There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Fast parallel algorithms for short-range molecular dynamics

Accelerating the discovery of advanced materials is essential for human welfare and sustainable, clean energy. In this paper, we introduce the Materials Project (www.materialsproject.org), a core program of the Materials Genome Initiative that uses high-throughput computing to uncover the properties of all known inorganic materials. This open dataset can be accessed through multiple channels for both interactive exploration and data mining. The Materials Project also seeks to create open-source platforms for developing robust, sophisticated materials analyses. Future efforts will enable users to perform ‘‘rapid-prototyping’’ of new materials in silico, and provide researchers with new avenues for cost-effective, data-driven materials design. © 2013 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 Unported License.

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Commentary: The Materials Project: A materials genome approach to accelerating materials innovation

Li-ion battery materials: present and future

https://dc.engconfintl.org/cgi/viewcontent.cgi?article=1032&context=superalloys_ii

A critical review of high entropy alloys and related concepts

I4-type LiZnPS4 solid electrolyte was synthesized starting from Li2S, P2S5, and ZnS, and its room temperature ionic conductivity, σ25°C, was ∼10–8 S/cm. To improve σ25°C, compositions of Li1+2xZn1–xPS4 (x = 0.125, 0.25, 0.375, 0.5, 0.625, 0.75, 0.8, 0.9) were synthesized from mixtures of LiZnPS4 and amorphous Li3PS4 (a-LPS). The samples with x ≤ 0.8 were confirmed by means of XRD and Raman spectroscopy to have the I4 structure. The maximum σ25°C was 5.7 × 10–4 S/cm at x = 0.625. NMR measurement revealed that Li1+2xZn1–xPS4 (x ≤ 0.625) is almost a single phase material and not a simple mixture of LiZnPS4 and a-LPS, confirming that its crystal structure is responsible for the improved ionic conductivity. Li2.25Zn0.375PS4 (x = 0.625) was reactive to graphite and indium anodes but stable against a Li4Ti5O12 anode and a 4 V class cathode. We fabricated an all-solid-state battery in the form of graphite|a-LPS|Li2.25Zn0.375PS4|Li2O-ZrO2 coated Li(Ni, Mn, Co)O2 and examined its performance. It showed a first-cy...

Synthesis and Electrochemical Properties of I4̅-Type Li1+2xZn1–xPS4 Solid Electrolyte

Li9S3N (LSN) is investigated as a new lithium ion conductor and barrier coating between an electrolyte and Li metal anode in all solid state lithium ion batteries. LSN is an intriguing material since it has a 3-dimensional conduction channel, high lithium content, and is expected to be stable against lithium metal. The conductivity of LSN is measured with impedance spectroscopy as 8.3 × 10−7 S cm−1 at room temperature with an activation energy of 0.52 eV. Cyclic voltammetry (CV) scans showed reversible Li plating and striping. First principles calculations of stability, nudged elastic band (NEB) calculations, and ab initio molecular dynamics (AIMD) simulations support these experimental results. Substitution as a means to enhance conductivity is also investigated. First-principles calculations predict that divalent cation substituents displace a lithium from a tetrahedral site along the migration pathway, and reduce the migration energy for the lithium ions in the vicinity of the substituent. A percolating path with low migration energies (∼0.3 eV) can be formed throughout the crystal structure at a concentration of Li8.5M0.25S3N (M = Ca2+, Zn2+, or Mg2+), resulting in predicted conductivities as high as σ300 K = 2.3 mS cm−1 at this concentration. However, the enhanced conductivity comes at the expense of relatively large substitution energy. Halide substitution, such as Cl on a S site ( in Kroger–Vink notation), has a relatively low energy cost, but only provides a modest improvement in conductivity.

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Li-ion conductivity in Li9S3N

We present an investigation of the phase stability, electrochemical stability and Li+ conductivity in the Li10±1MP2X12 (M = Ge, Si, Sn, Al or P, and X = O, S or Se) family of superionic conductors. The Li10GeP2S12 (LGPS) superionic conductor has the highest Li+ conductivity reported to date, with excellent electrochemical performance demonstrated in a Li-ion rechargeable battery. Our results show that isovalent cation substitutions of Ge4+ have a small effect on the relevant intrinsic properties, with Li10SiP2S12 and Li10SnP2S12 having similar phase stability, electrochemical stability and Li+ conductivity as LGPS. Aliovalent cation ∗To whom correspondence should be addressed †Massachusetts Institute of Technology ‡Samsung Advanced Institute of Technology 1 substitutions (M = Al or P) with compensating changes in Li+ concentration also have a small effect on the Li+ conductivity in this structure. Anion substitutions, however, have a much larger effect on these properties. The oxygen-substituted Li10MP2O12 compounds are in general predicted not to be stable (with equilibrium decomposition energies > 90 meV/atom) and have much lower Li+ conductivities than their sulfide counterparts. The selenium-substituted Li10MP2Se12 compounds, on the other hand, show a marginal improvement in conductivity, but at the expense of reduced electrochemical stability. We also studied the effect of lattice parameter changes on the Li+ conductivity and found the same asymmetry in behavior between increases and decreases in the lattice parameters, i.e., decreases in the lattice parameters lower the Li+ conductivity significantly, while increases in the lattice parameters increase the Li+ conductivity only marginally. Based on these results, we conclude that the size of the S2− is near optimal for Li+ conduction in this structural framework.

Phase stability, electrochemical stability and ionic conductivity of the Li[subscript 10±1]MP[subscript 2]X[subscript 12] (M = Ge, Si, Sn, Al or P, and X = O, S or Se) family of superionic conductors

A solid electrolyte material represented by Formula 1: L 1+2x (M1) 1-x (M2)(M3) 4   Formula 1
 wherein 0.25<x<1, L is at least one element selected from a Group 1 element, M1 is at least one element selected from a Group 2 element, a Group 3 element, a Group 12 element, and a Group 13 element, M2 is at least one element selected from a Group 5 element, a Group 14 element, and a Group 15 element, and M3 is at least one element selected from a Group 16 element, and wherein the solid electrolyte material has an I-4 crystal structure.

William D. Richards

Papers

Synthesis and Electrochemical Properties of I4̅-Type Li1+2xZn1–xPS4 Solid Electrolyte

Li-ion conductivity in Li9S3N

Phase stability, electrochemical stability and ionic conductivity of the Li[subscript 10±1]MP[subscript 2]X[subscript 12] (M = Ge, Si, Sn, Al or P, and X = O, S or Se) family of superionic conductors

Solid electrolyte and lithium battery including the same

Synthesis and Electrochemical Property of I-4 Type Li1+2xZn1-XPS4 Solid Electrolyte