Bayesian optimization of the composition of the lanthanide metal–organic framework MIL-103 for white-light emission

Abstract

To realize lanthanide metal-organic frameworks (Ln-MOFs) with white light emission, it is necessary to adjust their RGB composition. We adopted the Bayesian optimization technique to optimize the stoichiometric ratio of...

Multi-fidelity Bayesian optimization of covalent organic frameworks for xenon/krypton separations

“…BO has been deployed for the optimization and discovery of many different materials 12,[23][24][25][26] in the lab or a computer simulation, including nanoporous materials, [27][28][29][30][31] nanoparticles, 32 light emitting diodes, 33 carbon nanotubes, 34 photovoltaics, [35][36][37] additively manufactured structures, 38 polymers, [39][40][41][42][43] thermoelectrics, 44 anti-microbial active surfaces, 45 quantum dots, 46 luminescent materials, 47 catalysts, [48][49][50][51][52] thin lms, 53 solid chemical propellants, 54 alloys, 55 and phase-change memory materials. 56 More, BO has been used to optimize processes to synthesize materials and chemicals [57][58][59][60][61][62][63] or to employ materials for an industrial-scale task.…”

Single-phase white light material and antibiotic detection of lanthanide metal–organic frameworks

“…The luminescence of Ln–MOF was regulated by controlling the amount of different rare earth ions (Eu 3+ , Tb 3+ , La 3+ ) added in the synthesis process. 39 By adding different proportions of rare earth elements, a variety of Ln–MOF with different luminous colors were synthesized, in which Eu 0.015 Tb 0.037 La 0.148 -TCA exhibited quite close white light emission ( λ ex = 365 nm). The actual molar ratio of rare earth ions as measured by ICP was Eu : Tb : La = 0.011 : 0.034 : 0.086.…”

Exploring Metal Nanocluster Catalysts for Ammonia Synthesis Using Informatics Methods: A Concerted Effort of Bayesian Optimization, Swarm Intelligence, and First-Principles Computation

“…We focused on Bayesian optimization (BO) , to achieve the objectives of this study. BO is a powerful machine learning technique that can optimize a black box function with a limited number of evaluations. − In the context of nanocluster catalyst design, BO can be used to efficiently explore the vast space of possible combinations of the type and number of metal atoms constituting a nanocluster and to identify the optimal composition of nanoclusters that maximizes the desired catalytic properties.…”