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锂-氧气电池因其超高的理论比容量而受到科研界的广泛关注, 但其存在较为严重的充放电极化和较差的循环稳定性等问题, 从而极大地限制其商业化进程. 因此设计出有效的正极催化剂是解决锂-氧气电池面临的这些棘手问题的必要手段. 通过对不同充电状态的废旧锂电池正极进行回收制得三种不同锂含量的多元金属氧化物LixMO (x=0.79, 0.30, 0.08; M=Ni/Co/Mn), 并分别用作锂-氧气电池正极催化剂. 系统研究了LixMO材料中锂含量及晶体结构对其电化学性能的影响. 电化学测试结果表明, 与Li0.79MO和Li0.08MO催化剂相比, 基于Li0.30MO为正极催化剂的锂-氧气电池在电流密度100 mA•g–1和限定容量800 mAh•g–1的条件下具有较高的放电比容量(14655.9 mAh•g–1)、较低的充电电压(3.83 V)和较高的能量转换效率(72.2%). 而且该电池体系在充放电循环140圈后充电终止电压仍低于4.3 V. 最终认为制得的Li0.30MO材料具有优异的催化性能归因于其稳定的层状-岩盐相复合结构以及结构中富含的氧化镍相和氧空位之间的协同作用. 这些优点能够促进放电产物的可逆形成与分解, 从而提高锂-氧气电池循环性能. 相似文献
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Advances in neuromorphic computing:Expanding horizons for AI development through novel artificial neurons and in-sensor computing
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AI development has brought great success to upgrading the information age. At the same time, the large-scale artificial neural network for building AI systems is thirsty for computing power, which is barely satisfied by the conventional computing hardware. In the post-Moore era, the increase in computing power brought about by the size reduction of CMOS in very large-scale integrated circuits(VLSIC) is challenging to meet the growing demand for AI computing power. To address the issue, technical... 相似文献
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