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Abstract We report a deep learning‐based approach to accurately predict the emission spectra of phosphorescent heteroleptic [Ir(C6N)₂(N^N)]⁺complexes, enabling the rapid discovery of novel Ir(III) chromophores for diverse applications including organic light‐emitting diodes and solar fuel cells. The deep learning models utilize graph neural networks and other chemical features in architectures that reflect the inherent structure of the heteroleptic complexes, composed of C^N and N^N ligands, and are thus geared towards efficient training over the dataset. By leveraging experimental emission data, our models reliably predict the full emission spectra of these complexes across various emission profiles, surpassing the accuracy of conventional DFT and correlated wavefunction methods, while simultaneously achieving robustness to the presence of imperfect (noisy, low‐quality) training spectra. We showcase the potential applications for these and related models forin silicoprediction of complexes with tailored emission properties, as well as in “design of experiment” contexts to reduce the synthetic burden of high‐throughput screening. In the latter case, we demonstrate that the models allow us to exploit a limited amount of experimental data to explore a wide range of chemical space, thus leveraging a modest synthetic effort. 

Abstract We present a JWST MIRI medium-resolution spectrometer spectrum (5–27μm) of the Type Ia supernova (SN Ia) SN 2021aefx at +415 days pastB-band maximum. The spectrum, which was obtained during the iron-dominated nebular phase, has been analyzed in combination with previous JWST observations of SN 2021aefx to provide the first JWST time series analysis of an SN Ia. We find that the temporal evolution of the [Coiii] 11.888μm feature directly traces the decay of⁵⁶Co. The spectra, line profiles, and their evolution are analyzed with off-center delayed-detonation models. Best fits were obtained with white dwarf (WD) central densities ofρ_c= 0.9−1.1 × 10⁹g cm⁻³, a WD mass ofM_WD= 1.33–1.35M_⊙, a WD magnetic field of ≈10⁶G, and an off-center deflagration-to-detonation transition at ≈0.5M_⊙seen opposite to the line of sight of the observer (−30°). The inner electron capture core is dominated by energy deposition fromγ-rays, whereas a broader region is dominated by positron deposition, placing SN 2021aefx at +415 days in the transitional phase of the evolution to the positron-dominated regime. The formerly “flat-tilted” profile at 9μm now has a significant contribution from [Niiv], [Feii], and [Feiii] and less from [Ariii], which alters the shape of the feature as positrons mostly excite the low-velocity Ar. Overall, the strength of the stable Ni features in the spectrum is dominated by positron transport rather than the Ni mass. Based on multidimensional models, our analysis is consistent with a single-spot, close-to-central ignition with an indication of a preexisting turbulent velocity field and excludes a multiple-spot, off-center ignition. 

The crystallization of amorphous solids impacts fields ranging from inorganic crystal growth to biophysics. Promoting or inhibiting nanoscale epitaxial crystallization and selecting its final products underpin applications in cryopreservation, semiconductor devices, oxide electronics, quantum electronics, structural and functional ceramics, and advanced glasses. As precursors for crystallization, amorphous solids are distinguished from liquids and gases by the comparatively long relaxation times for perturbations of the mechanical stress and for variations in composition or bonding. These factors allow experimentally controllable parameters to influence crystallization processes and to drive materials toward specific outcomes. For example, amorphous precursors can be employed to form crystalline phases, such as polymorphs of Al 2 O 3 , VO 2 , and other complex oxides, that are not readily accessible via crystallization from a liquid or through vapor-phase epitaxy. Crystallization of amorphous solids can further be guided to produce a desired polymorph, nanoscale shape, microstructure, or orientation of the resulting crystals. These effects enable advances in applications in electronics, magnetic devices, optics, and catalysis. Directions for the future development of the chemical physics of crystallization from amorphous solids can be drawn from the structurally complex and nonequilibrium atomic arrangements in liquids and the atomic-scale structure of liquid–solid interfaces.