Engineering topics
Wei, Yuan
Publications and source records attributed to Wei, Yuan.
The role of oxygen in automotive grade lithium-ion battery cathodes: an atomistic survey of ageing
The rising demand for high-performance lithium-ion batteries, pivotal to electric transportation, hinges on key materials like the Ni-rich layered oxide LiNi x Co y Al z O 2 (NCA) used in cathodes. The present study investigates the redox mechanisms, with particular focus on the role of oxygen in commercial NCA electrodes, both fresh and aged under various conditions (aged cells have performed >900 cycles until a cathode capacity retention of ~80%). Our findings reveal that oxygen participates in charge compensation during NCA delithiation, both through changes in transition metal (TM)–O bond hybridization and formation of partially reversible O 2 , the latter occurs already below 3.8 V vs. Li/Li + . Aged NCA material undergoes more significant changes in TM–O bond hybridization when cycling above 50% SoC, while reversible O 2 formation is maintained. Nickel is found to be redox active throughout the entire delithiation and shows a more classical oxidation state change during cycling with smaller changes in the Ni–O hybridization. By contrast, Co redox activity relies on a stronger change in Co–O hybridization, with only smaller Co oxidation state changes. The Ni–O bond displays an almost twice as large change in its bond length on cycling as the Co–O bond. The Ni–O 6 octahedra are similar in size to the Co–O 6 octahedra in the delithiated state, but are larger in the lithiated state, a size difference that increases with battery ageing. These contrasting redox activities are reflected directly in structural changes. The NCA material exhibits the formation of nanopores upon ageing, and a possible connection to oxygen redox activity is discussed. The difference in interaction of Ni and Co with oxygen provides a key understanding of the mechanism and the electrochemical instability of Ni-rich layered transition metal oxide electrodes. Our research specifically highlights the significance of the role of oxygen in the electrochemical performance of electric-vehicle-grade NCA electrodes, offering important insights for the creation of next-generation long-lived lithium-ion batteries.
Antiferromagnetism in the kagome-lattice compound α-Cu 3 Mg(OH) 6 Br 2
The antiferromagnetism in α-Cu 3 Mg(OH) 6 Br 2 was studied by magnetic-susceptibility, specificheat and neutron-diffraction measurements. The crystal structure consists of Cu 2+ kagome layers with Mg 2+ ions occupying the centers of the hexagons, separated by Br 1- ions. The magnetic system orders antiferromagnetically at 5.4 K with the magnetic moments aligned ferromagnetically within the kagome planes. The ordered moment is 0.94 µ B , suggesting little quantum and geometrical fluctuations. By comparing the magnetic and specific-heat properties with those of the haydeeite, we suggest that α-Cu 3 Mg(OH) 6 Br 2 may be described by the two-dimensional spin-1/2 Heisenberg kagome model and is in the region of the ferromagnetic-order side of the phase diagram.
Infrared and radar fusion detection method based on heterogeneous data preprocessing
The difficulty in infrared and radar fusion target detection lies in the pre-processing steps such as sample reduction and feature reduction of heterogeneous sensors. For the problem of data volume redundancy, HVS sample reduction is proposed to reduce the amount of data in the infrared data set. Infrared and radar joint feature vectors are constructed through nearest neighbor data association. For the problem of feature redundancy, a weighted mutual information feature selection method based on prior information is proposed according to the difference of feature sources. The fusion data set is then used for classification. The experiments show that the HVS-based sample reduction and the prior weighted feature selection achieved a higher detection probability and a shorter detection time, and improved the robustness in the case of large differences between the training set and the test set.