Structure determination of LISICON solid solutions by powder neutron diffraction

Abrahams, Isaac; Bruce, Peter G.; West, Anthony R.; David, William I. F.

doi:10.1016/0022-4596(88)90179-x

Cited by 32 publications

(33 citation statements)

References 13 publications

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“…The search for new, fast Li-ionic conductors has been area of considerable activity (1,2), as Li-ion based systems are very attractive for battery applications due to the electropositive nature of Li and its low density. A number of lithium titanates have been investigated including Li TiO (3), Li TiO (4), and Li Ti O .…”

Section: Introductionmentioning

confidence: 99%

A New Solid Solution Series Linking LiTi2O4and Li2Ti3O7Ramsdellites: A Combined X-Ray and Neutron Study

Gover

Irvine²

1998

Journal of Solid State Chemistry

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Section: Introductionmentioning

confidence: 99%

A New Solid Solution Series Linking LiTi2O4and Li2Ti3O7Ramsdellites: A Combined X-Ray and Neutron Study

Gover

Irvine²

1998

Journal of Solid State Chemistry

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“…The LISICON structure models developed on the basis of powder X ray diffraction data [6,7] are imple mented with low accuracy, and ancillary positions between the major Li positions (Li1 and Li2) are char acterized by abnormal interatomic distances.…”

Section: Analysis Of Lisicon Structure Modelsmentioning

confidence: 99%

“…According to Plattner and Voellenkle [5], superionic LISICON corresponds to the formula Li 6 Zn(GeO 4 ) 2 (Li 3 Zn 0.5 GeO 4 ); according to Abrahams et al [6,7], this is the only composition stable at room tempera ture and corresponds to the single phase crystalliza tion region in the Li 4 GeO 4 -Zn 2 GeO 4 system.…”

mentioning

confidence: 98%

“…structural analogues [2,3,12], at least five atomic models have been proposed for superionic LISICON with Pearson's indices from oP40 to oP52; this diver sity is because of an ambiguity of locating randomly disordered Li atoms. The structural models of LISI CON derived from studies of single crystals all having the least value of Pearson's index of oP40 but having different Wyckoff's sequences (d 2 c 5 a [4] and d 3 c 4 [5]) con siderably differ from the models advanced for ceramic LISICON samples (d 3 c 5 , d 4 c 4 b, and d 3 c 5 b) [6,7].…”

mentioning

confidence: 99%

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Mechanism of structural phase transitions in the Li4GeO4-ZnGeO4 system: Computer modeling and identification of invariant nanocluster structures in Li4GeO4, LISICON Li6Zn(GeO4)2, and Li4Zn2(GeO4)2 (γ phase)

Ilyushin

Блатов²,

Dem’yanets

et al. 2012

Russ. J. Inorg. Chem.

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The cluster modeling of structural phase transitions Li 4 GeO 4 → LISICON Li 6 Zn(GeO 4 ) 2 → γ Li 4 Zn 2 (GeO 4 ) 2 was carried out using computer assisted methods (the TOPOS program package). The pre cursor nanoclusters of crystal structures were recognized in an automated data processing mode using an algorithm developed for selecting combinations from nonintersecting suprapolyhedral clusters. 3D macro structure modeling employed the principle of maximal space filling and, accordingly, took into account the requirement for the maximal complementary connectivity of precursor nanoclusters in crystal structure self assembly followed by consecutive primary chain-microlayer-microframework assembly. A crystallochemi cally correct structure model was advanced for superionic LISICON Li 6 Zn(GeO 4 ) 2 as a 2D analogue of Li 4 GeO 4 containing only two types of voids in a layer, which are most likely to be sites for Li atoms to reside. A migration map was constructed to characterize the 2D set of conductivity channels in superionic LISICON.

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“…[27][28][29][30] Previous studies showed that its superionicity results from the existence of many vacant interstitial sites in its body-centered cubic (bcc) structure. 31,32 However, there are few studies that explain the superionic conduction mechanism quantitatively.…”

Section: α-Agimentioning

confidence: 99%

The graph-theoretic minimum energy path problem for ionic conduction

Kishida

2015

AIP Advances

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A new computational method was developed to analyze the ionic conduction mechanism in crystals through graph theory. The graph was organized into nodes, which represent the crystal structures modeled by ionic site occupation, and edges, which represent structure transitions via ionic jumps. We proposed a minimum energy path problem, which is similar to the shortest path problem. An effective algorithm to solve the problem was established. Since our method does not use randomized algorithm and time parameters, the computational cost to analyze conduction paths and a migration energy is very low. The power of the method was verified by applying it to α-AgI and the ionic conduction mechanism in α-AgI was revealed. The analysis using single point calculations found the minimum energy path for long-distance ionic conduction, which consists of 12 steps of ionic jumps in a unit cell. From the results, the detailed theoretical migration energy was calculated as 0.11 eV by geometry optimization and nudged elastic band method. Our method can refine candidates for possible jumps in crystals and it can be adapted to other computational methods, such as the nudged elastic band method. We expect that our method will be a powerful tool for analyzing ionic conduction mechanisms, even for large complex crystals. C

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Structure determination of LISICON solid solutions by powder neutron diffraction

Cited by 32 publications

References 13 publications

A New Solid Solution Series Linking LiTi2O4and Li2Ti3O7Ramsdellites: A Combined X-Ray and Neutron Study

A New Solid Solution Series Linking LiTi2O4and Li2Ti3O7Ramsdellites: A Combined X-Ray and Neutron Study

Mechanism of structural phase transitions in the Li4GeO4-ZnGeO4 system: Computer modeling and identification of invariant nanocluster structures in Li4GeO4, LISICON Li6Zn(GeO4)2, and Li4Zn2(GeO4)2 (γ phase)

The graph-theoretic minimum energy path problem for ionic conduction

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