Omar Allam

Ruddlesden–Popper perovskites (RPPs) feature enhanced stability compared to their bulk counterparts and attract attention for potential applications in light-emitting diodes (LEDs). However, to date, blue-emitting RPPs rely on halide compositional tuning, resulting in spectral shifts due to halide segregation under photo-/electrical-excitation. Here, efficient blue-emitting materials with single-halide RPPs using organic spacer engineering are reported. Experimental and computational results show that the (110)-oriented thin films exhibit larger bandgap and enhanced stability regardless of the choice of spacers, relative to the (100)-oriented RPPs. The correlation between the lattice structures and optoelectronic properties reveals that this new class of RPPs exhibits sky-blue emission at 483 nm with a quantum efficiency of ≈62%. Spearman correlation between the steric size of the spacers and the bandgap is estimated to be 92%, showing that the steric effect is crucial influencers. The protocol and strategy established in this study can be exploited to develop blue perovskite LEDs.

Organic materials with redox-active oxygen functional groups are of great interest as electrode materials for alkali-ion storage due to their earth-abundant constituents, structural tunability, and enhanced energy storage properties. Herein, a hybrid carbon framework consisting of reduced graphene oxide and oxygen functionalized carbon quantum dots (CQDs) is developed via the one-pot solvothermal reduction method, and a systematic study is undertaken to investigate its redox mechanism and electrochemical properties with Li-, Na-, and K-ions. Due to the incorporation of CQDs, the hybrid cathode delivers consistent improvements in charge storage performance for the alkali-ions and impressive reversible capacity (257 mAh g−1 at 50 mA g−1), rate capability (111 mAh g−1 at 1 A g−1), and cycling stability (79% retention after 10 000 cycles) with Li-ion. Furthermore, density functional theory calculations uncover the CQD structure-electrochemical reactivity trends for different alkali-ion. The results provide important insights into adopting CQD species for optimal alkali-ion storage.

Practical lithium–oxygen batteries require a shift from pure O2 to air. CO2 traces, however, fundamentally alter the O2 electrochemistry towards Li2CO3 formation via peroxocarbonate intermediates in highly-solvating electrolytes e.g., tetraethylene glycol dimethyl ether (G4). Here, we reveal that operating temperatures (0∼70 °C) critically dictate Li2CO3-associated cell overcharges (4.60∼3.77 V), by determining temperature-dependent reaction kinetics and evolving species mobility, as analogously witnessed under pure O2-conditions. Against what is observed for Li2O2 formation in the Li–O2 cell, however, cell temperatures do not govern the crystallinity of the Li2CO3 discharge product. In agreement with experimental observations, comprehensive density functional theory calculations also uncover the effect of the temperature on the Li2CO3 precipitation mechanism and shed light on the dwindling stabilization of metastable peroxocarbonate intermediates during discharge at increasing cycling temperatures. On the other hand, during extended operation, the temperature-dependent reactants mobility in the viscous G4 electrolyte and remnant Li-deficient carbonate surfaces from precedent recharge steps play equally prominent roles on the Li2CO3 precipitation mechanism and the resulting cell capacity. Our study highlights the complexity of practical Li–O2 cells with temperature-dependent performances.

In recent years, metal halide perovskites (MHPs) have attracted attention as semiconductors that achieve desirable properties for optoelectronic devices. However, two challenges—instability and the regulated nature of Pb —remain to be addressed with commercial applications. The development of Pb-free halide double perovskite (HDP) materials has gained interest and attention as a result. This family offers potential in the field of optoelectronic devices through flexible material designs and compositional adjustments. We highlight recent progress and development in halide double perovskites and encompass the synthesis, optoelectronic properties, and engineering of the electronic structures of these materials along with their applications in optoelectronic devices. Computational and data-driven statistical methods can also be used to explore mechanisms and discover promising candidate double perovskites.

In this study, we utilize a density functional theory-machine learning framework to develop a high-throughput screening method for designing new molecular electrode materials. For this purpose, a density functional theory modeling approach is employed to predict basic quantum mechanical quantities such as redox potentials, and electronic properties such as electron affinity, highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO), for a selected set of organic materials. Both the electronic properties and structural information, such as the numbers of oxygen atoms, lithium atoms, boron atoms, carbon atoms, hydrogen atoms, and aromatic rings, are considered as input variables for the machine learning-based prediction of redox potentials. The large-set of input variables are further downsized using a linear correlation analysis to have six core input variables, namely electron affinity, HOMO, LUMO, HOMO–LUMO gap, the number of oxygen atoms and the number of lithium atoms. The artificial neural network trained using the quasi-Newton method demonstrates a capability for accurately estimating the redox potentials. From the contribution analysis, in which the influence of each input on the target are accessed, we highlight that the electron affinity has the highest contribution to redox potential, followed by the number of oxygen atoms, HOMO–LUMO gap, the number of lithium atoms, LUMO, and HOMO, in order.