| 1. |
- Lu, Xin, et al.
(författare)
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A Generic Digital Twin Framework for Collaborative Supply Chain Development
- 2022
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Ingår i: 2022 5th International Conference on Computing and Big Data (ICCBD 2022). - : IEEE. - 9781665457163 - 9781665457156 - 9781665457170 ; , s. 177-181
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Konferensbidrag (refereegranskat)abstract
- Current Supply Chains (SCs) are complex and diverse along with fragile to SC disruptions. This leads urgently needs to develop an intelligent, transparent, collaborative and resilient SC system to cope with unexpected SC disruptions. Digital twin (DT) is one of the most promising solutions to develop smart SCs that has been extensively studied recent years. However, SCDT paradigm is still at an early stage. This paper presents a generic and modularized five layers DT framework to provide a flexible and collaborative solution, which can be compatible with different DT systems in various SCs. The feasibility of the proposed framework is validated through a practical implementation in a distributed eyewear industry.
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| 2. |
- Zhang, Liang, et al.
(författare)
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Deep Learning for Additive Screening in Perovskite Light-Emitting Diodes
- 2022
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Ingår i: Angewandte Chemie International Edition. - : WILEY-V C H VERLAG GMBH. - 1433-7851 .- 1521-3773. ; 61:37
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Tidskriftsartikel (refereegranskat)abstract
- Additive engineering with organic molecules is of critical importance for achieving high-performance perovskite optoelectronic devices. However, experimentally finding suitable additives is costly and time consuming, while conventional machine learning (ML) is difficult to predict accurately due to the limited experimental data available in this relatively new field. Here, we demonstrate a deep learning method that can predict the effectiveness of additives in perovskite light-emitting diodes (PeLEDs) with a high accuracy up to 96 % by using a small dataset of 132 molecules. This model can maximize the information of the molecules and significantly mitigate the duplicated problem that usually happened with previous models in ML for molecular screening. Very high efficiency PeLEDs with a peak external quantum efficiency up to 22.7 % can be achieved by using the predicated additive. Our work opens a new avenue for further boosting the performance of perovskite optoelectronic devices.
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| 3. |
- Zou, Yatao, et al.
(författare)
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Manipulating crystallization dynamics through chelating molecules for bright perovskite emitters
- 2021
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 12:1
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Tidskriftsartikel (refereegranskat)abstract
- Molecular additives are widely utilized to minimize non-radiative recombination in metal halide perovskite emitters due to their passivation effects from chemical bonds with ionic defects. However, a general and puzzling observation that can hardly be rationalized by passivation alone is that most of the molecular additives enabling high-efficiency perovskite light-emitting diodes (PeLEDs) are chelating (multidentate) molecules, while their respective monodentate counterparts receive limited attention. Here, we reveal the largely ignored yet critical role of the chelate effect on governing crystallization dynamics of perovskite emitters and mitigating trap-mediated non-radiative losses. Specifically, we discover that the chelate effect enhances lead-additive coordination affinity, enabling the formation of thermodynamically stable intermediate phases and inhibiting halide coordination-driven perovskite nucleation. The retarded perovskite nucleation and crystal growth are key to high crystal quality and thus efficient electroluminescence. Our work elucidates the full effects of molecular additives on PeLEDs by uncovering the chelate effect as an important feature within perovskite crystallization. As such, we open new prospects for the rationalized screening of highly effective molecular additives.
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| 4. |
- Zou, Yatao, et al.
(författare)
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Thermal-induced interface degradation in perovskite light-emitting diodes
- 2020
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Ingår i: Journal of Materials Chemistry C. - : ROYAL SOC CHEMISTRY. - 2050-7526 .- 2050-7534. ; 8:43, s. 15079-15085
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Tidskriftsartikel (refereegranskat)abstract
- Perovskite light-emitting diodes (PeLEDs) have experienced rapid improvements in device efficiency during the last several years. However, the operational instability of PeLEDs remains a key barrier hindering their practical applications. A fundamental understanding of the degradation mechanism is still lacking but will be important to seek ways to mitigate these unwanted processes. In this work, through comprehensive characterizations of the perovskite emitters and the interfacial contacts, we figure out that Joule heating induced interface degradation is one of the dominant factors affecting the operational stability of PeLEDs. We investigate the interfacial contacts of PeLEDs based on a commonly used device structure, with an organic electron transport layer of 1,3,5-tris(N-phenylbenzimiazole-2-yl)benzene (TPBi), and observe obvious photoluminescence quenching of the perovskite layer after device operation. Detailed characterizations of the interlayers and the interfacial contacts reveal that photoluminescence quenching is mainly due to the element inter-diffusion at the interface induced by the morphological evolution of the TPBi layers under Joule heating during the operation of PeLEDs. Our work provides direct insights into the degradation pathways and highlights the importance of exploring intrinsically stable interlayers as well as interfacial contacts beyond the state-of-the-art to further boost the operational stability of PeLEDs.
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| 5. |
- Boyko, Andrey A., et al.
(författare)
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High-energy, narrowband, non-resonant PPKTP optical parametric oscillator
- 2022
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Ingår i: Nonlinear Frequency Generation and Conversion. - : SPIE - International Society for Optical Engineering.
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Konferensbidrag (refereegranskat)abstract
- We present a narrowband, non-resonant optical parametric oscillator based on 5-mm thick Rb-doped periodically-poled KTiOPO4 (PPKTP) operating in the high-energy/low repetition-rate regime. An uncoated volume Bragg grating (VBG) is employed as one of the cavity mirrors reflecting only the signal whereas the other cavity mirror is reflecting only the idler. Pumping by a Nd:YAG laser at 1.0642 mu m in a double-pass, the signal plus idler output energy reached almost 5 mJ at a repetition rate of 100 Hz corresponding to a conversion efficiency of similar to 26%. Both signal and idler are narrowband with full width at half maximum (FWHM) of 0.5 nm at 1942 nm and 0.76 nm at 2355 nm, respectively.
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| 6. |
- Chen, Weidong, et al.
(författare)
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Narrowband BaGa2GeSe6 Optical Parametric Oscillator Pumped in an Intracavity Cascade Configuration
- 2023
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Ingår i: Proceedings - Optica Nonlinear Optics Topical Meeting 2023, NLO 2023. - : Optical Society of America.
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Konferensbidrag (refereegranskat)abstract
- We present a tunable (6.62-11.34 µm), singly-resonant, cascade optical parametric oscillator with intracavity pumping of BaGa2GeSe6 in the second stage and spectral narrowing realized by a Volume Bragg Grating, providing millijoule output at 100 Hz.
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| 7. |
- Chen, Weidong, et al.
(författare)
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Narrowband, intracavity-pumped, type-II BaGa2GeSe6 optical parametric oscillator
- 2024
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Ingår i: Optics Express. - : Optica Publishing Group. - 1094-4087. ; 31:2, s. 1728-1735
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Tidskriftsartikel (refereegranskat)abstract
- We present a tunable (6.62-11.34 µm), singly-resonant, cascade optical parametric oscillator with intracavity pumping of BaGa2GeSe6 in the second stage and spectral narrowing realized by a Volume Bragg Grating acting on the signal wave of the first stage which serves as a pump for the second stage. The maximum energy achieved near 8 µm in the narrowband regime is 1.1 mJ at 100 Hz (spectral width: ∼20 cm−1, pulse duration: ∼7 ns). The overall conversion efficiency from 1 to 8 µm for broadband and narrowband operation is 4.0% and 3.1%, respectively, corresponding to quantum efficiencies of 31% and 23%.
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| 8. |
- Hu, Kaixiong, et al.
(författare)
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CNN-BiLSTM enabled prediction on molten pool width for thin-walled part fabrication using Laser Directed Energy Deposition
- 2022
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Ingår i: JOURNAL OF MANUFACTURING PROCESSES. - : Elsevier BV. - 1526-6125. ; 78, s. 32-45
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Tidskriftsartikel (refereegranskat)abstract
- Laser Directed Energy Deposition (LDED) is a promising metal Additive Manufacturing (AM) technology capable of fabricating thin-walled parts to support some high-value applications. Accurate and efficient prediction on the molten pool width is critical to support in-situ control of LDED for part quality assurance. Nevertheless, owing to the intricate physical mechanisms of the process, it is challenging to designing an effective approach to accomplish the prediction target. To tackle the issue, in this research, a new data model-driven predictive approach, which is enabled by a hybrid machine learning model namely CNN-BiLSTM, is presented. High prediction accuracy and efficiency are achievable through innovative measures in the research, that is, (i) the CNN-BiLSTM model is designed and configured by addressing the characteristics of the LDED process; (ii) process parameters related to the deposition and heat accumulation phenomena during the LDED process are extensively considered to strengthen the prediction accuracy. Experiments for thin-walled part fabrication were conducted to validate and benchmark the approach. In average, 4.286% of the mean absolute percentage error (MAPE) was acquired, and the prediction time took by the approach was only 0.04% of that by a finite element analysis (FEA) approach. Compared to the LSTM model, the BiLSTM model and the CNN-LSTM model, MAPEs of the CNN-BiLSTM model were improved by 27.0%, 17.3% and 12.6%, respectively. It demonstrates that the approach is competent in producing good-quality thin-walled parts using the LDED process.
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| 9. |
- Huang, Zhiwen, et al.
(författare)
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Cross-domain tool wear condition monitoring via residual attention hybrid adaptation network
- 2024
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Ingår i: Journal of manufacturing systems. - : Elsevier BV. - 0278-6125 .- 1878-6642. ; 72, s. 406-423
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Tidskriftsartikel (refereegranskat)abstract
- Intelligent models for tool wear condition monitoring (TWCM) have been extensively researched. However, in industrial scenarios, limited acquired monitoring signals and variations of machining parameters lead to insufficient training samples and data distribution shifts for the models. To address the issues, this research presents a novel residual attention hybrid adaptation network (RAHAN) model based on a residual attention network (ResAttNet) and a hybrid adaptation strategy. In the RAHAN model, by integrating a channel attention mechanism and deep residual modules, ResAttNet is designed as a feature extractor to acquire features from monitoring signals for tool wear conditions. Embedding subdomain adaptation into a condition recognizer while establishing separate adversarial learning in a domain obfuscator, the hybrid adaptation strategy is developed to eliminate global distribution shifts and align local distributions of each tool wear phase simultaneously. Six migration tasks under a laboratory and two factory machining platforms were conducted to evaluate the effectiveness of the RAHAN model. Compared with a baseline model, four ablation models, and six state-of-the-art transfer learning models, the RAHAN model achieved the highest average accuracy of 92.70% on six migration tasks. Furthermore, the RAHAN model shows clearer feature representations of each tool wear condition than other compared models. The comparative results demonstrate that the RAHAN model has superior transferability and therefore can be considered as a good potential solution to support cross-domain TWCM under different machining processes.
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| 10. |
- Luo, Xiyu, et al.
(författare)
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Effects of local compositional heterogeneity in mixed halide perovskites on blue electroluminescence
- 2024
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Ingår i: Matter. - 2590-2393. ; 7:3, s. 1054-1070
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Tidskriftsartikel (refereegranskat)abstract
- Compositional heterogeneity is commonly observed in mixed bromide/iodide perovskite photoabsorbers, typically with minimal effects on charge carrier recombination and photovoltaic performance. Consistently, it has so far received very limited attention in bromide/chloride-mixed perovskites, which hold particular significance for blue light-emitting diodes. Here, we uncover that even a minor degree of localized halide heterogeneity leads to severe non-radiative losses in mixed bromide/chloride blue perovskite emitters, presenting a stark contrast to general observations in photovoltaics. We not only provide a visualization of the heterogeneity landscape spanning from micro-to sub-microscale but also identify that this issue mainly arises from the initially formed chloride-rich clusters during perovskite nucleation. Our work sheds light on a long-term neglected factor impeding the advancement of blue light-emitting diodes using mixed halide perovskites and provides a practical strategy to mitigate this issue.
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