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Ke Yin on Muck Rack

Ke Yin

As seen in: Nature, Wiley Online Library, arXiv, ScienceDirect, Frontiers, MDPI, ACS Publications, Science Magazine, Royal Society of Chemistry, Physical Review B and
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Articles

Overcoming the thermo-refractive noise limit for a full-spectrum Hertz-linewidth microcomb

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By Chao Zhou, Runlin Miao, Pan Han, Mingxin Yang, Xing Zou, Ke Wei, Ke Yin, Tian Jiang
| Nature Verified
Abstract Chip-scale microcombs combining high repetition rates and Hertz-level linewidths are critical for precision measurements and parallel coherent communications. Self-injection locking (SIL) has been widely used but faces a fundamental limitation: the microresonator must simultaneously generate the comb and suppress noise, creating a coherence ceiling set by thermo-refractive noise (TRN). This imposes a fundamental trade-off between repetition rate and linewidth.
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Critical point–based wireless sensors enabling tiny perturbation detection

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By Robert A Kozol, Peishi Rao, Yvonne T. Kschonsak, Chao Ma, Ke Yin, Zhuoyu Zhang, Ruyi Huang, Yuangen Huang, Lanyue Gan, Yuxuan Liu, Fan Xia, Tian Xia, Yufan Chen, Wangchang Li, Lian-Mao Peng, Tianyu Dong, Youfan Hu
| Science Magazine Verified
Abstract INTRODUCTION RESULTS DISCUSSION MATERIALS AND METHODS Acknowledgments Supplementary Materials REFERENCES Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract High quality factor and sensitivity are critical to wireless sensors targeting small perturbation detection. Although introducing parity-time symmetric dynamics promises enhanced performance, the symmetric scheme often yields limited sensing behaviors.
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Misbehaviour dominates GHG emissions from food loss and waste

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By Ke Yin, Jingyu Zhu, Mo Wu, Houhu Zhang, Xue Ling, Shuhan Ren, Xingyu Zhao, Chen Ling, Lei Yu, Huanhuan Tong, Yao Wang, Xunchang Fei, Maoyao Cai
| Nature Verified
Abstract Food loss and waste (FLW) generates ~19% of global anthropogenic greenhouse gas emissions, yet its determinants and mitigation potential remain insufficiently understood. To address this, we develop a mechanistic framework that disaggregates FLW emissions into those driven by techno-economic constraints, surplus production and mis-consumption, with the latter two constituting misbehaviour-driven emissions.
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