Reconstructing sources location of visual color cortex by the task-irrelevant visual stimuli through machine learning decoding

Visual color sensing is generated by electrical discharges from endocranial neuronal sources that penetrate the skull and reach to the cerebral cortex. However, the space location of the source generated by this neural mechanism remains elusive. In this paper, we emulate the generation of visual color signal by task-irrelevant stimuli to activate brain neurons, where its consequences over the cerebral cortex is experimentally tracked. We first document the changes to brain color sensing using electroencephalography (EEG), and find that the sensing classification accuracy of primary visual cortex (V1) regions was positively correlated with the space correlation of visual evoked potential (VEP) power distribution under machine learning decoding. We then explore the decoded results to trace the brain activity neural source location of EEG inversion problem and assess its reconstructive possibility. We show that visual color EEG in V1 can reconstruct endocranial neuronal source location, through the machine learning decoding of channel location.

A green, efficient, closed-loop direct regeneration technology for reconstructing of the LiNi0.5Co0.2Mn0.3O2 cathode material from spent lithium-ion batteries

Lithium nickel manganese cobalt oxide in the spent lithium ion batteries (LIBs) contains a lot of lithium, nickel, cobalt and manganese. However, how to effectively recover these valuable metals under the premise of reducing environmental pollution is still a challenge. In this work, a green, efficient, closed-loop direct regeneration technology is proposed to reconstruct LiNi_0.5Co_0.2Mn_0.3O₂ (NCM523) cathode materials from spent LIBs. Firstly, the failure mechanism of NCM523 cathode materials in the spent LIBs is analyzed deeply. It is found that the spent NCM523 material has problems such as the dissolution of lithium and transition metals, surface interface failure and structural transformation, resulting in serious deterioration of electrochemical performance. Then NCM523 material was directly regenerated by supplementing metal ions, granulation, ion doping and heat treatment. Meanwhile, PO₄^3- polyanions were doped into the regenerated NCM material in the recovery process, showing excellent electrochemical performance with discharge capacity of 189.8 mAh g^-1 at 0.1 C. The recovery process proposed in this study puts forward a new strategy for the recovery various lithium nickel cobalt manganese oxide (e.g., LiNi_1/3Co_1/3Mn_1/3O₂, LiNi_0.5Co_0.2Mn_0.3O₂, LiNi_0.6Co_0.2Mn_0.2O₂ and LiNi_0.8Co_0.1Mn_0.1O₂) and accelerates the industrialization of spent lithium ion battery recycling.