Sustainable Materials Research Through Robotic Palletization Enables QSPR Mapping in Hybrid Perovskites

Wang, Tonghui; Li, Ruipeng; Ardekani, Hossein; Serrano-Luján, Lucía; Ramezani, Mahdi; Wilmington, Ryan; Epps, Robert W.; Darabi, Kasra; Guo, Boyu; Sun, Dianjun; Abolhasani, Milad; Gündoğdu, Kenan; Amassian, Aram

doi:10.2139/ssrn.4339783

Cited by 2 publications

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“…Smaller devices consume less power, making them more sustainable and environmentally friendly. [52] In addition, chip-based systems enable mass production processes that can reduce production costs over time. This greater accessibility can enable more extensive technological applications, such as new lighting solutions.…”

Section: On-chip Quantum Photonics: a Promising Platformmentioning

confidence: 99%

Exploring Trends and Opportunities in Quantum‐Enhanced Advanced Photonic Illumination Technologies

Taha,

Addie,

Haider

et al. 2024

Adv Quantum Tech

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The development of quantum‐enabled photonic technologies has opened new avenues for advanced illumination across diverse fields, including sensing, computing, materials, and integration. This review highlights how Quantum‐enhanced sensing and imaging exploit nonclassical correlations to attain unprecedented accuracy in chaotic environments. As well as guaranteeing secure communications, quantum cryptography, protected by physical principles, ensures unbreakable cryptographic key exchange. As quantum computing speed increases exponentially, previously unimplementable uses for classical computers become feasible. On‐chip integration enables the mass production of quantum photonic components for pervasive applications by facilitating miniaturization and scalability. A powerful and flexible platform is produced when classical and quantum systems are combined. Quantum spin liquids and other topological materials can maintain their quantum states while subject to decoherence. Despite challenges with decoherence, production, and commercialization, quantum photonics is an exciting new area of study that promises lighting techniques impossible with conventional optics. To realize this promise, researchers from several fields must work together to solve complex technical problems and decode fundamental physics. Finally, advances in quantum‐enabled photonics have the potential to evolve quantum photonic devices and cutting‐edge imaging methods and usher in a new age of lighting options based on quantum dots.

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Section: On-chip Quantum Photonics: a Promising Platformmentioning

confidence: 99%

Exploring Trends and Opportunities in Quantum‐Enhanced Advanced Photonic Illumination Technologies

Taha,

Addie,

Haider

et al. 2024

Adv Quantum Tech

View full text Add to dashboard Cite

show abstract

“…For example, Wagner et al [7] developed the AMANDA platform to produce and characterize solution-processed thin-film devices for organic photovoltaic applications. Other MAPs have been implemented for the discovery of metal halide perovskite alloys [8], polymer composites for photovoltaics [9,10] and metal nanoparticles [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Evolution-guided Bayesian optimization for constrained multi-objective optimization in self-driving labs

Hippalgaonkar,

Low,

Mekki-Berrada

et al. 2023

Preprint

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The development of automated high-throughput experimental platforms has enabled fast sampling of high-dimensional decision spaces. To reach target properties efficiently, these platforms are increasingly paired with intelligent experimental design. However, current optimizers show limitations in maintaining sufficient exploration/exploitation balance for problems dealing with multiple conflicting objectives and complex constraints. Here, we devised an Evolution-Guided Bayesian Optimization (EGBO) algorithm that integrates selection pressure in parallel with a q-Noisy Expected Hypervolume Improvement (qNEHVI) optimizer; this not only solves for the Pareto Front (PF) efficiently but also achieves better coverage of the PF while limiting sampling in the infeasible space. The algorithm was developed together with a custom self-driving lab for seed-mediated silver nanoparticle synthesis, targeting 3 objectives (1) optical properties, (2) fast reaction, and (3) minimal seed usage alongside complex constraints. We demonstrated that, with appropriate constraint handling, EGBO performance improves upon state-of-the-art qNEHVI. Furthermore, across various synthetic multi-objective problems, EGBO showed significative hypervolume improvement, revealing the synergy between selection pressure and the qNEHVI optimizer. We also demonstrated EGBO’s good coverage of the PF as well as comparatively better ability to propose feasible solutions. We thus propose EGBO as a general framework for efficiently solving constrained multi-objective problems in high-throughput experimentation platforms.

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Sustainable Materials Research Through Robotic Palletization Enables QSPR Mapping in Hybrid Perovskites

Cited by 2 publications

References 0 publications

Exploring Trends and Opportunities in Quantum‐Enhanced Advanced Photonic Illumination Technologies

Exploring Trends and Opportunities in Quantum‐Enhanced Advanced Photonic Illumination Technologies

Evolution-guided Bayesian optimization for constrained multi-objective optimization in self-driving labs

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