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Stable, deep blue tandem phosphorescent organic light-emitting diode enabled by the double-sided polariton-enhanced Purcell effect

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Nature Photonics 2025年第6期19卷 607-614页

作者： Zhao, Haonan Arneson, Claire E. Forrest, Stephen R. Department of Physics University of Michigan Ann ArborMI United States Department of Electrical Engineering and Computer Science University of Michigan Ann ArborMI United States Department of Materials Science and Engineering University of Michigan Ann ArborMI United States

Blue phosphorescent organic light-emitting diodes (PHOLEDs) are highly efficient, although their short operational lifetimes have limited their commercial acceptance in displays and lighting. A high density of energetic triplet excitons accumulates in the emission layer that eventually annihilate, leading to molecular degradation. Here we report long operational lifetime, efficient and deep blue tandem PHOLEDs using the polariton-enhanced Purcell (PEP) effect at both the diode cathode and anode. The Pt- and Ir-complex-based bottom-emitting tandem PEP-PHOLEDs show a tenfold increase in lifetime and colour saturation compared with their analogous single-junction PHOLEDs. Particularly, the Pt-complex-based tandem PEP-PHOLED on flat glass substrates has lifetimes of LT90 = 830 ± 30 h and 1,800 ± 100 h (LT90 = the time to reach 90% of the initial luminance of 500 cd m−2), and forward-viewing external quantum efficiencies of 36.8 ± 0.5% or 56.0 ± 1.0% without or with substrate light extraction, respectively. The lifetime enhancement is equivalent to 250 times that of conventional single-junction Ir-based PHOLED lifetimes with similar blue chromaticity coordinates. The tandem PEP-PHOLED has chromaticity coordinates of CIExy = (0.14, 0.12) and a marginally perceptible colour shift with viewing angle up to ±75°. The double-sided PEP effect is readily integrated with other established lifetime-extending technologies, allowing for a multiplicative increase in lifetime. To our knowledge, this is the first demonstration of a deep blue PHOLED that shows stability comparable to green PHOLEDs, accelerating the use of the deep blue phosphorescent emitters in power-efficient displays and lighting. © The Author(s), under exclusive licence to Springer Nature Limited 2025.

关键词： Organic light emitting diodes (OLED)

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Phase-Field Model of Electronic Antidoping

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Physical Review Letters 2024年第25期132卷 256502-256502页

作者： Yin Shi Guo-Dong Zhao Ismaila Dabo Shriram Ramanathan Long-Qing Chen Department of Materials Science and Engineering Department of Electrical and Computer Engineering

Charge carrier doping usually reduces the resistance of a semiconductor or insulator, but was recently found to dramatically enhance the resistance in certain series of materials. This remarkable antidoping effect has been leveraged to realize synaptic memory trees in nanoscale hydrogenated perovskite nickelates, opening a new direction for neuromorphic computing. To understand these phenomena, we formulate a physical phase-field model of the antidoping effect based on its microscopic mechanism and simulate the voltage-driven resistance change in the prototypical system of hydrogenated perovskite nickelates. Remarkably, the simulations using this model, containing only one adjustable parameter whose magnitude is justified by first-principles calculations, quantitatively reproduce the experimentally observed treelike resistance states, which are shown unambiguously to arise from proton redistribution-induced local band gap enhancement and carrier blockage. Our work lays the foundation for modeling the antidoping phenomenon in strongly correlated materials at the mesoscale, which can provide guidance to the design of novel antidoping-physics-based devices.

关键词： Doping effects Neural basis of learning & memory Strongly correlated systems Phase-field modeling

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Highly efficient ternary organic solar cells with excellent open-circuit voltage and fill factor via precisely tuning molecular stacking and morphology

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science China Chemistry 2024年第3期67卷 963-972页

作者： Dinghong Sun Zhenyu Chen Jianfeng Zhang Wei Song Jingyu Shi Jintao Zhu Yuanyuan Meng Fei Jin Shuncheng Yang Ziyi Ge Faculty of Electrical Engineering and Computer Science Ningbo UniversityNingbo 315211China Faculty of Material Science and Chemical Engineering Ningbo UniversityNingbo 315211China Zhejiang Provincial Engineering Research Center of Energy Optoelectronic Materials and Devices Ningbo Institute of Materials Technology&EngineeringChinese Academy of SciencesNingbo 315201China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of Sciences Beijing 100049China Department of Chemical and Environmental Engineering University of Nottingham NingboNingbo 315100China

The micro-morphology and molecular stacking play a key role in determining the charge transport process and nonradiative energy loss, thus impacting the performances of organic solar cells(OSCs). To address this issue, a non-fullerene acceptor PhC6-IC-F with alkylbenzene side-chain, possessing optimized molecular stacking, complementary absorption spectra and forming a cascade energy level alignment in the PM6:BTP-eC9 blend, is introduced as guest acceptor to improve efficiency of ternary OSCs. The bulky phenyl in the side-chain can regulate crystallinity and optimizing phase separation between receptors in ternary blend films, resulting in the optimal phase separations in the ternary films. As a result, high efficiencies of 18.33% as photovoltaic layer are obtained for PhC6-IC-F-based ternary devices with excellent fill factor(FF) of 78.92%. Impressively, the ternary system produces a significantly improved open circuit voltage(V_(oc)) of 0.857 V compared with the binary device,contributing to the reduced density of trap states and suppressed non-radiative recombination result in lower energy loss. This work demonstrates an effective approach for adjusting the aggregation, molecular packing and fine phase separation morphology to increase V_(oc) and FF, paving the way toward high-efficiency OSCs.

关键词： alkylbenzene side-chain morphology regulation ternary blends organic solar cells

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Crafting chirality in three dimensions via a novel fabrication technique for bound states in the continuum metasurfaces

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Light(science & Applications) 2024年第3期13卷 390-392页

作者： Zaid Haddadin Anna My Nguyen Lisa V.Poulikakos Department of Electrical&Computer Engineering University of California San DiegoLa JollaCAUSA Department of Mechanical&Aerospace Engineering University of California San DiegoLa JollaCAUSA Program of Materials Science&Engineering University of California San DiegoLa JollaCAUSA

An additional deposition step was added to a multi-step electron beam lithographic fabrication process to unlock the height dimension as an accessible parameter for resonators comprising unit cells of quasi-bound stat... 详细信息

关键词： dimensions dimension intrinsic

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Trade Ease with Machine Learning and AWS

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IEEE Access 2023年 11卷 25893-25905页

作者： Teja, Kamurthi Ravi Liu, Chuan-Ming National Taipei University of Technology International Program of Electrical Engineering and Computer Science Taipei10608 Taiwan National Taipei University of Technology Department of Computer Science and Information Engineering Taipei10608 Taiwan

Global trading is undergoing significant changes, necessitating modifications to the trading strategies. This study presents a newly developed cloud-based trading strategy that uses Amazon Web Services (AWS), machine learning (ML), and data science to automate trading tasks. The study begins by creating a machine learning trading strategy using a customized deep neural network (DNN). The strategy was then tested using a trading station before deployment on a cloud machine. The execution of the strategy resulted in a total profit of 42.74526 USD, with a test accuracy score of 87.45% and a training accuracy score of 89.15% over 6047 epochs. The roadmap provides a step-by-step overview of the entire process from strategy development to execution. In addition, this study offers insights into related issues and solutions that can enhance the effectiveness of trading strategies. Overall, this study contributes significantly to the field of cloud-based trading strategies and opens avenues for future research. © 2013 IEEE.

关键词： Deep neural networks

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RUL Estimation for Power Electronic Devices Using RNNs

RUL Estimation for Power Electronic Devices Using RNNs

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2024 Prognostics and System Health Management Conference, PHM 2024

作者： Cai, Congrui Lu, Zhonghai School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Embedded Systems Master Program Sweden School of Electrical Engineering and Computer Science Department of Electrical Engineering KTH Royal Institute of Technology Sweden

ISBN: (纸本)9798350360585

Recurrent Neural Networks (RNNs) are commonly used in data-driven approaches to estimate the Remaining Useful Lifetime (RUL) of power electronic devices. RNNs are preferred because their intrinsic feedback mechanisms are better suited to model time-series data. However, the impact of RNN complexity on estimation accuracy is rarely discussed in the literature. This issue is important because choosing a lower-complexity model that delivers the same or similar performance as a higher-complexity model can increase implementation efficiency. In the paper, we use three RNN models, namely, the vanilla version, LSTM (Long Short Term Memory) and GRU (Gated Recurrent Unit) to conduct RUL estimation for power electronic devices. We use two accelerated aging datasets, one dataset targeting the package failure of MOSFETs, and the other dataset targeting package failure of power diodes. Our study shows that a lower-complexity RNN does not necessarily deliver a lower performance. Similarly, a higher-complexity model does not assure a higher performance. As such, our work highlights the importance of selecting a proper neural network for RUL estimation not biased towards complex models. This is especially useful and important for implementing such RUL estimation techniques in embedded resource-constrained and speed-limited computins platforms. © 2024 IEEE.

关键词： Long short-term memory

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Magnetic tunnel junctions featuring the topological Weyl semimetal Co2MnGa

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Physical Review Applied 2024年第4期22卷 044024页

作者： Zhiping He Chung-Tao Chou Eugene Park Alexandre C. Foucher Brooke C. McGoldrick Qiuyuan Wang Justin T. Hou Luqiao Liu Department of Electrical Engineering and Computer Science Department of Physics Department of Materials Science and Engineering

Magnetic Weyl semimetals are promising materials for spintronic applications due to their unique properties in bulk and surface topological states and the rich interplay between band topology and magnetism. While various nontraditional magneto-electrical effects have been studied in magnetic Weyl semimetals, transport properties related to spin-polarized tunneling from these materials remain less explored. In this work, we developed fully epitaxial magnetic tunnel junctions (MTJs) based on a ferromagnetic Weyl semimetal Co2MnGa. By growing Co2MnGa films under different conditions, we fabricated a series of MTJs possessing different degrees of order in the semimetal electrodes and compared their tunneling magnetoresistance (TMR). We find that the TMR becomes enhanced with the improvement of the chemical ordering of Co2MnGa. Our results reveal the relationship between the spin tunneling in MTJs and the chemical order of the Co2MnGa electrode and provide insights on further enhancing TMR via semimetal engineering.

关键词： Spintronics Tunneling magnetoresistance Ferromagnets Heusler alloy Magnetic tunnel junctions Single crystal materials Weyl semimetal Epitaxy

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Excitonic Shockley-Read-Hall recombination in organic semiconductors

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Physical Review Applied 2024年第6期21卷 064019-064019页

作者： Noel C. Giebink Stephen R. Forrest Department of Electrical Engineering and Computer Science and Department of Physics Department of Materials Science and Engineering

Trap-mediated recombination influences the performance of a wide range of electronic devices. The well-known Shockley-Read-Hall (SRH) expression for inorganic semiconductors is often invoked to describe the recombination rate in organic materials, although without a clear understanding of how its parameters relate to the underlying material properties or how it should be modified to account for the finite lifetime of exciton intermediates in, for example, the doped emissive layer of an organic light-emitting diode (OLED). Here, we formalize SRH recombination for organic semiconductors based on diffusive trapping and Langevin recombination. We show that including the exciton state suppresses the recombination rate in host-guest systems with type II energy level alignment whenever the interfacial gap between the host and guest molecular orbitals is comparable to the exciton energy. These results quantify the balance between bimolecular and trap-mediated recombination in doped OLED emissive layers, and indicate that devices with type II host-guest pairings can, in principle, beat the thermodynamic limit of their neat guest counterparts.

关键词： Carrier generation & recombination Organic LEDs Organic semiconductors Semiconductors materials modeling

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Dynamical phase-field model of cavity electromagnonic systems

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npj Computational materials 2024年第1期10卷 1263-1273页

作者： Shihao Zhuang Yujie Zhu Changchun Zhong Liang Jiang Xufeng Zhang Jia-Mian Hu Department of Materials Science and Engineering University of Wisconsin-MadisonMadisonWI53706USA Pritzker School of Molecular Engineering The University of ChicagoChicagoIL60637USA Department of Electrical and Computer Engineering Northeastern UniversityBostonMA02115USA Department of Physics Northeastern UniversityBostonMA02115USA

Cavity electromagnonic system,which simultaneously consists of cavities for photons,magnons(quanta of spin waves),and acoustic phonons,provides an exciting platform to achieve coherent energy transduction among different physical systems down to single quantum *** we report a dynamical phase-field model that allows simulating the coupled dynamics of the electromagnetic waves,magnetization,and strain in 3D multiphase *** examples of application,we computationally demonstrate the excitation of hybrid magnon-photon modes(magnon polaritons),Floquet-induced magnonic Aulter-Townes splitting,dynamical energy exchange(Rabi oscillation)and relative phase control(Ramsey interference)between the two magnon polariton *** simulation results are consistent with analytical calculations based on Floquet Hamiltonian *** are also performed to design a cavity electro-magno-mechanical system that enables the triple phononmagnon-photon resonance,where the resonant excitation of a chiral,fundamental(n=1)transverse acoustic phonon mode by magnon polaritons is *** the capability to predict coupling strength,dissipation rates,and temporal evolution of photon/magnon/phonon mode profiles using fundamental materials parameters as the inputs,the present dynamical phase-fieldmodel represents a valuable computational tool to guide the fabrication of the cavity electromagnonic system and the design of operating conditions for applications in quantum sensing,transduction,and communication.

关键词： theory phonon phase

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Compact Model Build Upon Dynamic Weighting Artificial Neural Network Approach for Complementary Field Effect Transistors

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IEEE Transactions on Electron Devices 2024年第1期71卷 246-253页

作者： Butola, Rajat Li, Yiming Kola, Sekhar Reddy National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Hsinchu300093 Taiwan Institute of Pioneer Semiconductor Innovation The Institute of Artificial Intelligence Innovation National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program The Institute of Communications Engineering the Institute of Biomedical Engineering Department of Electronics and Electrical Engineering Hsinchu300093 Taiwan

In this work, a dynamic weighting-artificial neural network (DW-ANN) methodology is presented for quick and automated compact model (CM) generation. It takes advantage of both TCAD simulations for high accuracy and SPICE simulations for cost-effectiveness. This methodology is developed for gate-all-around (GAA) silicon (Si) nanosheet (NS) complementary field effect transistor (CFET), a potential candidate for future CMOS technology due to its innate properties. The critical process variation (PV) sources that severely degrade the CFET performance are estimated using DW-ANN. It reduces the computation cost and predicts the effects of PV sources with less than 1% error. Furthermore, a compact DW-ANN-based Verilog-A model has been developed that captures the dc as well as transient behavior accurately for circuit-level analysis. CFET-based circuits such as inverter, 6T-static random access memory (SRAM), and ring oscillator (RO) are characterized and implemented using DW-ANN-based CM. The overall average error of the model is reported as less than 2%. Therefore, the proposed device and circuit modeling approach provides a feasible solution for the rapid compact modeling of new emerging devices with good convergence and high accuracy. © 1963-2012 IEEE.

关键词： Neural networks

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