The nature of the nonmetal–metal transition in LixCoO2 oxide

Milewska, Anna; Świerczek, Konrad; Toboła, J.; Boudoire, Florent; Hu, Yongfeng; Bora, Debajeet K.; Mun, Bongjin Simon; Braun, Artur; Molenda, Janina

doi:10.1016/j.ssi.2014.05.011

Cited by 64 publications

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“…Embedded crossbar memory eliminates the need for this data movement as processing and memory storage are co-located, mimicking the high density interconnectivity found in the brain. [31,32] Furthermore, Li intercalation has been demonstrated with overpotentials as low as 5 mV, and at high current densities with overpotentials as low as 100 mV. Specifically, there are two key neuromorphic computational kernels that are more efficient on a crossbar: vector-matrix multiplication and parallel rank 1 weight updates.…”

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confidence: 99%

“…A 400 nm thick lithium phosphorous oxynitride electrolyte (LiPON) layer (green) separates the channel from a 50 nm Si gate electrode (purple). [31,43] As the fraction x in Li 1−x CoO 2 is varied from 0 to 0.5 the material undergoes an insulator-to-metal transition with nearly six orders of magnitude increase in electronic conductivity. [39] Figure 1b is a diagram illustrating the resistance switching mechanism in a LISTA device.…”

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confidence: 99%

“…The LiPON solid electrolyte was chosen for scalability (≈20 nm), [38] a large chemical stability window, and a high electrical resistivity (>10 15 Ω cm). [31,40] This process is highly reversible, and the application of a positive voltage V G with respect to OCP acts to re-intercalate Li ions (reducing Co from 4+ to 3+) and return the channel to its initial conductivity. Here, voltage applied to the gate, V G, determines the source-drain conductance, G SD, by controlling the Li content in the channel.…”

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Li‐Ion Synaptic Transistor for Low Power Analog Computing

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Nonvolatile redox transistors (NVRTs) based upon Li-ion battery materials are demonstrated as memory elements for neuromorphic computer architectures with multi-level analog states, "write" linearity, low-voltage switching, and low power dissipation. Simulations of backpropagation using the device properties reach ideal classification accuracy. Physics-based simulations predict energy costs per "write" operation of <10 aJ when scaled to 200 nm × 200 nm.

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Li‐Ion Synaptic Transistor for Low Power Analog Computing

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“…5). In fact, according to band-structure calculations by Mileweska et al [29,30], the Fermi level is located in the bandgap for Li 1 CoO 2 , but for Li 0.99 CoO 2 already within the electronic band. Using the relation between Pauli-susceptibility…”

Section: Discussion Of χ 0 : Metal/insulator Transitionmentioning

confidence: 96%

“…From the χ-values measured operando at 300 K an increase of D(ε F ) by 6.8/eV is deduced for the range x = 1.00 − 0.77, taking into account that D(E F ) = 0 for Li 1 CoO 2 [29] and assuming that the contribution of localized momenta is constant within this range. The observed increase of D(ε F ) with Li-extraction appears to be slightly higher than the value of 4.5 states/eV which can be derived from the band-structure calculations between x = 0.99 and x = 0.60 [29]. Obviously, the χ 0 variation with Li + -concentration cannot entirely be attributed to a rise of D(ε F ).…”

Section: Discussion Of χ 0 : Metal/insulator Transitionmentioning

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Charging of lithium cobalt oxide battery cathodes studied by means of magnetometry

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Modeling the Metal–Insulator Phase Transition in Li_xCoO₂ for Energy and Information Storage

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Zhou

Fraggedakis

et al. 2019

Adv Funct Materials

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An electro-chemomechanical phase-field model is developed to capture the metal-insulator phase transformation along with the structural and chemical changes that occur in Li x CoO 2 in the regular operating range of 0.5 < x < 1. Under equilibrium, in the regime of phase coexistence, it is found that transport limitations lead to kinetically arrested states that are not determined by strain-energy minimization. Further, lithiation profiles are obtained for different discharging rates and the experimentally observed voltage plateau is observed. Finally, a simple model is developed to account for the conductivity changes for a polycrystalline Li x CoO 2 thin film as it transforms from the metallic phase to the insulating phase and a strategy is outlined for memristor design. The theory can therefore be used for modeling Li x CoO 2 -electrode batteries as well as low voltage nonvolatile redox transistors for neuromorphic computing architectures.The ORCID identification number(s) for the author(s) of this article can be found under https://doi.org/10.1002/adfm.201902821. the lithiation process, the crystal structure of LCO remains unchanged with the host lattice contracting along the c-axis. [8,12,13] Another important characteristic of LCO is the metal-insulator transition, in which the material transitions from a good (x < 0.75) to a poor (x > 0.94) electron conductor. [8,21,25] The metal-insulator phase coexistence, during the transition, is observed macroscopically through a voltage plateau in the voltage versus state of charge diagram, occurring over the entire range of 0.75 < x < 0.94. [13,21,25] The layered structure of LCO allows for Li to diffuse only in the plane perpendicular to the [0001] direction, leading to effectively 2D transport in the crystal. [11,26] LCO is therefore a widely studied material and has been in commercial use in battery technology for over three decades. [1,2] Thus, developing a predictive mesoscopic model is paramount in studying the nonequilibrium charging/discharging as well as phase-separating behavior for this material.Recently, there has been renewed interest in LCO because of its metal-insulator transition behavior for the development of nonvolatile redox memristors to be used in neuromorphic computing technology. [27] In order to mimic the efficiency of the human brain, neuromorphic computing architecture is becoming an exciting avenue toward development of hardware specialized for machine learning and pattern recognition algorithms. [28][29][30] Current CMOS technologies consume high energy due to the movement of data between the processor, and static and dynamic random access memory. [27,31] In contrast, resistive memory crossbars, in which processing and memory storage occurs simultaneously, have been predicted to lower this energy requirement by six orders of magnitude. [32,33] The memristor, first proposed by Leon Chua, is the unit circuit element that forms the basis of this architecture. [34] The current state-of-the-art memristors, e.g., phase-change memories (PCM) [35...

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The nature of the nonmetal–metal transition in LixCoO2 oxide

Cited by 64 publications

References 27 publications

Li‐Ion Synaptic Transistor for Low Power Analog Computing

Li‐Ion Synaptic Transistor for Low Power Analog Computing

Charging of lithium cobalt oxide battery cathodes studied by means of magnetometry

Modeling the Metal–Insulator Phase Transition in Li_xCoO₂ for Energy and Information Storage

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The nature of the nonmetal–metal transition in LixCoO2 oxide

Cited by 64 publications

References 27 publications

Li‐Ion Synaptic Transistor for Low Power Analog Computing

Li‐Ion Synaptic Transistor for Low Power Analog Computing

Charging of lithium cobalt oxide battery cathodes studied by means of magnetometry

Modeling the Metal–Insulator Phase Transition in LixCoO2 for Energy and Information Storage

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Modeling the Metal–Insulator Phase Transition in Li_xCoO₂ for Energy and Information Storage