Metaheuristics-Assisted Combinatorial Screening of Eu2+-Doped Ca-Sr-Ba-Li-Mg-Al-Si-Ge-N Compositional Space in Search of a Narrow-Band Green Emitting Phosphor and Density Functional Theory Calculations

Argyrodite configuration determination for DFT and AIMD calculations using an integrated optimization strategy

When constructing a partially occupied model structure for use in density functional theory (DFT) and ab initio molecular dynamics (AIMD) calculations, the selection of appropriate configurations has been a vexing issue. Random sampling and the ensuing low-Coulomb-energy entry selection have been routine. Here, we report a more efficient way of selecting low-Coulomb-energy configurations for a representative solid electrolyte, Li₆PS₅Cl. Metaheuristics (genetic algorithm, particle swarm optimization, cuckoo search, and harmony search), Bayesian optimization, and modified deep Q-learning are utilized to search the large configurational space. Ten configuration candidates that exhibit relatively low Coulomb energy values and thereby lead to more convincing DFT and AIMD calculation results are pinpointed along with computational cost savings by the assistance of the above-described optimization algorithms, which constitute an integrated optimization strategy. Consequently, the integrated optimization strategy outperforms the conventional random sampling-based selection strategy.

When constructing a partially occupied model structure for use in density functional theory (DFT) and ab initio molecular dynamics (AIMD) calculations, the selection of appropriate configurations has been a vexing issue. We suggest a reasonable strategy to sort out this issue.

A microfluidic-enabled combinatorial formulation and integrated inkjet printing platform for evaluating functionally graded material blends

Sample library preparation is a central step in the process of evaluating materials with the general aim of efficient library formulation while minimizing resource consumption. We demonstrate here the first implementation of a microfluidic-enabled thin film sample library formulation platform with integrated inkjet printing capability for directly patterning these libraries with reduced material wastage. System development and general performance screening protocol for these patterned thin films are described. We study the combinatorial formulation capabilities of this system by focusing on some practical case studies for probing the electrical conductivity in organic, biocompatible and electroactive polymer/additive (PEDOT:PSS/DMSO and PEDOT:PSS/EG) blends. Functionally-graded thin film libraries are prepared by mixing ink components and directly dispensing the processed blends into programmed geometries using the integrated platform. Electrical and morphological characterization of these printed thin film libraries is conducted to validate the formulation efficacy of the platform. Interrogating these printed libraries, we were able to iteratively identify the location of conductivity maxima for the studied blends and corroborate the morphological basis of this enhancement with established theories.

Bayesian optimization for goal-oriented multi-objective inverse material design

Bayesian optimization (BO) can accelerate material design requiring time-consuming experiments. However, although most material designs require tuning of multiple properties, the efficiency of multi-objective (MO) BO in time-consuming experimental material design remains unclear, due to the complexity of handling multiple objectives. This study introduces MO BO method that efficiently achieves predefined goals and shows that by focusing on achieving the goals, BO can efficiently accelerate realistic MO design problems with small efforts. Benchmarks showed that the proposed BO method dramatically reduced the number of experiments needed to achieve goals relative to a baseline method. Virtual MO inverse design experiments with realistic material design problems were also performed, during which the proposed method could achieve goals within only around ten experiments in average and showed over 1000-fold acceleration relative to the random sampling for the most difficult case. The introduction of goal-oriented BO will precede real-world application of BO.

A rate equation model for the energy transfer mechanism of a novel multi-color-emissive phosphor, Ca1.624Sr0.376Si5O3N6:Eu2+

A novel multi-color-emissive phosphor (Ca_1.624Sr_0.376Si₅O₃N₆:Eu²⁺) and a rate equation model to elucidate the mechanism of energy-transfer leading to broadband emission.

Multichannel Luminescence Properties of Mixed-Valent Eu2+/Eu3+ Coactivated SrAl3BO7 Nanocrystalline Phosphors for Near-UV LEDs

Up to now, orchestrating the coexistence of Eu²⁺ and Eu³⁺ activators in a single host lattice has been an extremely difficult task, especially for the appearance of the characteristic emission of Eu²⁺ and Eu³⁺ in order to generate white light. Nevertheless, here we demonstrate a new Eu²⁺/Eu³⁺ coactivated SrAl₃BO₇ nanocrystalline phosphor with abundant and excellent multichannel luminescence properties. A series of Eu²⁺/Eu³⁺ coactivated SrAl₃BO₇ nanocrystalline phosphors were prepared through a Pechini-type sol-gel method followed by a reduction process. With excitation of UV/NUV light, the prepared SrAl₃BO₇:Eu²⁺,Eu³⁺ phosphors show not only the characteristic f-f transitions of Eu³⁺ ion (⁵D_J → ⁷F_J,J', J, J' = 0-3), but also the 5d → 4f transitions of Eu²⁺ ion with comparable intensity from 400 to 700 nm in the whole visible spectral region. The luminescence color of the SrAl₃BO₇:Eu²⁺,Eu³⁺ phosphor can be tuned from blue, blue-green, white, and orange to orange-red by changing the excitation wavelength, the overall doping concentration of europium ions (Eu²⁺, Eu³⁺), and the relative ratio of Eu²⁺ to Eu³⁺ ions to some extent. A single-phase white-light emission has been realized in SrAl₃BO₇:Eu²⁺,Eu³⁺ phosphor. The obtained SrAl₃BO₇:Eu²⁺,Eu³⁺ phosphor has potential application in the area of NUV white-light-emitting diodes.