Combining composition graded positive and negative electrodes for higher performance Li-ion batteries

Cheng, Chuan; Drummond, Ross; Duncan, Stephen R.; Grant, Patrick S.

doi:10.1016/j.jpowsour.2019.227376

Cited by 28 publications

(43 citation statements)

References 41 publications

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“…The arrangement of G and LTO layers in the multilayered structure is tailored simply by switching between G or LTO containing feedstock suspensions during deposition. This freedom in design for discrete layers and various types of grading [23][24][25][26][27][28][29] is not available by conventional slurry casting manufacture of LIB and LIC electrodes, and was investigated to obtain more attractive balance of overall LIC performance.…”

Section: Resultsmentioning

confidence: 99%

Scalable Multilayer Printing of Graphene Interfacial Layers for Ultrahigh Power Lithium‐Ion Storage

2020

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A low resistance graphene-based interfacial layer is developed for multi-layered lithium-ion capacitor electrodes using a layer-by-layer printing approach, with the goal of boosting energy storage performance at ultra-fast charge/discharge rates (≥ 100 C). The electrochemical behavior of spray printed Li 4 Ti 5 O 12 -based hetero-structure electrodes is investigated as a thin, discrete graphene layer is placed: (i) at the base of the Li 4 Ti 5 O 12 (at the electrode/current collector interface); (ii) on the top of the Li 4 Ti 5 O 12 (at the electrode/separator junction); and (iii) both at the base and on the top of the Li 4 Ti 5 O 12 (sandwich configuration), with marked improved electrode performance at > 50 C when the graphene layer is interleaved at the Li 4 Ti 5 O 12 /current collector interface. This best performing hetero-structure negative electrode is then coupled with a spray printed activated carbon positive electrode in a lithium-ion capacitor configuration, showing an attractive power density of ~ 8000 W/kg at 350 C. The fabrication of double-sided graphene/Li 4 Ti 5 O 12 multi-layered hetero-electrodes is successfully demonstrated over areas of 20 cm × 15 cm and in various patterned configurations.

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Section: Resultsmentioning

confidence: 99%

Scalable Multilayer Printing of Graphene Interfacial Layers for Ultrahigh Power Lithium‐Ion Storage

2020

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“…The voltage difference between the differential peaks in charge-discharge profiles were taken to calculate the cell polarization [21,22] in Fig. 5 (c).…”

Section: Electrochemical Performance Of Bi-layer Cathodesmentioning

confidence: 99%

“…Very few researchers have investigated graded electrodes through experiment to validate the simulation results [16][17][18][19][20][21][22][23]. Huang et al synthesized a thin (12.2µm) TiO 2 graded anode structure with two discrete layers fabricated by spray deposition [16].…”

Section: Introductionmentioning

confidence: 99%

“…Liu et al [20] and Cheng et al [21,22] ) with thicknesses ranging from 81µm to 143µm with the aid of the same spray deposition equipment used in [16]. Benefits of such graded structures over conventional electrodes include reduced capacity degradation rate (<50% at 1C [22] and 40-50% at 2C [21]), increased discharge capacity (120% at 1C [22], 31% at 2C [21], and ~7.6% at 0.1C [20]), and an improved power-energy density balance.…”

Section: Introductionmentioning

confidence: 99%

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Revisiting the promise of Bi-layer graded cathodes for improved Li-ion battery performance

Chowdhury

Zhao

Xia

et al. 2021

Sustainable Energy Fuels

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“…[1][2][3][4][5] However, their performance, durability, recyclability and CO2 fingerprint require further improvement to make feasible this transition. This can be achieved thanks to materials design, [6][7][8] innovative manufacturing [9][10][11] and manufacturing optimization, [12][13][14] or most likely, thanks to a combination of all of them. Regarding the latter, both experimental and modelling approaches can be used to carry out its optimization.…”

Section: Introductionmentioning

confidence: 99%

Accelerating Battery Manufacturing Optimization by Combining Experiments, In Silico Electrodes Generation and Machine Learning

Duquesnoy¹,

Lombardo²,

Chouchane³

et al. 2020

Preprint

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Both the society and the market calls for safer, high-performing and cheap Li-ion batteries (LIBs) in order to speed up the transition from oil-based to electric-based economy. One critical aspect to be taken into account in this modern challenge is LIBs manufacturing process, whose optimization is time and resources consuming due to the several interdependent physicochemical mechanisms involved. In order to tackle rapidly this challenge, digital tools able to accelerate LIBs manufacturing optimization are crucially needed for both well assessed and recently discovered chemistries. The methodology presented here encompasses experimental characterizations, in silico generation of electrode mesostructures and machine learning algorithms to track the effect of manufacturing over a wide array of mesoscale electrode properties critically linked to the electrochemical performance. Particularly, features as the interconnectivity of the particles network, the electrolyte tortuosity and effective ionic conductivity, the percentage of current collector surface covered by either active material or carbon-binder domain particles and the active material surface in contact with electrolyte were analysed and discussed in detail. This approach was tested and validated for the case of LiNi1/3Mn1/3Co1/3O2-based cathodes calendering, proving its capability to ease the process parameters-electrode properties interdependencies analysis, paving the way to deeper understanding and then faster optimization of LIBs manufacturing.

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Combining composition graded positive and negative electrodes for higher performance Li-ion batteries

Abstract: Please refer to published version for the most recent bibliographic citation information. If a published version is known of, the repository item page linked to above, will contain details on accessing it.

Cited by 28 publications

References 41 publications

Scalable Multilayer Printing of Graphene Interfacial Layers for Ultrahigh Power Lithium‐Ion Storage

Scalable Multilayer Printing of Graphene Interfacial Layers for Ultrahigh Power Lithium‐Ion Storage

Revisiting the promise of Bi-layer graded cathodes for improved Li-ion battery performance

Accelerating Battery Manufacturing Optimization by Combining Experiments, In Silico Electrodes Generation and Machine Learning

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