Tianyu Zhang

East China University of Science and Technology

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Mingyang Sun

Jilin University

Wenfa Xie

State Key Laboratory on Integrated Optoelectronics

Haoran Wang

Jilin University

Kaiwen Song

Jilin University

Xinyu Guo

Jilin University

Yanbin Shao

Jilin University

Letian Zhang

Army Medical University

Yue Wang

Jilin University

Chuandong Dou

Jilin University

Zeyi Li

Jilin University

Cooperative Institutions

Jilin University

112

Chinese Academy of Sciences

Jilin Medical University

State Key Laboratory on Integrated Optoelectronics

Harbin Institute of Technology

Zhejiang University

Ministry of Education of the People's Republic of China

Sun Yat-sen University

University of Electronic Science and Technology of China

University of Chinese Academy of Sciences

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Transparent white organic light-emitting devices with a LiF/Yb:Ag cathode

Optics Letters (2009)

Tianyu Zhang Letian Zhang Wenyu Ji Wenfa Xie

Transparent white organic light-emitting devices with a LiF/Yb:Ag cathode are reported. The device with a structure of indium-tin oxide/ 4,4('),4('') -tris(3-methylphenyl-phenylamino)-tripheny-lamine (40 nm)/N,N(')-bis-(1-naphthyl)- N,N(') -diphenyl- 1,1(')-biph-enyl-4,4(')-diamine (NPB: 7 nm)/rubrene (0.1 nm)/NPB(3 nm)/2,2('),2('')-(1,3,5-phenylene) tris(1-phenyl- 1H- benzimidazole (30 nm)/tris (8-hydroxyquinoline) aluminum (20 nm)/LiF(0.5 nm)/Yb:Ag (15 nm, volume ratio 1:1) shows few differences in luminance and color purity from both sides. For instant, at a driving voltage of 10 V, the luminance and CIE coordinates of 1173/1488 cd/m(2) and (0.3482,0.3596)/(0.3508,0.3352) are obtained from top/bottom sides. CIE coordinates of the device from both sides are voltage independent, and the maximum total electroluminescence efficiencies of the device are 4.6 cd/A.

Rubrene

Indium tin oxide

Chromaticity

10.1364/ol.34.001174

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Citations (13)

Molecular Graph Representation Learning Integrating Large Language Models with Domain-specific Small Models

2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (2024)

Tianyu Zhang Yuxiang Ren Chengbin Hou Hairong Lv Xuegong Zhang

Representation

10.1109/bibm62325.2024.10821952

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Eating disorders among adolescents: The form and mechanism of peer influence

Advances in Psychological Science (2019)

Tianyu Zhang Xiangkui Zhang

性主要表现为神经贪食症(bulimia nervosa, BN)、神经性厌食症(anorexia nervosa

10.3724/sp.j.1042.2019.00657

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Citations (2)

Diradical B/N‐Doped Polycyclic Hydrocarbons

Angewandte Chemie International Edition (2023)

Jiaxiang Guo Zeyi Li Xinyu Tian Tianyu Zhang Yue Wang

Heterocyclic diradicaloids with atom-precise control over open-shell nature are promising materials for organic electronics and spintronics. Herein, we disclose quinoidal π-extension of a B/N-heterocycle for generating B/N-type organic diradicaloids. Two quinoidal π-extended B/N-doped polycyclic hydrocarbons that feature fusion of the B/N-heterocycle motif with the antiaromatic s-indacene or dicyclopenta[b,g]naphthalene core were synthesized. This quinoidal π-extension and B/N-heterocycle leads to their open-shell electronic nature, which stands in contrast to the multiple-resonance effect of conventional B/N-type emitters. These B/N-type diradicaloids have modulated (anti)aromaticity and enhanced diradical characters comparing with the all-carbon analogues, as well as intriguing properties, such as magnetic activities, narrow energy gaps and highly red-shifted absorptions. This study thus opens the new space for both of B/N-doped polycyclic π-systems and heterocyclic diradicaloids.

Diradical

Antiaromaticity

Open shell

10.1002/anie.202217470

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Citations (32)

An Unsupervised Local Outlier Detection Method for Wireless Sensor Networks

International Journal of Advanced Computer Science and Applications (2017)

Tianyu Zhang Qian Zhao Yoshihiro Shin Yukikazu Nakamoto

Recently, wireless sensor networks (WSNs) have provided many applications, which need precise sensing data analysis, in many areas. However, sensing datasets contain outliers sometimes. Although outliers rarely occur, they seriously reduce the precision of the sensing data analysis. In the past few years, many researches focused on outlier detection. However, many of them ignored one factor that WSNs are usually deployed in a dynamic environment that changes with time. Thus, we propose a new method, which is an unsupervised learning method based on mean-shift algorithm, for outlier detection that can be used in a dynamic environment for WSNs. To make our method adapt to a dynamic environment, we define two new distances for outlier detection. Moreover, the simulation shows that our method performed on real sensing dataset has ideal results; it finds outliers with a low false positive rate and has a high recall. For generality, we also test our method on different synthetic datasets.

Generality

10.14569/ijacsa.2017.080850

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Citations (3)

Parse Trees Guided LLM Prompt Compression

arXiv (Cornell University) (2024)

Wenhao Mao Chengbin Hou Tianyu Zhang Xinyu Lin Ke Tang

Offering rich contexts to Large Language Models (LLMs) has shown to boost the performance in various tasks, but the resulting longer prompt would increase the computational cost and might exceed the input limit of LLMs. Recently, some prompt compression methods have been suggested to shorten the length of prompts by using language models to generate shorter prompts or by developing computational models to select important parts of original prompt. The generative compression methods would suffer from issues like hallucination, while the selective compression methods have not involved linguistic rules and overlook the global structure of prompt. To this end, we propose a novel selective compression method called PartPrompt. It first obtains a parse tree for each sentence based on linguistic rules, and calculates local information entropy for each node in a parse tree. These local parse trees are then organized into a global tree according to the hierarchical structure such as the dependency of sentences, paragraphs, and sections. After that, the root-ward propagation and leaf-ward propagation are proposed to adjust node values over the global tree. Finally, a recursive algorithm is developed to prune the global tree based on the adjusted node values. The experiments show that PartPrompt receives the state-of-the-art performance across various datasets, metrics, compression ratios, and target LLMs for inference. The in-depth ablation studies confirm the effectiveness of designs in PartPrompt, and other additional experiments also demonstrate its superiority in terms of the coherence of compressed prompts and in the extreme long prompt scenario.

10.48550/arxiv.2409.15395

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Extracellular Amyloid β-protein (1–42) Oligomers Anchor Brain Cells and Make them inert as an Unconventional Integrin-Coupled Ligand

Cellular and Molecular Neurobiology (2022)

Tianyu Zhang Chuli Song Changxin Zheng Xu Chen Yingjiu Zhang

10.1007/s10571-022-01219-2

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Spiro‐Fused vs 575‐Ringed Boron‐Doped Polycyclic π‐Systems: Selective Synthesis, Reactivity and Properties

Angewandte Chemie International Edition (2024)

Yujia Liu Xinyu Tian Zeyi Li Tianyu Zhang Liuzhong Yuan

Incorporation of heteroatoms and/or non-hexagonal rings into polycyclic aromatic hydrocarbons (PAHs) can alter their intrinsic structures and physical properties. However, it is challenging to construct PAHs featuring boron/carbon composition and non-hexagonal combination. Herein, we disclose the selective synthesis of spiro-type and pentagon/heptagon-containing boron-doped polycyclic π-systems by the Scholl reaction. Two spiro-fused organoboranes 1 and 2 and one 575-ringed boron-doped nanographene 3 were synthesized. The key point is that the boron-edged π-system enabled unexpected spiro-formation via dearomatization, whereas the boron-centered π-system enabled desired 575-ringed π-extension via cyclodehydrogenation. The thus-obtained molecules exhibit the intriguing but fully distinct reactivity, electronic structures and properties, for instance, while 2 may react with Brønsted acid to display reversible chemochromism and further convert into 1, 3 possesses very broad absorption, short excited-state lifetime and no fluorescence nature. As disclosed, the boron atom together with the spirocycle region or 575-ringed structural motif significantly contribute to their characteristic properties. Thus, this study sheds light on control over the Scholl reaction using organoborane π-systems and will promote the exploration of more sophisticated polycyclic π-systems as organic reactive and optical scaffolds.

Heteroatom

Reactivity

Polycyclic aromatic hydrocarbon

10.1002/anie.202422031

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Mathematical Methods and Algorithms for Improving Near-Infrared Tunable Diode-Laser Absorption Spectroscopy

Sensors (2018)

Tianyu Zhang Jiawen Kang Dezhuang Meng Hongwei Wang Zhengming Mu

Tunable diode laser absorption spectroscopy technology (TDLAS) has been widely applied in gaseous component analysis based on gas molecular absorption spectroscopy. When dealing with molecular absorption signals, the desired signal is usually interfered by various noises from electronic components and optical paths. This paper introduces TDLAS-specific signal processing issues and summarizes effective algorithms so solve these.

SIGNAL (programming language)

10.3390/s18124295

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Citations (37)

Knowledge-Based Multiple Relations Modeling for Traffic Forecasting

IEEE Transactions on Intelligent Transportation Systems (2024)

Xiao Han Xinfeng Zhang Yiling Wu Zhenduo Zhang Tianyu Zhang

Traffic forecasting is a critical task in intelligent transportation systems. In recent years, lots of methods have been proposed and achieved significant progress in modeling highly nonlinear and complex spatiotemporal pattern for traffic forecasting. However, most methods neglect the specific internal and external factors of the traffic system, such as the road connections, buildings surrounding each place, transfer stations, etc. The main challenges of utilizing the diverse knowledge from internal and external factors are to represent and fuse the impact of various factors. Few works use distance-based adjacency matrices to represent factors and the element-wise multiplication to fuse them, which may lead to even worse performances. In this paper, we propose to utilize knowledge graph to represent traffic system factors and design a novel neural network to exploit them for traffic foresting. First, we model the relations between factors and traffic conditions from the perspective of the knowledge graph and express them as unified triplets. Then, we generate multi-hop path features with embeddings learned from the knowledge representation model and multi-hop paths searched from the graph structure. Next, we present a knowledge-based multi-hop network (KMHNet) that uses an attention-based module to learn the correlation from multi-hop path features. Finally, to evaluate the performance of the proposed method, we build two real-world datasets both containing a traffic condition sub-dataset and a traffic knowledge graph. Experiments on two datasets demonstrate that our proposed KMHNet outperforms eight well-known methods. The code is publicly available at https://github.com/2448845600/KMHNet.

10.1109/tits.2024.3373123

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