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117 results on '"Song, Yiwen"'

1. TDNetGen: Empowering Complex Network Resilience Prediction with Generative Augmentation of Topology and Dynamics

Author

Liu, Chang, Ding, Jingtao, Song, Yiwen, and Li, Yong

Subjects
Computer Science - Artificial Intelligence
Abstract

Predicting the resilience of complex networks, which represents the ability to retain fundamental functionality amidst external perturbations or internal failures, plays a critical role in understanding and improving real-world complex systems. Traditional theoretical approaches grounded in nonlinear dynamical systems rely on prior knowledge of network dynamics. On the other hand, data-driven approaches frequently encounter the challenge of insufficient labeled data, a predicament commonly observed in real-world scenarios. In this paper, we introduce a novel resilience prediction framework for complex networks, designed to tackle this issue through generative data augmentation of network topology and dynamics. The core idea is the strategic utilization of the inherent joint distribution present in unlabeled network data, facilitating the learning process of the resilience predictor by illuminating the relationship between network topology and dynamics. Experiment results on three network datasets demonstrate that our proposed framework TDNetGen can achieve high prediction accuracy up to 85%-95%. Furthermore, the framework still demonstrates a pronounced augmentation capability in extreme low-data regimes, thereby underscoring its utility and robustness in enhancing the prediction of network resilience. We have open-sourced our code in the following link, https://github.com/tsinghua-fib-lab/TDNetGen.

Published
2024
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2. The Llama 3 Herd of Models

Author

Dubey, Abhimanyu, Jauhri, Abhinav, Pandey, Abhinav, Kadian, Abhishek, Al-Dahle, Ahmad, Letman, Aiesha, Mathur, Akhil, Schelten, Alan, Yang, Amy, Fan, Angela, Goyal, Anirudh, Hartshorn, Anthony, Yang, Aobo, Mitra, Archi, Sravankumar, Archie, Korenev, Artem, Hinsvark, Arthur, Rao, Arun, Zhang, Aston, Rodriguez, Aurelien, Gregerson, Austen, Spataru, Ava, Roziere, Baptiste, Biron, Bethany, Tang, Binh, Chern, Bobbie, Caucheteux, Charlotte, Nayak, Chaya, Bi, Chloe, Marra, Chris, McConnell, Chris, Keller, Christian, Touret, Christophe, Wu, Chunyang, Wong, Corinne, Ferrer, Cristian Canton, Nikolaidis, Cyrus, Allonsius, Damien, Song, Daniel, Pintz, Danielle, Livshits, Danny, Esiobu, David, Choudhary, Dhruv, Mahajan, Dhruv, Garcia-Olano, Diego, Perino, Diego, Hupkes, Dieuwke, Lakomkin, Egor, AlBadawy, Ehab, Lobanova, Elina, Dinan, Emily, Smith, Eric Michael, Radenovic, Filip, Zhang, Frank, Synnaeve, Gabriel, Lee, Gabrielle, Anderson, Georgia Lewis, Nail, Graeme, Mialon, Gregoire, Pang, Guan, Cucurell, Guillem, Nguyen, Hailey, Korevaar, Hannah, Xu, Hu, Touvron, Hugo, Zarov, Iliyan, Ibarra, Imanol Arrieta, Kloumann, Isabel, Misra, Ishan, Evtimov, Ivan, Copet, Jade, Lee, Jaewon, Geffert, Jan, Vranes, Jana, Park, Jason, Mahadeokar, Jay, Shah, Jeet, van der Linde, Jelmer, Billock, Jennifer, Hong, Jenny, Lee, Jenya, Fu, Jeremy, Chi, Jianfeng, Huang, Jianyu, Liu, Jiawen, Wang, Jie, Yu, Jiecao, Bitton, Joanna, Spisak, Joe, Park, Jongsoo, Rocca, Joseph, Johnstun, Joshua, Saxe, Joshua, Jia, Junteng, Alwala, Kalyan Vasuden, Upasani, Kartikeya, Plawiak, Kate, Li, Ke, Heafield, Kenneth, Stone, Kevin, El-Arini, Khalid, Iyer, Krithika, Malik, Kshitiz, Chiu, Kuenley, Bhalla, Kunal, Rantala-Yeary, Lauren, van der Maaten, Laurens, Chen, Lawrence, Tan, Liang, Jenkins, Liz, Martin, Louis, Madaan, Lovish, Malo, Lubo, Blecher, Lukas, Landzaat, Lukas, de Oliveira, Luke, Muzzi, Madeline, Pasupuleti, Mahesh, Singh, Mannat, Paluri, Manohar, Kardas, Marcin, Oldham, Mathew, Rita, Mathieu, Pavlova, Maya, Kambadur, Melanie, Lewis, Mike, Si, Min, Singh, Mitesh Kumar, Hassan, Mona, Goyal, Naman, Torabi, Narjes, Bashlykov, Nikolay, Bogoychev, Nikolay, Chatterji, Niladri, Duchenne, Olivier, Çelebi, Onur, Alrassy, Patrick, Zhang, Pengchuan, Li, Pengwei, Vasic, Petar, Weng, Peter, Bhargava, Prajjwal, Dubal, Pratik, Krishnan, Praveen, Koura, Punit Singh, Xu, Puxin, He, Qing, Dong, Qingxiao, Srinivasan, Ragavan, Ganapathy, Raj, Calderer, Ramon, Cabral, Ricardo Silveira, Stojnic, Robert, Raileanu, Roberta, Girdhar, Rohit, Patel, Rohit, Sauvestre, Romain, Polidoro, Ronnie, Sumbaly, Roshan, Taylor, Ross, Silva, Ruan, Hou, Rui, Wang, Rui, Hosseini, Saghar, Chennabasappa, Sahana, Singh, Sanjay, Bell, Sean, Kim, Seohyun Sonia, Edunov, Sergey, Nie, Shaoliang, Narang, Sharan, Raparthy, Sharath, Shen, Sheng, Wan, Shengye, Bhosale, Shruti, Zhang, Shun, Vandenhende, Simon, Batra, Soumya, Whitman, Spencer, Sootla, Sten, Collot, Stephane, Gururangan, Suchin, Borodinsky, Sydney, Herman, Tamar, Fowler, Tara, Sheasha, Tarek, Georgiou, Thomas, Scialom, Thomas, Speckbacher, Tobias, Mihaylov, Todor, Xiao, Tong, Karn, Ujjwal, Goswami, Vedanuj, Gupta, Vibhor, Ramanathan, Vignesh, Kerkez, Viktor, Gonguet, Vincent, Do, Virginie, Vogeti, Vish, Petrovic, Vladan, Chu, Weiwei, Xiong, Wenhan, Fu, Wenyin, Meers, Whitney, Martinet, Xavier, Wang, Xiaodong, Tan, Xiaoqing Ellen, Xie, Xinfeng, Jia, Xuchao, Wang, Xuewei, Goldschlag, Yaelle, Gaur, Yashesh, Babaei, Yasmine, Wen, Yi, Song, Yiwen, Zhang, Yuchen, Li, Yue, Mao, Yuning, Coudert, Zacharie Delpierre, Yan, Zheng, Chen, Zhengxing, Papakipos, Zoe, Singh, Aaditya, Grattafiori, Aaron, Jain, Abha, Kelsey, Adam, Shajnfeld, Adam, Gangidi, Adithya, Victoria, Adolfo, Goldstand, Ahuva, Menon, Ajay, Sharma, Ajay, Boesenberg, Alex, Vaughan, Alex, Baevski, Alexei, Feinstein, Allie, Kallet, Amanda, Sangani, Amit, Yunus, Anam, Lupu, Andrei, Alvarado, Andres, Caples, Andrew, Gu, Andrew, Ho, Andrew, Poulton, Andrew, Ryan, Andrew, Ramchandani, Ankit, Franco, Annie, Saraf, Aparajita, Chowdhury, Arkabandhu, Gabriel, Ashley, Bharambe, Ashwin, Eisenman, Assaf, Yazdan, Azadeh, James, Beau, Maurer, Ben, Leonhardi, Benjamin, Huang, Bernie, Loyd, Beth, De Paola, Beto, Paranjape, Bhargavi, Liu, Bing, Wu, Bo, Ni, Boyu, Hancock, Braden, Wasti, Bram, Spence, Brandon, Stojkovic, Brani, Gamido, Brian, Montalvo, Britt, Parker, Carl, Burton, Carly, Mejia, Catalina, Wang, Changhan, Kim, Changkyu, Zhou, Chao, Hu, Chester, Chu, Ching-Hsiang, Cai, Chris, Tindal, Chris, Feichtenhofer, Christoph, Civin, Damon, Beaty, Dana, Kreymer, Daniel, Li, Daniel, Wyatt, Danny, Adkins, David, Xu, David, Testuggine, Davide, David, Delia, Parikh, Devi, Liskovich, Diana, Foss, Didem, Wang, Dingkang, Le, Duc, Holland, Dustin, Dowling, Edward, Jamil, Eissa, Montgomery, Elaine, Presani, Eleonora, Hahn, Emily, Wood, Emily, Brinkman, Erik, Arcaute, Esteban, Dunbar, Evan, Smothers, Evan, Sun, Fei, Kreuk, Felix, Tian, Feng, Ozgenel, Firat, Caggioni, Francesco, Guzmán, Francisco, Kanayet, Frank, Seide, Frank, Florez, Gabriela Medina, Schwarz, Gabriella, Badeer, Gada, Swee, Georgia, Halpern, Gil, Thattai, Govind, Herman, Grant, Sizov, Grigory, Guangyi, Zhang, Lakshminarayanan, Guna, Shojanazeri, Hamid, Zou, Han, Wang, Hannah, Zha, Hanwen, Habeeb, Haroun, Rudolph, Harrison, Suk, Helen, Aspegren, Henry, Goldman, Hunter, Damlaj, Ibrahim, Molybog, Igor, Tufanov, Igor, Veliche, Irina-Elena, Gat, Itai, Weissman, Jake, Geboski, James, Kohli, James, Asher, Japhet, Gaya, Jean-Baptiste, Marcus, Jeff, Tang, Jeff, Chan, Jennifer, Zhen, Jenny, Reizenstein, Jeremy, Teboul, Jeremy, Zhong, Jessica, Jin, Jian, Yang, Jingyi, Cummings, Joe, Carvill, Jon, Shepard, Jon, McPhie, Jonathan, Torres, Jonathan, Ginsburg, Josh, Wang, Junjie, Wu, Kai, U, Kam Hou, Saxena, Karan, Prasad, Karthik, Khandelwal, Kartikay, Zand, Katayoun, Matosich, Kathy, Veeraraghavan, Kaushik, Michelena, Kelly, Li, Keqian, Huang, Kun, Chawla, Kunal, Lakhotia, Kushal, Huang, Kyle, Chen, Lailin, Garg, Lakshya, A, Lavender, Silva, Leandro, Bell, Lee, Zhang, Lei, Guo, Liangpeng, Yu, Licheng, Moshkovich, Liron, Wehrstedt, Luca, Khabsa, Madian, Avalani, Manav, Bhatt, Manish, Tsimpoukelli, Maria, Mankus, Martynas, Hasson, Matan, Lennie, Matthew, Reso, Matthias, Groshev, Maxim, Naumov, Maxim, Lathi, Maya, Keneally, Meghan, Seltzer, Michael L., Valko, Michal, Restrepo, Michelle, Patel, Mihir, Vyatskov, Mik, Samvelyan, Mikayel, Clark, Mike, Macey, Mike, Wang, Mike, Hermoso, Miquel Jubert, Metanat, Mo, Rastegari, Mohammad, Bansal, Munish, Santhanam, Nandhini, Parks, Natascha, White, Natasha, Bawa, Navyata, Singhal, Nayan, Egebo, Nick, Usunier, Nicolas, Laptev, Nikolay Pavlovich, Dong, Ning, Zhang, Ning, Cheng, Norman, Chernoguz, Oleg, Hart, Olivia, Salpekar, Omkar, Kalinli, Ozlem, Kent, Parkin, Parekh, Parth, Saab, Paul, Balaji, Pavan, Rittner, Pedro, Bontrager, Philip, Roux, Pierre, Dollar, Piotr, Zvyagina, Polina, Ratanchandani, Prashant, Yuvraj, Pritish, Liang, Qian, Alao, Rachad, Rodriguez, Rachel, Ayub, Rafi, Murthy, Raghotham, Nayani, Raghu, Mitra, Rahul, Li, Raymond, Hogan, Rebekkah, Battey, Robin, Wang, Rocky, Maheswari, Rohan, Howes, Russ, Rinott, Ruty, Bondu, Sai Jayesh, Datta, Samyak, Chugh, Sara, Hunt, Sara, Dhillon, Sargun, Sidorov, Sasha, Pan, Satadru, Verma, Saurabh, Yamamoto, Seiji, Ramaswamy, Sharadh, Lindsay, Shaun, Feng, Sheng, Lin, Shenghao, Zha, Shengxin Cindy, Shankar, Shiva, Zhang, Shuqiang, Wang, Sinong, Agarwal, Sneha, Sajuyigbe, Soji, Chintala, Soumith, Max, Stephanie, Chen, Stephen, Kehoe, Steve, Satterfield, Steve, Govindaprasad, Sudarshan, Gupta, Sumit, Cho, Sungmin, Virk, Sunny, Subramanian, Suraj, Choudhury, Sy, Goldman, Sydney, Remez, Tal, Glaser, Tamar, Best, Tamara, Kohler, Thilo, Robinson, Thomas, Li, Tianhe, Zhang, Tianjun, Matthews, Tim, Chou, Timothy, Shaked, Tzook, Vontimitta, Varun, Ajayi, Victoria, Montanez, Victoria, Mohan, Vijai, Kumar, Vinay Satish, Mangla, Vishal, Albiero, Vítor, Ionescu, Vlad, Poenaru, Vlad, Mihailescu, Vlad Tiberiu, Ivanov, Vladimir, Li, Wei, Wang, Wenchen, Jiang, Wenwen, Bouaziz, Wes, Constable, Will, Tang, Xiaocheng, Wang, Xiaofang, Wu, Xiaojian, Wang, Xiaolan, Xia, Xide, Wu, Xilun, Gao, Xinbo, Chen, Yanjun, Hu, Ye, Jia, Ye, Qi, Ye, Li, Yenda, Zhang, Yilin, Zhang, Ying, Adi, Yossi, Nam, Youngjin, Yu, Wang, Hao, Yuchen, Qian, Yundi, He, Yuzi, Rait, Zach, DeVito, Zachary, Rosnbrick, Zef, Wen, Zhaoduo, Yang, Zhenyu, and Zhao, Zhiwei

Subjects
Computer Science - Artificial Intelligence, Computer Science - Computation and Language, Computer Science - Computer Vision and Pattern Recognition
Abstract

Modern artificial intelligence (AI) systems are powered by foundation models. This paper presents a new set of foundation models, called Llama 3. It is a herd of language models that natively support multilinguality, coding, reasoning, and tool usage. Our largest model is a dense Transformer with 405B parameters and a context window of up to 128K tokens. This paper presents an extensive empirical evaluation of Llama 3. We find that Llama 3 delivers comparable quality to leading language models such as GPT-4 on a plethora of tasks. We publicly release Llama 3, including pre-trained and post-trained versions of the 405B parameter language model and our Llama Guard 3 model for input and output safety. The paper also presents the results of experiments in which we integrate image, video, and speech capabilities into Llama 3 via a compositional approach. We observe this approach performs competitively with the state-of-the-art on image, video, and speech recognition tasks. The resulting models are not yet being broadly released as they are still under development.

Published
2024

3. ToMoBrush: Exploring Dental Health Sensing using a Sonic Toothbrush

Author

Yuan, Kuang, Ibrahim, Mohamed, Song, Yiwen, Deng, Guoxiang, Vijayan, Suvendra, Nerone, Robert, Gadre, Akshay, and Kumar, Swarun

Subjects
Electrical Engineering and Systems Science - Audio and Speech Processing, Computer Science - Sound, J.3, C.3, H.5.2
Abstract

Early detection of dental disease is crucial to prevent adverse outcomes. Today, dental X-rays are currently the most accurate gold standard for dental disease detection. Unfortunately, regular X-ray exam is still a privilege for billions of people around the world. In this paper, we ask: "Can we develop a low-cost sensing system that enables dental self-examination in the comfort of one's home?" This paper presents ToMoBrush, a dental health sensing system that explores using off-the-shelf sonic toothbrushes for dental condition detection. Our solution leverages the fact that a sonic toothbrush produces rich acoustic signals when in contact with teeth, which contain important information about each tooth's status. ToMoBrush extracts tooth resonance signatures from the acoustic signals to characterize varied dental health conditions of the teeth. We evaluate ToMoBrush on 19 participants and dental-standard models for detecting common dental problems including caries, calculus, and food impaction, achieving a detection ROC-AUC of 0.90, 0.83, and 0.88 respectively. Interviews with dental experts validate ToMoBrush's potential in enhancing at-home dental healthcare.

Published
2024
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4. Emu: Enhancing Image Generation Models Using Photogenic Needles in a Haystack

Author

Dai, Xiaoliang, Hou, Ji, Ma, Chih-Yao, Tsai, Sam, Wang, Jialiang, Wang, Rui, Zhang, Peizhao, Vandenhende, Simon, Wang, Xiaofang, Dubey, Abhimanyu, Yu, Matthew, Kadian, Abhishek, Radenovic, Filip, Mahajan, Dhruv, Li, Kunpeng, Zhao, Yue, Petrovic, Vladan, Singh, Mitesh Kumar, Motwani, Simran, Wen, Yi, Song, Yiwen, Sumbaly, Roshan, Ramanathan, Vignesh, He, Zijian, Vajda, Peter, and Parikh, Devi

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Training text-to-image models with web scale image-text pairs enables the generation of a wide range of visual concepts from text. However, these pre-trained models often face challenges when it comes to generating highly aesthetic images. This creates the need for aesthetic alignment post pre-training. In this paper, we propose quality-tuning to effectively guide a pre-trained model to exclusively generate highly visually appealing images, while maintaining generality across visual concepts. Our key insight is that supervised fine-tuning with a set of surprisingly small but extremely visually appealing images can significantly improve the generation quality. We pre-train a latent diffusion model on $1.1$ billion image-text pairs and fine-tune it with only a few thousand carefully selected high-quality images. The resulting model, Emu, achieves a win rate of $82.9\%$ compared with its pre-trained only counterpart. Compared to the state-of-the-art SDXLv1.0, Emu is preferred $68.4\%$ and $71.3\%$ of the time on visual appeal on the standard PartiPrompts and our Open User Input benchmark based on the real-world usage of text-to-image models. In addition, we show that quality-tuning is a generic approach that is also effective for other architectures, including pixel diffusion and masked generative transformer models.

Published
2023

5. Controlling the 2D magnetism of CrBr$_3$ by van der Waals stacking engineering

Author

Yang, Shiqi, Xu, Xiaolong, Han, Bo, Gu, Pingfan, Guzman, Roger, Song, Yiwen, Lin, Zhongchong, Gao, Peng, Zhou, Wu, Yang, Jinbo, Chen, Zuxin, and Ye, Yu

Subjects
Condensed Matter - Materials Science, Condensed Matter - Mesoscale and Nanoscale Physics
Abstract

The manipulation of two-dimensional (2D) magnetic order is of significant importance to facilitate future 2D magnets for low-power and high-speed spintronic devices. Van der Waals stacking engineering makes promises for controllable magnetism via interlayer magnetic coupling. However, directly examining the stacking order changes accompanying magnetic order transitions at the atomic scale and preparing device-ready 2D magnets with controllable magnetic orders remain elusive. Here, we demonstrate effective control of interlayer stacking in exfoliated CrBr$_3$ via thermally assisted strain engineering. The stable interlayer ferromagnetic (FM), antiferromagnetic (AFM), and FM-AFM coexistent ground states confirmed by the magnetic circular dichroism measurements are realized. Combined with the first-principles calculations, the atomically-resolved imaging technique reveals the correlation between magnetic order and interlay stacking order in the CrBr$_3$ flakes unambiguously. A tunable exchange bias effect is obtained in the mixed phase of FM and AFM states. This work will introduce new magnetic properties by controlling the stacking order, and sequence of 2D magnets, providing ample opportunities for their application in spintronic devices., Comment: 7 pages, 4 figures

Published
2023

6. PACO: Parts and Attributes of Common Objects

Author

Ramanathan, Vignesh, Kalia, Anmol, Petrovic, Vladan, Wen, Yi, Zheng, Baixue, Guo, Baishan, Wang, Rui, Marquez, Aaron, Kovvuri, Rama, Kadian, Abhishek, Mousavi, Amir, Song, Yiwen, Dubey, Abhimanyu, and Mahajan, Dhruv

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Object models are gradually progressing from predicting just category labels to providing detailed descriptions of object instances. This motivates the need for large datasets which go beyond traditional object masks and provide richer annotations such as part masks and attributes. Hence, we introduce PACO: Parts and Attributes of Common Objects. It spans 75 object categories, 456 object-part categories and 55 attributes across image (LVIS) and video (Ego4D) datasets. We provide 641K part masks annotated across 260K object boxes, with roughly half of them exhaustively annotated with attributes as well. We design evaluation metrics and provide benchmark results for three tasks on the dataset: part mask segmentation, object and part attribute prediction and zero-shot instance detection. Dataset, models, and code are open-sourced at https://github.com/facebookresearch/paco.

Published
2023

8. Ultra-Wide Bandgap Ga$_2$O$_3$-on-SiC MOSFETs

Author

Song, Yiwen, Bhattacharyya, Arkka, Karim, Anwarul, Shoemaker, Daniel, Huang, Hsien-Lien, Roy, Saurav, McGray, Craig, Leach, Jacob H., Hwang, Jinwoo, Krishnamoorthy, Sriram, and Choi, Sukwon

Subjects
Condensed Matter - Materials Science, Physics - Applied Physics
Abstract

Ulta-wide bandgap semiconductors based on $\beta$-Ga$_2$O$_3$ offer the potential to achieve higher power switching performance, efficiency, and lower manufacturing cost than today's wide bandgap power semiconductors. However, the most critical challenge to the commercialization of Ga$_2$O$_3$ electronics is overheating, which impacts the device's performance and reliability. We fabricated a Ga$_2$O$_3$/4H-SiC composite wafer using a fusion-bonding method. A low temperature ($\le$ 600 $^{\circ}$C) epitaxy and device processing approach based on low-temperature (LT) metalorganic vapor phase epitaxy is developed to grow a Ga$_2$O$_3$ epitaxial channel layer on the composite wafer and subsequently fabricate into Ga$_2$O$_3$ power MOSFETs. This LT approach is essential to preserve the structural integrity of the composite wafer. These LT-grown epitaxial Ga$_2$O$_3$ MOSFETs deliver high thermal performance (56% reduction in channel temperature), high voltage blocking capabilities up to 2.45 kV, and power figures of merit of $\sim$ 300 MW/cm$^2$, which is a record high for any heterogeneously integrated Ga$_2$O$_3$ devices reported to date. This work is the first realization of multi-kilovolt homoepitaxial Ga$_2$O$_3$ power MOSFETs fabricated on a composite substrate with high heat transfer performance which delivers state-of-the-art power density values while running much cooler than those on native substrates. Thermal characterization and modeling results reveal that a Ga$_2$O$_3$/diamond composite wafer with a reduced Ga$_2$O$_3$ thickness ($\sim$ 1 $\mu$m) and thinner bonding interlayer ($<$ 10 nm) can reduce the device thermal impedance to a level lower than today's GaN-on-SiC power switches., Comment: 17 pages, 9 figures

Published
2022

12. Substrate dependence of the self-heating in lead zirconate titanate (PZT) MEMS actuators.

Author

Song, Yiwen, Kang, Kyuhwe, Tipsawat, Pannawit, Cheng, Christopher Y., Zhu, Wanlin, LaBella, Michael, Choi, Sukwon, and Trolier-McKinstry, Susan E.

Subjects
*LEAD zirconate titanate, *ACTUATORS, *THERMAL conductivity, *FINITE element method, *MEMS resonators, *MICROELECTROMECHANICAL systems, *ENERGY dissipation
Abstract

Lead zirconate titanate (PZT) thin films offer advantages in microelectromechanical systems (MEMSs) including large motion, lower drive voltage, and high energy densities. Depending on the application, different substrates are sometimes required. Self-heating occurs in the PZT MEMS due to the energy loss from domain wall motion, which can degrade the device performance and reliability. In this work, the self-heating of PZT thin films on Si and glass and a film released from a substrate were investigated to understand the effect of substrates on the device temperature rise. Nano-particle assisted Raman thermometry was employed to quantify the operational temperature rise of these PZT actuators. The results were validated using a finite element thermal model, where the volumetric heat generation was experimentally determined from the hysteresis loss. While the volumetric heat generation of the PZT films on different substrates was similar, the PZT films on the Si substrate showed a minimal temperature rise due to the effective heat dissipation through the high thermal conductivity substrate. The temperature rise on the released structure is 6.8× higher than that on the glass substrates due to the absence of vertical heat dissipation. The experimental and modeling results show that the thin layer of residual Si remaining after etching plays a crucial role in mitigating the effect of device self-heating. The outcomes of this study suggest that high thermal conductivity passive elastic layers can be used as an effective thermal management solution for PZT-based MEMS actuators. [ABSTRACT FROM AUTHOR]

Published
2024
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14. A study on the configuration of factors influencing overweight and obesity in adolescents based on fuzzy set qualitative comparative analysis.

Author

Song, Yiwen, Li, Xinru, Hu, Bingqin, Chen, Yitong, Cui, Peiyao, Liang, Yifang, He, Xin, Yang, Guofeng, and Li, Jinghua

Subjects
*ADOLESCENT obesity, *PUBLIC health, *PHYSICAL activity, *SLEEP duration, *SOCIAL surveys
Abstract

Objective: Overweight and obesity among adolescents are grave public health issues around the world. Although the conditions that contribute to obesity have been extensively researched, little is known about how multiple conditions interact to cause overweight and obesity. The current study intends to investigate the histomorphic configuration pathways of several conditions of adolescent overweight and obesity by gender. Method: The data came from a social survey conducted in June 2021 in Changchun, Jilin Province, China. The sample collected was 14‐year‐old adolescents, including 167 boys and 137 girls. The school physicians examined the participants' weight and height, and questionnaires were used to collect risk indicators from adolescents, such as sleep duration, electronic screens times, consumption of sugary drinks and fried foods, and physical activity. Simultaneously, a Fuzzy Qualitative Comparative Analysis will be performed to investigate the combinations of diverse conditions. Result: We found that there is no determining necessary condition that, once present, directly determines that an individual is in a state of overweight and obesity. Simultaneously, this study revealed nine alternative configurational paths of overweight and obesity in teenagers of different genders, with a concordance of 0.805 for six male groupings and 0.916 for three female groupings. The outcomes of overweight obesity in adolescents under different genders are similar but not identical. Conclusion: This study examined the interactions of a number of conditions from the individual, behavioral, learning and living environment that led to the same overweight obese outcome among adolescents of different genders. Our research will be useful to policymakers in that interventions should take into account the combined effects of a number of different aspects rather than focusing on a single factor that causes overweight and obesity. [ABSTRACT FROM AUTHOR]

Published
2024
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20. Growth-microstructure-thermal property relations in AlN thin films.

Author

Song, Yiwen, Zhang, Chi, Lundh, James Spencer, Huang, Hsien-Lien, Zheng, Yue, Zhang, Yingying, Park, Mingyo, Mirabito, Timothy, Beaucejour, Rossiny, Chae, Chris, McIlwaine, Nathaniel, Esteves, Giovanni, Beechem, Thomas E., Moe, Craig, Dargis, Rytis, Jones, Jeremy, Leach, Jacob H., Lavelle, Robert M., Snyder, David W., and Maria, Jon-Paul

Subjects
*THIN films, *PHONON scattering, *THERMAL conductivity, *REACTIVE sputtering, *MICROELECTROMECHANICAL systems, *POWER electronics
Abstract

AlN thin films are enabling significant progress in modern optoelectronics, power electronics, and microelectromechanical systems. The various AlN growth methods and conditions lead to different film microstructures. In this report, phonon scattering mechanisms that impact the cross-plane (κz; along the c-axis) and in-plane (κr; parallel to the c-plane) thermal conductivities of AlN thin films prepared by various synthesis techniques are investigated. In contrast to bulk single crystal AlN with an isotropic thermal conductivity of ∼330 W/m K, a strong anisotropy in the thermal conductivity is observed in the thin films. The κz shows a strong film thickness dependence due to phonon-boundary scattering. Electron microscopy reveals the presence of grain boundaries and dislocations that limit the κr. For instance, oriented films prepared by reactive sputtering possess lateral crystalline grain sizes ranging from 20 to 40 nm that significantly lower the κr to ∼30 W/m K. Simulation results suggest that the self-heating in AlN film bulk acoustic resonators can significantly impact the power handling capability of RF filters. A device employing an oriented film as the active piezoelectric layer shows an ∼2.5× higher device peak temperature as compared to a device based on an epitaxial film. [ABSTRACT FROM AUTHOR]

Published
2022
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33. PACO: Parts and Attributes of Common Objects

Author

Ramanathan, Vignesh, primary, Kalia, Anmol, additional, Petrovic, Vladan, additional, Wen, Yi, additional, Zheng, Baixue, additional, Guo, Baishan, additional, Wang, Rui, additional, Marquez, Aaron, additional, Kovvuri, Rama, additional, Kadian, Abhishek, additional, Mousavi, Amir, additional, Song, Yiwen, additional, Dubey, Abhimanyu, additional, and Mahajan, Dhruv, additional

Published
2023
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34. Nanoscale Channel Length MoS2Vertical Field-Effect Transistor Arrays with Side-Wall Source/Drain Electrodes

Author

Jia, Xionghui, Cheng, Zhixuan, Song, Yiwen, Zhang, Yi, Ye, Yu, Li, Minglai, Cheng, Xing, Xu, Wanjin, Li, Yanping, and Dai, Lun

Abstract

Two-dimensional transition metal dichalcogenides (TMDCs) have natural advantages in overcoming the short-channel effect in field-effect transistors (FETs) and in fabricating three-dimensional FETs, which benefit in increasing device density. However, so far, most reported works related to MoS2FETs with a sub-100 nm channel employ mechanically exfoliated materials and all of the works involve electron beam lithography (EBL), which may limit their application in fabricating wafer-scale device arrays as demanded in integrated circuits (ICs). In this work, MoS2FET arrays with a side-wall source and drain electrodes vertically distributed are designed and fabricated. The channel length of the as-fabricated FET is basically determined by the thickness of an insulating layer between the source and drain electrodes. The vertically distributed source and drain electrodes enable to reduce the electrode-occupied area and increase in the device density. The as-fabricated vertical FETs exhibit on/off ratios comparable to those of mechanically exfoliated MoS2FETs with a nanoscale channel length under identical VDS. In addition, the as-fabricated FETs can work at a VDSas low as 10 mV with a desirable on/off ratio (1.9 × 107), which benefits in developing low-power devices. Moreover, the fabrication process is free from EBL and can be applied to wafer-scale device arrays. The statistical results show that the fabricated FET arrays have a device yield of 87.5% and an average on/off ratio of about 1.7 × 106at a VDSof 10 mV, with the lowest and highest ones to be about 1.3 × 104and 1.9 × 107, respectively, demonstrating the good reliability of our fabrication process. Our work promises a bright future for TMDCs in realizing high-density and low-power nanoelectronic devices in ICs.

Published
2024
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38. Controlling the 2D Magnetism of CrBr3by van der Waals Stacking Engineering

Author

Yang, Shiqi, Xu, Xiaolong, Han, Bo, Gu, Pingfan, Guzman, Roger, Song, Yiwen, Lin, Zhongchong, Gao, Peng, Zhou, Wu, Yang, Jinbo, Chen, Zuxin, and Ye, Yu

Abstract

The manipulation of two-dimensional (2D) magnetic order is of significant importance to facilitate future 2D magnets for low-power and high-speed spintronic devices. van der Waals stacking engineering makes promises for controllable magnetism via interlayer magnetic coupling. However, directly examining the stacking order changes accompanying magnetic order transitions at the atomic scale and preparing device-ready 2D magnets with controllable magnetic orders remain elusive. Here, we demonstrate the effective control of interlayer stacking in exfoliated CrBr3via thermally assisted strain engineering. The stable interlayer ferromagnetic (FM), antiferromagnetic (AFM), and FM-AFM coexistent ground states confirmed by the magnetic circular dichroism measurements are realized. Combined with the first-principles calculations, the atomically resolved imaging technique reveals the correlation between magnetic order and interlayer stacking order in CrBr3flakes unambiguously. A tunable exchange bias effect is obtained in the mixed phase of FM and AFM states. This work will introduce new magnetic properties by controlling the stacking order and sequence of 2D magnets, providing ample opportunities for their application in spintronic devices.

Published
2023
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39. Thermal analysis of an α-Ga2O3 MOSFET using micro-Raman spectroscopy.

Author

Karim, Anwarul, Song, Yiwen, Shoemaker, Daniel C., Jeon, Dae-Woo, Park, Ji-Hyeon, Mun, Jae Kyoung, Lee, Hun Ki, and Choi, Sukwon

Subjects
*MODULATION-doped field-effect transistors, *METAL oxide semiconductor field-effect transistors, *THERMAL resistance, *THERMAL analysis, *BUFFER layers, *POWER electronics
Abstract

The ultra-wide bandgap (UWBG) energy (∼5.4 eV) of α-phase Ga2O3 offers the potential to achieve higher power switching performance and efficiency than today's power electronic devices. However, a major challenge to the development of the α-Ga2O3 power electronics is overheating, which can degrade the device performance and cause reliability issues. In this study, thermal characterization of an α-Ga2O3 MOSFET was performed using micro-Raman thermometry to understand the device self-heating behavior. The α-Ga2O3 MOSFET exhibits a channel temperature rise that is more than two times higher than that of a GaN high electron mobility transistor (HEMT). This is mainly because of the low thermal conductivity of α-Ga2O3 (11.9 ± 1.0 W/mK at room temperature), which was determined via laser-based pump-probe experiments. A hypothetical device structure was constructed via simulation that transfer-bonds the α-Ga2O3 epitaxial structure over a high thermal conductivity substrate. Modeling results suggest that the device thermal resistance can be reduced to a level comparable to or even better than those of today's GaN HEMTs using this strategy combined with thinning of the α-Ga2O3 buffer layer. The outcomes of this work suggest that device-level thermal management is essential to the successful deployment of UWBG α-Ga2O3 devices. [ABSTRACT FROM AUTHOR]

Published
2023
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40. Large‐Scale N‐Type FET and Homogeneous CMOS Inverter Array Based on Few‐Layer MoTe2.

Author

Cheng, Zhixuan, Jia, Xionghui, Cheng, Xing, Song, Yiwen, Ran, Yuqia, Li, Minglai, Xu, Wanjin, Li, Yanping, Ye, Yu, and Dai, Lun

Subjects
FIELD-effect transistors, ELECTRON density, COMPLEMENTARY metal oxide semiconductors, NANOELECTRONICS, TRANSISTORS, DIELECTRICS
Abstract

2D MoTe2 is regarded as a favorable candidate for semiconductor nanoelectronics integration. Chemical‐vapor‐deposition‐grown MoTe2 usually presents p‐type characteristics. In order to realize basic electronic units like complementary metal‐oxide‐semiconductor (CMOS) inverter, controllable fabrication of p‐ and n‐type transistors at large scale is of vital importance. Here, large‐scale MoTe2 n‐channel field‐effect transistor (n‐FET) arrays are successfully fabricated with seamless coplanar metallic 1T′‐WTe2 contacts to reduce contact resistance. High‐k HfO2 serves as a gate dielectric and its atomic‐layer‐deposition (ALD) process causes an n‐doping effect on the 2H‐MoTe2 channel. The FETs perform typical n‐type characteristics with average electron density and on/off ratio of ≈1.7 × 1013 cm−2 and 2.1 × 104, respectively. Furthermore, large‐scale homogeneous CMOS inverter arrays are fabricated, showing clear logic swing with low power consumption (≈0.4 nW) and high device yield (≈92%). Notably, their voltage transfer characteristics exhibit small hysteresis, and they work well after being kept in air for 16 months, indicating high device stability. The statistical results show that both the n‐FETs and CMOS inverters have high uniformity and reliability in performance. Significantly, this fabrication method is free from transfer processes and compatible with traditional silicon technology. This work paves the way for the application of few‐layer MoTe2 in semiconductor nanoelectronics integration. [ABSTRACT FROM AUTHOR]

Published
2023
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41. Composition and temperature-dependent terahertz emission in ferrimagnetic Ta/Tbx(FeCo)1–x/Pt heterostructures.

Author

Ji, Zhihao, Song, Yuna, Liu, Yu, Zhang, Yu, Li, Ziyang, Song, Yiwen, Zhang, Jingying, Lou, Shitao, Zhang, Zongzhi, and Jin, Qingyuan

Subjects
TANTALUM, SPIN Hall effect, SPIN polarization, TERBIUM, HETEROSTRUCTURES, MAGNETIC moments, EMISSION spectroscopy
Abstract

A spintronic terahertz (THz) emitter based on rare-earth-transition-metal ferrimagnetic alloys has drawn wide attention due to its prominent THz emission signals at a magnetic compensated state. Here, THz emission spectroscopy is performed in a layered ferrimagnetic/nonmagnetic structure of Ta/Tbx(FeCo)1–x/Pt to investigate the impact of magnetization and spin polarization on THz radiation. Composition and temperature-dependent THz emission signals are observed by an inverse spin Hall effect. The variation of THz amplitude approximately follows the in-plane magnetization in the composition range, yet a nonvanishing THz radiation at the compensation point indicates that net spin polarization dominates the emitted THz electric field rather than net magnetization in this two-sublattice system. A significant gap of 90 K between the compensation point of magnetic moment and spin polarization is found in a Tb0.24(FeCo)0.76 sample, which is a striking difference to that of 25 K in GdCo/Pt THz emitters. We attribute this anomalous gap to the strong intersublattice 3d-5d6s-4f exchange interaction of TbFeCo alloy; thus, the contribution of spin polarized Tb 4f electrons should be reconsidered after fs laser pulse excitation. These results gain insight into spin dynamics of complex multisublattice systems and pave the way for further optimized spintronic THz emitters to modulate THz radiation efficiently. [ABSTRACT FROM AUTHOR]

Published
2023
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44. Ultra-Wide Band Gap Ga2O3-on-SiC MOSFETs

Author

Song, Yiwen, primary, Bhattacharyya, Arkka, additional, Karim, Anwarul, additional, Shoemaker, Daniel, additional, Huang, Hsien-Lien, additional, Roy, Saurav, additional, McGray, Craig, additional, Leach, Jacob H., additional, Hwang, Jinwoo, additional, Krishnamoorthy, Sriram, additional, and Choi, Sukwon, additional

Published
2023
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48. Frequency Dependence of Wake-Up and Fatigue Characteristics in Ferroelectric Al0 .93 B 0.07 N Thin Films

Author

He, Fan, primary, Zhu, Wanlin, additional, Hayden, John, additional, Casamento, Joseph, additional, Tran, Quyen, additional, Kang, Kyuhwe, additional, Song, Yiwen, additional, Akgun, Betul Akkopru, additional, Yang, Jung In, additional, Tipsawat, Pannawit, additional, Brennecka, Geoff, additional, Choi, Sukwon, additional, Jackson, Thomas N., additional, Maria, Jon-Paul, additional, and Trolier-McKinstry, Susan, additional

Published
2023
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