Establishing baselines for generative discovery of inorganic crystals.

Generative artificial intelligence offers a promising avenue for materials discovery, yet its advantages over traditional methods remain unclear. In this work, we introduce and benchmark two baseline approaches - random enumeration of charge-balanced prototypes and data-driven ion exchange of known compounds - against four generative techniques based on diffusion models, variational autoencoders, and large language models. Our results show that established methods such as ion exchange are better at generating novel materials that are stable, although many of these closely resemble known compounds.

Unraveling the Growth Dynamics of Rutile SnGeO Using Theory and Experiment.

Rutile GeO and related materials are attracting interest due to their ultrawide band gaps and potential for ambipolar doping in high-power electronic applications. This study examines the growth of rutile SnGeO films through oxygen-plasma-assisted hybrid molecular beam epitaxy (hMBE). The film composition and thickness are evaluated across a range of growth conditions, with the outcomes rationalized by using density functional theory calculations.

Coherent-Precipitation-Stabilized Phase Formation in Over-Stoichiometric Rocksalt-Type Li Superionic Conductors.

Rationalizing synthetic pathways is crucial for material design and property optimization, especially for polymorphic and metastable phases. Over-stoichiometric rocksalt (ORX) compounds, characterized by their face-sharing configurations, are a promising group of materials with unique properties; however, their development is significantly hindered by challenges in synthesizability. Here, taking the recently identified Li superionic conductor, over-stoichiometric rocksalt Li-In-Sn-O (o-LISO) material as a prototypical ORX compound, the mechanisms of phase formation are systematically investigated.

Direct Lithium Extraction from α-Spodumene through Solid-State Reactions for Sustainable LiCO Production.

With increasing battery demand comes a need for diversified Li sources beyond brines. Among all Li-bearing minerals, spodumene is most often used for its high Li content and natural abundance. However, the traditional approach to process spodumene is costly and energy-intensive, requiring the mineral be transformed from its natural α to β phase at >1000 °C.

Quantifying the regime of thermodynamic control for solid-state reactions during ternary metal oxide synthesis.

The success of solid-state synthesis often hinges on the first intermediate phase that forms, which determines the remaining driving force to produce the desired target material. Recent work suggests that when reaction energies are large, thermodynamics primarily dictates the initial product formed, regardless of reactant stoichiometry. Here, we validate this principle and quantify its constraints by performing in situ characterization on 37 pairs of reactants.

Selective formation of metastable polymorphs in solid-state synthesis.

Metastable polymorphs often result from the interplay between thermodynamics and kinetics. Despite advances in predictive synthesis for solution-based techniques, there remains a lack of methods to design solid-state reactions targeting metastable materials. Here, we introduce a theoretical framework to predict and control polymorph selectivity in solid-state reactions.

Autonomous and dynamic precursor selection for solid-state materials synthesis.

Solid-state synthesis plays an important role in the development of new materials and technologies. While in situ characterization and ab-initio computations have advanced our understanding of materials synthesis, experiments targeting new compounds often still require many different precursors and conditions to be tested. Here we introduce an algorithm (ARROWS) designed to automate the selection of optimal precursors for solid-state materials synthesis.

Toward autonomous design and synthesis of novel inorganic materials.

Autonomous experimentation driven by artificial intelligence (AI) provides an exciting opportunity to revolutionize inorganic materials discovery and development. Herein, we review recent progress in the design of self-driving laboratories, including robotics to automate materials synthesis and characterization, in conjunction with AI to interpret experimental outcomes and propose new experimental procedures. We focus on efforts to automate inorganic synthesis through solution-based routes, solid-state reactions, and thin film deposition.

Design of Heteroanionic MoON Exhibiting a Peierls Metal-Insulator Transition.

Using a first-principles approach, we design the heteroanionic oxynitride MoON to exhibit a first-order isosymmetric thermally activated Peierls-type metal-insulator transition (MIT). We identify a ground state insulating phase (α-MoON) with monoclinic Pc symmetry and a metastable high temperature metallic phase (β-MoON) of equivalent symmetry. We find that ordered fac-MoO_{3}N_{3} octahedra with edge and corner connectivity stabilize the twisted Mo-Mo dimers present in the α phase, which activate the MIT through electron localization within the 4d a_{1g} manifold.