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Record W2342989935 · doi:10.1149/ma2016-03/2/337

A Novel P2-Type Layered Cathode Material for Sodium-Ion Batteries

2016· article· en· W2342989935 on OpenAlexaff
Hari Vignesh Ramasamy, K. Karthikeyan, Xueliang Sun, Hyun Jun Choi, Ranjith Thangavel, Gyung Hwan Lee, Park Sung Ho, Yun‐Sung Lee

Bibliographic record

VenueECS Meeting Abstracts · 2016
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsWestern University
Fundersnot available
KeywordsCathodeMaterials scienceElectrochemistryElectrolyteIonEnergy storageLithium (medication)CoatingDissolutionOctahedronChemical engineeringNanotechnologyEngineering physicsChemistryPower (physics)Electrical engineeringElectrodeEngineering

Abstract

fetched live from OpenAlex

Since 1990 lithium-ion (Li-ion) batteries have been commercially available and currently remain as the technology of choice for applications where high energy densities are required. Sodium-ion (Na-ion) technology is similar in many ways to Li-ion technology, but is still in its initial stage. Current research trends are mostly based on Na-ion based technology due to several commercial advantages, including lower cost, greater sustainability and improved safety characteristics.1, 2 Among different types of cathode materials available, layered oxides such as NaxMO2 (M = transition metal) have shown great promise in terms of both cost and performance.3,4 According to Delmas et al, these layered oxides are classified into different structures, the most common of which are O3, P2 and P3.5 In these descriptions, the O and P refer to an octahedral (O), or prismatic (P), coordination of the Na-ions, and the number refers to the number of layers in the unit cell. P2-type Na-Ni-Mn-O has been considered as a suitable cathode material for the modern day requirement of high power and energy applications due to their low cost, easy synthesis and high theoretical capacity of greater than 250 mAhg-1. However this material has the serious problem of capacity fading due to structural instability. Cationic substitution and surface coating was an efficient strategy to enhance the electrochemical performance by improving the structural stability and preventing Mn3+ dissolution into electrolyte at higher voltages. In this work a novel P2-type Na0.5Ni0.33Cu0.07Mn0.67O2 was synthesized using the single step conventional solid state method and studied as cathode material for sodium ion batteries. The presence of Cu in the lattice structure enhanced the capacity retention to 83% after 100 cycles along with smooth voltage plateau in the high voltage region as shown in Figure 1. Surface coating with MgO increased the specific capacity of the material in the extended voltage window of 2.0 – 4.5V. The MgO coated material shows a smooth voltage plateau without any phase gliding in the higher voltage as in Figure 2. The capacity retention after 70 cycles is found to be 77.6% with enhanced performance. Hence the MgO coated Na0.5Ni0.26Cu0.07Mn0.67O2is studied as a novel cathode for room temperature Na-ion batteries. References: [1] V. Palomares, P. Serras, I. Villaluenga, K.B. Hueso, J. Carretero-Gonz, T. Rojo, Energy Environ. Sci. 5, 2012, 5884. [2] J. Barker, M.Y. Saidi, J. Swoyer, Electrochem. Solid St. 6, 2003, A1. [3] S.W. Kim, D.H. Seo, X. Ma, G. Ceder, K. Kang, Adv. Energy Mater. 2, 2012, 710. [4] M. Slater, D. Kim, E. Lee, C.S. Johnson, Adv. Func. Mater. 23, 2013, 947. [5] C. Delmas, C. Fouassier, P. Hagenmuller, Physica B+C , 99, 1980, 81. Figure 1(a). Cycle stability of Na0.5Ni0.26Cu0.07Mn0.66O2 at 0.25C from 2.0 - 4.25V. ( Inset figure shows the XRD pattern and unit cell diagram of metal substituted sample). (b) Cyclic stability of MgO coated Na0.5Ni0.26Cu0.07Mn0.66O2 in high voltage of 2-4.5V Figure 1

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.025
GPT teacher head0.257
Teacher spread0.232 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2016
Admission routes1
Has abstractyes

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