Polymorph of LiAlP₂O₇: Combined Computational, Synthetic, Crystallographic, and Ionic Conductivity Study

Area of Science:

• Solid-state chemistry
• Materials science
• Crystallography

Background:

• Lithium aluminum pyrophosphate (LiAlP2O7) is a material with potential applications in energy storage.
• Understanding its structural diversity and properties is crucial for optimizing its performance.
• Previous research has identified various polymorphs, but a comprehensive exploration of the phase field was lacking.

Purpose of the Study:

• To discover and characterize new polymorphs of lithium aluminum pyrophosphate.
• To investigate the structural, thermal, and ionic conductivity properties of the newly found polymorph.
• To computationally assess the stability and potential for ion conductivity enhancement in related structures.

Main Methods:

• Computationally guided synthetic exploration of the Li-Mg-Al-P-O phase field.
• Single-crystal X-ray diffraction for crystal structure determination (orthorhombic, Cmcm).
• Density functional theory (DFT) calculations for stability analysis.
• Alternating-current impedance spectroscopy and variable-temperature static 7Li NMR for Li-ion conductivity measurements.
• Bond-valence-sum mapping for topological analysis of ion pathways.

Main Results:

• A new orthorhombic polymorph of LiAlP2O7 (Cmcm) was synthesized and structurally characterized, stable up to ~1023 K.
• DFT calculations confirm this polymorph as the most stable low-temperature structure among seven known A(I)M(III)P2O7 types.
• Low bulk Li-ion conductivity was observed, attributed to long Li-Li distances and absence of Li pathways in the c-direction.
• Analysis identified two other structure types with favorable Li-site topologies for enhanced conductivity, potentially accessible via doping.

Conclusions:

• The discovery of a new LiAlP2O7 polymorph expands the understanding of its phase diagram and structural landscape.
• The identified structure, while stable, exhibits limited Li-ion conductivity due to specific structural features.
• Computational and topological analyses provide insights into designing related materials with improved ionic conductivity through doping strategies.