivo experiments also confirmed that the intelligent micelles could effectively target tumor sites, penetrate tumor tissues, enrich in tumor cells, inhibit tumor cell proliferation, inhibit tumor cell invasion and migration, and induce tumor cell apoptosis. Conclusion Berberine plus baicalin intelligent micelles have excellent anti-tumor effects and no toxicity to normal tissues, which provides a new potential drug delivery strategy for the treatment of breast cancer.

Wei-Wei Chen

Papers

Commentary: The Materials Project: A materials genome approach to accelerating materials innovation

Multiple stimulus-response berberine plus baicalin micelles with particle size-charge-release triple variable properties for breast cancer therapy