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Abstract: Metal–organic frameworks (MOFs) are crystalline synthetic porous materials formed by binding organic linkers to metal nodes: they can be either rigid1,2 or flexible3. Zeolites and rigid MOFs have widespread applications in sorption, separation and catalysis that arise from their ability to control the arrangement and chemistry of guest molecules in their pores via the shape and functionality of their internal surface, defined by their chemistry and structure4,5. Their structures correspond to an energy landscape with a single, albeit highly functional, energy minimum. By contrast, proteins function by navigating between multiple metastable structures using bond rotations of the polypeptide6,7, where each structure lies in one of the minima of a conformational energy landscape and can be selected according to the chemistry of the molecules that interact with the protein. These structural changes are realized through the mechanisms of conformational selection (where a higher-energy minimum characteristic of the protein is stabilized by small-molecule binding) and induced fit (where a small molecule imposes a structure on the protein that is not a minimum in the absence of that molecule)8. Here we show that rotation about covalent bonds in a peptide linker can change a flexible MOF to afford nine distinct crystal structures, revealing a conformational energy landscape that is characterized by multiple structural minima. The uptake of small-molecule guests by the MOF can be chemically triggered by inducing peptide conformational change. This change transforms the material from a minimum on the landscape that is inactive for guest sorption to an active one. Chemical control of the conformation of a flexible organic linker offers a route to modifying the pore geometry and internal surface chemistry and thus the function of open-framework materials.

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Abstract: It is challenging to achieve p-type doping of zinc oxides (ZnO), which are of interest as transparent conductors in optoelectronics. A ZnO-related ternary compound, SrZnO2, was investigated as a potential host for p-type conductivity. First-principles investigations were used to select from a range of candidate dopants the substitution of Li+ for Zn2+ as a stable, potentially p-type, doping mechanism in SrZnO2. Subsequently, single-phase bulk samples of a new p-type-doped oxide, SrZn1–xLixO2 (0 < x < 0.06), were prepared. The structural, compositional, and physical properties of both the parent SrZnO2 and SrZn1–xLixO2 were experimentally verified. The band gap of SrZnO2 was calculated using HSE06 at 3.80 eV and experimentally measured at 4.27 eV, which confirmed the optical transparency of the material. Powder X-ray diffraction and inductively coupled plasma analysis were combined to show that single-phase ceramic samples can be accessed in the compositional range x < 0.06. A positive Seebeck coefficient of 353(4) μV K–1 for SrZn1–xLixO2, where x = 0.021, confirmed that the compound is a p-type conductor, which is consistent with the pO2 dependence of the electrical conductivity observed in all SrZn1–xLixO2 samples. The conductivity of SrZn1–xLixO2 is up to 15 times greater than that of undoped SrZnO2 (for x = 0.028 σ = 2.53 μS cm–1 at 600 °C and 1 atm of O2).

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Abstract: In order to understand the structural and compositional factors controlling lithium transport in sulfides, we explored the Li5AlS4 – Li4GeS4 phase field for new materials. Both parent compounds are defined structurally by a hexagonal close packed sulfide lattice, where distinct arrangements of tetrahedral metal sites give Li5AlS4 a layered structure and Li4GeS4 a three dimensional structure related to γ-Li3PO4. The combination of the two distinct structural motifs is expected to lead to new structural chemistry. We identified the new crystalline phase Li4.4Al0.4Ge0.6S4, and investigated the structure and Li+ ion dynamics of the family of structurally related materials Li4.4M0.4M’0.6S4 (M = Al3+, Ga3+ and M’= Ge4+, Sn4+). We used neutron diffraction to solve the full structures of the Al-homologues, which adopt a layered close-packed structure with a new arrangement of tetrahedral (M/M’) sites and a novel combination of ordered and disordered lithium vacancies. AC impedance spectroscopy revealed lithium conductivities in the range 3(2) x 10-6 to 4.3(3) x 10-5 S cm-1 at room temperature with activation energies between 0.43(1) and 0.38(1) eV. Electrochemical performance was tested in a plating and stripping experiment against Li metal electrodes and showed good stability of the Li4.4Al0.4Ge0.6S4 phase over 200 hours. A combination of variable temperature 7Li solid state nuclear magnetic resonance spectroscopy and ab initio molecular dynamics calculations on selected phases showed that two dimensional diffusion with a low energy barrier of 0.17 eV is responsible for long-range lithium transport, with diffusion pathways mediated by the disordered vacancies while the ordered vacancies do not contribute to the conductivity. This new structural family of sulfide Li+ ion conductors offers insight into the role of disordered vacancies on Li+ ion conductivity mechanisms in hexagonally close packed sulfides that can inform future materials design.

Open Access

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Abstract: Covalent organic frameworks (COFs) are network polymers with long-range positional order whose properties can be tuned using the isoreticular chemistry approach. Making COFs from strong bonds is challenging because irreversible rapid formation of the network produces amorphous materials with locked-in disorder. Reversibility in bond formation is essential to generate ordered networks, as it allows the error-checking that permits the network to crystallise, and so candidate network-forming chemistries such as amide that are irreversible under conventional low temperature bond-forming conditions have been underexplored. Here we show that we can prepare two- and three-dimensional covalent amide frameworks (CAFs) by devitrification of amorphous polyamide network polymers using high-temperature and high-pressure reaction conditions. In this way we have accessed reversible amide bond formation that allows crystalline order to develop. This strategy permits the direct synthesis of practically irreversible ordered amide networks that are stable thermally and under both strong acidic and basic hydrolytic conditions.

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Abstract: The discovery of new materials is hampered by the lack of efficient approaches to the exploration of both the large number of possible elemental compositions for such materials, and of the candidate structures at each composition1. For example, the discovery of inorganic extended solid structures has relied on knowledge of crystal chemistry coupled with time-consuming materials synthesis with systematically varied elemental ratios2, 3. Computational methods have been developed to guide synthesis by predicting structures at specific compositions4, 5, 6 and predicting compositions for known crystal structures7, 8, with notable successes9, 10. However, the challenge of finding qualitatively new, experimentally realizable compounds, with crystal structures where the unit cell and the atom positions within it differ from known structures, remains for compositionally complex systems. Many valuable properties arise from substitution into known crystal structures, but materials discovery using this approach alone risks both missing best-in-class performance and attempting design with incomplete knowledge8, 11. Here we report the experimental discovery of two structure types by computational identification of the region of a complex inorganic phase field that contains them. This is achieved by computing probe structures that capture the chemical and structural diversity of the system and whose energies can be ranked against combinations of currently known materials. Subsequent experimental exploration of the lowest-energy regions of the computed phase diagram affords two materials with previously unreported crystal structures featuring unusual structural motifs. This approach will accelerate the systematic discovery of new materials in complex compositional spaces by efficiently guiding synthesis and enhancing the predictive power of the computational tools through expansion of the knowledge base underpinning them.