Central Detector
(1) Laser measurement system for acrylic transmittance of JUNO central detector, Zhaohan Li, et al., Rad.Det.Tech.Meth. 5 (2021) 3, 356-363
(2) The stress measurement system for the JUNO Central Detector acrylic panels, X. Yang, et al., JINST 16 (2021) 12, P12040. https://doi.org/10.1088/1748-0221/16/12/P12040
(3) Structure design and compression experiment of the supporting node for JUNO PMMA detector, Xiaohui Qian, et al., Radiat Detect Technol Methods 4 (2020) 345-355. https://doi.org/10.1007/s41605-020-00190-0
(4) The measurement system of acrylic transmittance for the JUNO central detector, Xiaoyu Yang, et al., Radiat Detect Technol Methods 4, 284–292 (2020). https://doi.org/10.1007/s41605-020-00182-0
(5) FE Analysis on the Thermoforming Behaviour of Large Spherical PMMA Panelapplied in JUNO, Xiaohui Qian, et al., IOP Conf. Ser.: Mater. Sci. Eng. 774 012148. https://doi.org/10.1088/1757-899x/774/1/012148
(6) Thermal reliability analysis of the central detector of JUNO, Xiaoyu Yang, et al., Radiat Detect Technol Methods 3, 64 (2019). https://doi.org/10.1007/s41605-019-0142-y
(7) The design of the small prototype for the central detector of JUNO, Xiaoyu Yang, et al, Radiat Detect Technol Methods 2, 46 (2018). https://doi.org/10.1007/s41605-018-0073-z
Liquid Scintillator
(1) Measurements of Rayleigh Ratios in Linear Alkylbenzene, Miao Yu et al., Rev.Sci.Inst. 93 (2022) 063106. https://doi.org/10.1063/5.0091847 https://arxiv.org/abs/2203.03126
(2) Exploring the intrinsic energy resolution of liquid scintillator to approximately 1 MeV electrons, Y. Deng, et al., JINST 17 (2022) 04, P04018. https://doi.org/10.1088/1748-0221/17/04/P04018 https://arxiv.org/abs/2203.05200
(3) Development of water extraction system for liquid scintillator purification of JUNO Y. Deng, et al., Nucl.Instrum.Meth.A 1027 (2022) 166251. https://doi.org/10.1016/j.nima.2021.166251 https://arxiv.org/abs/2109.07317
(4) The replacement system of the JUNO liquid scintillator pilot experiment at Daya Bay, Wenqi Yan, et al., Nucl.Instrum.Meth.A 996 (2021) 165109. https://doi.org/10.1016/j.nima.2021.165109 https://arxiv.org/abs/2011.05655
(5) Radon activity measurement of JUNO nitrogen, X. Yu, et al., JINST 15 (2020) 09, P09001. https://doi.org/10.1088/1748-0221/15/09/P09001
(6) Distillation and stripping pilot plants for the JUNO neutrino detector: Design, operations and reliability, P. Lombardi, et al., Nucl.Instrum.Meth.A 925 (2019) 6-17. https://doi.org/10.1016/j.nima.2019.01.071 https://arxiv.org/abs/1902.05288
(7) Thermal diffusivity and specific heat capacity of linear alkylbenzene Wenjie Wu, et al., Phys.Scripta 94 (2019) 10, 105701. https://doi.org/10.1088/1402-4896/ab1cea https://arxiv.org/abs/1904.12147
(8) Measurements of the Lifetime of Orthopositronium in the LAB-Based Liquid Scintillator of JUNO, Mario Schwarz, et al., Nucl.Instrum.Meth.A 922 (2019) 64-70. https://doi.org/10.1016/j.nima.2018.12.068. https://arxiv.org/abs/1804.09456
(9) Light Absorption Properties of the High Quality Linear Alkylbenzene for the JUNO Experiment, Dewen Cao, et al., Nucl.Instrum.Meth.A 927 (2019) 230-235. https://doi.org/10.1016/j.nima.2019.01.077 https://arxiv.org/abs/1801.08363
(10) Densities, isobaric thermal expansion coefficients and isothermal compressibilities of linear alkylbenzene, Xiang Zhou, et al., Phys. Scr. 90 (2015) 055701. https://doi.org/10.1088/0031-8949/90/5/055701 https://arxiv.org/abs/1408.0877
(11) Rayleigh scattering of linear alkylbenzene in large liquid scintillator detectors, Xiang Zhou, et al., Rev. Sci. Instrum. 86 (2015) 073310. https://doi.org/10.1063/1.4927458 https://arxiv.org/abs/1504.00987
(12) Spectroscopic study of light scattering in linear alkylbenzene for liquid scintillator neutrino detectors, Xiang Zhou, et al., Eur. Phys. J. C 75 (2015) 545. https://doi.org/10.1140/epjc/s10052-015-3784-z https://arxiv.org/abs/1504.00986
PMT Instrumentation
(1) Design of the PMT underwater cascade implosion protection system for JUNO, M. He, et al., JINST 18 (2023) 02, P02013. https://doi.org/10.1088/1748-0221/18/02/P02013 https://arxiv.org/abs/2209.08441
(2) Database system for managing 20,000 20-inch PMTs at JUNO, J. Wang, et al., Nucl.Sci.Tech. 33 (2022) 24. https://doi.org/10.1007/s41365-022-01009-x
(3) A container-based facility for testing 20'000 20-inch PMTs for JUNO, B. Wonsak, et al., JINST 16 (2021) 08, T08001. https://doi.org/10.1088/1748-0221/16/08/T08001 https://arxiv.org/abs/2103.10193
(4) Gain and charge response of 20” MCP and dynode PMTs, H.Q. Zhang, et al., JINST 16 (2021) 08, T08009. https://doi.org/10.1088/1748-0221/16/08/T08009 https://arxiv.org/abs/2103.14822
(5) A quantitative approach to select PMTs for large detectors, L.J. Wen, et al., Nucl.Instrum.Meth.A 947 (2019) 162766. https://doi.org/10.1016/j.nima.2019.162766 https://arxiv.org/abs/1903.12595
(6) Comparison on PMT Waveform Reconstructions with JUNO Prototype, H.Q. Zhang, et al., JINST 14 (2019) 08, T08002. https://doi.org/10.1088/1748-0221/14/08/T08002 https://arxiv.org/abs/1905.03648
(7) A study of the new hemispherical 9-inch PMT, F. Luo, et al., JINST 14 (2019) 02, T02004. https://doi.org/10.1088/1748-0221/14/02/T02004 https://arxiv.org/abs/1801.02737
(8) Study on Relative Collection Efficiency of PMTs with Point Light, H.Q. Zhang, et al., RDTM 3 (2019) 20. https://doi.org/10.1007/s41605-019-0099-x https://arxiv.org/abs/1810.04550
(9) The study of linearity and detection efficiency for 20″ photomultiplier tube, A.B. Yang, et al., RDTM 3 (2019) 11. https://doi.org/10.1007/s41605-018-0088-5
(10) Signal Optimization with HV divider of MCP-PMT for JUNO, F.J. Luo, et al., Springer Proc.Phys. 213 (2018) 309-314. https://doi.org/10.1007/978-981-13-1316-5_58 https://arxiv.org/abs/1803.03746
(11) Large photocathode 20-inch PMT testing methods for the JUNO experiment, N. Anfimov, et al., JINST 12 (2017) 06, C06017. https://doi.org/10.1088/1748-0221/12/06/C06017 https://arxiv.org/abs/1705.05012
(12) Study of TTS for a 20-inch dynode PMT, D.H. Liao, et al., Chin.Phys.C 41 (2017) 7, 076001. https://doi.org/10.1088/1674-1137/41/7/076001
(13) PMT overshoot study for the JUNO prototype detector, F.J. Luo, et al., Chin.Phys.C 40 (2016) 9, 096002. https://doi.org/10.1088/1674-1137/40/9/096002 https://arxiv.org/abs/1602.06080
Small PMTs
(1) Study of the front-end signal for the 3-inch PMTs instrumentation in JUNO, Diru Wu, et al., Radiat Detect Technol Methods 6 (2022) 349 https://doi.org/10.1007/s41605-022-00324-6 https://arxiv.org/abs/2204.02612
(2) Mass production and characterization of 3-inch PMTs for the JUNO experiment, Chuanya Cao, et al., Nucl.Instrum.Meth.A 1005 (2021) 165347. https://doi.org/10.1016/j.nima.2021.165347 https://arxiv.org/abs/2102.11538
(3) CATIROC: an integrated chip for neutrino experiments using photomultiplier tubes, S. Conforti, et al., JINST 16 (2021) 05, P05010. https://doi.org/10.1088/1748-0221/16/05/P05010 https://arxiv.org/abs/2012.01565
(4) Characterization of 3-inch photomultiplier tubes for the JUNO central detector, Nan Li, et al., Radiat Detect Technol Methods 3 (2019) 6. https://doi.org/10.1007/s41605-018-0085-8
Veto Detectors
(1) The study of active geomagnetic shielding coils system for JUNO, G. Zhang, et al., JINST 16 (2021) 12, A12001. https://doi.org/10.1088/1748-0221/16/10/T10004 https://arxiv.org/abs/2106.09998
(2) Developing the radium measurement system for the water Cherenkov detector of the Jiangmen Underground Neutrino Observatory, L.F. Xie, et al., Nucl.Instrum.Meth.A 976 (2020) 164266. https://doi.org/10.1016/j.nima.2020.164266 https://arxiv.org/abs/1906.06895
(3) Study on the radon removal for the water system of Jiangmen Underground Neutrino Observatory, C. Guo, et al., Radiat Detect Technol Methods 2 (2018) 48. https://doi.org/10.1007/s41605-018-0077-8
(4) The development of 222Rn detectors for JUNO prototype, Y. P. Zhang,, et al., Radiat Detect Technol Methods 2 (2018) 5. https://doi.org/10.1007/s41605-017-0029-8 https://arxiv.org/abs/1710.03401
(5) Discriminating cosmic muons and radioactivity using a liquid scintillator fiber detector, Y.P. Zhang, et al., JINST 12 (2017) 03, P03015. https://doi.org/10.1088/1748-0221/12/03/P03015 https://arxiv.org/abs/1608.08307
Electronics and Trigger
(1) Embedded readout electronics R&D; for the large PMTs in the JUNO experiment, M.Bellatoa, et al., Nucl.Instrum.Meth.A 985 (2021) 164600. https://doi.org/10.1016/j.nima.2020.164600 https://arxiv.org/abs/2003.08339
(2) A 4 GHz phase locked loop design in 65 nm CMOS for the Jiangmen Underground Neutrino Observatory detector, N. Parkalian, et al., JINST 13 (2018)02, P02010. https://doi.org/10.1088/1748-0221/13/02/p02010
Calibration
(1) A Precise Method to Determine the Energy Scale and Resolution using Gamma Calibration Sources in a Liquid Scintillator Detector, Feiyang Zhang, et al., JINST 16 (2021) T08007. https://doi.org/10.1088/1748-0221/16/08/T08007 https://arxiv.org/abs/2106.06424
(2) The automatic calibration unit in JUNO, Jiaqi Hui, et al., JINST 16 (2021) 08, T08008. https://doi.org/10.1088/1748-0221/16/08/T08008 https://arxiv.org/abs/2104.02579
(3) Construction and Simulation Bias Study of The Guide Tube Calibration System for JUNO, Yuhang Guo, et al., JINST 16 (2021) T07005. https://doi.org/10.1088/1748-0221/16/07/T07005 https://arxiv.org/abs/2103.04602
(4) Cable loop calibration system for Jiangmen Underground Neutrino Observatory, Yuanyuan Zhang, et al., Nucl.Instrum.Meth.A 988 (2021) 164867. https://doi.org/10.1016/j.nima.2020.164867 https://arxiv.org/abs/2011.02183
(5) Design of the Guide Tube Calibration System for the JUNO experiment, Yuhang Guo, et al., JINST 14 (2019) 09, T09005. https://doi.org/10.1088/1748-0221/14/09/T09005 https://arxiv.org/abs/1905.02077
(6) Ultrasonic positioning system for the calibration of central detector, Guo-Lei Zhu, et al., Nucl.Sci.Tech. 30 (2019) 1, 5. https://doi.org/10.1007/s41365-018-0530-x
TAO
(1) Detector optimization to reduce the cosmogenic neutron backgrounds in the TAO experiment, Ruhui Li, et al., JINST 17 (2022) 09, P09024. https://iopscience.iop.org/article/10.1088/1748-0221/17/09/P09024 https://arxiv.org/abs/2206.01112
(2) Calibration Strategy of the JUNO-TAO Experiment, Hangkun Xu, et al., Eur.Phys.J.C 82 (2022) 1112. https://link.springer.com/article/10.1140/epjc/s10052-022-11069-3 https://arxiv.org/abs/2204.03256
(3) A liquid scintillator for a neutrino Detector working at -50 degree, Zhangquan Xie, et al., Nucl.Instrum.Meth.A 1009 (2021) 165459. https://doi.org/10.1016/j.nima.2021.165459 https://arxiv.org/abs/2012.11883
(4) Study of Silicon Photomultiplier Performance at Different Temperatures, N.Anfimov, et al., Nucl.Instrum.Meth.A 997 (2021) 165162. https://doi.org/10.1016/j.nima.2021.165162 https://arxiv.org/abs/2005.10665
(5) Reflectance of Silicon Photomultipliers in Linear Alkylbenzene, W. Wang, et al., Nucl.Instrum.Meth.A 973 (2020) 164171. https://doi.org/10.1016/j.nima.2020.164171 https://arxiv.org/abs/2002.04218
(6) Evaluation of the KLauS ASIC at low temperature, Wei Wang, et al., Nucl.Instrum.Meth.A 996 (2021) 165110. https://doi.org/10.1016/j.nima.2021.165110 https://arxiv.org/abs/2011.05643
Low Background
(1) A practical approach of high precision U and Th concentration measurement in acrylic, Chuanya Cao, et al., Nucl.Instrum.Meth.A 1004 (2021) 165377. https://doi.org/10.1016/j.nima.2021.165377 https://arxiv.org/abs/2011.06817
(2) Co-precipitation approach to measure amount of 238U in copper to sub-ppt level using ICP-MS, Ya-Yun Ding, Meng-Chao Liu, Jie Zhao, Wen-Qi Yan, Liang-Hong Wei, Zhi-Yong Zhang, Liang-Jian Wen, Nucl.Instrum.Meth.A 941 (2019) 162335. https://doi.org/10.1016/j.nima.2019.162335 https://arxiv.org/abs/2003.12229
(3) 222Rn contamination mechanisms on acrylic surfaces, M. Nastasi, et al., https://arxiv.org/abs/1911.04836
(4) Study on the large area MCP-PMT glass radioactivity reduction, Xuantong Zhang, et al., Nucl.Instrum.Meth.A 898 (2018) 67-71. https://doi.org/10.1016/j.nima.2018.05.008 https://arxiv.org/abs/1710.09965
Software Framework
(1) GDML based geometry management system for offline software in JUNO, Kaijie Li, et al., Nucl.Instrum.Meth.A 908 (2018) 43-48. https://doi.org/10.1016/j.nima.2018.08.008
(2) A ROOT Based Event Display Software for JUNO, Z. You, et al. JINST 13 (2018) 02, T02002. https://doi.org/10.1088/1748-0221/13/02/T02002 https://arxiv.org/abs/1712.07603
(3) Design and Development of JUNO Event Data Model, Teng Li, et al., Chin.Phys.C 41 (2017) 6, 066201. https://doi.org/10.1088/1674-1137/41/6/066201 https://arxiv.org/abs/1702.04100
Simulation
(1) A new optical model of a photomultiplier tube, Yaoguang Wang, Guofu Cao, Liangjian Wen, Yifang Wang, Eur.Phys.J.C 82 (2022) 4, 329. https://doi.org/10.1140/epjc/s10052-022-10288-y https://arxiv.org/abs/2204.02703
(2) Improving the Energy Resolution of the Reactor Antineutrino Energy Reconstruction with Positron Direction, Lianghong Wei, Liang Zhan, Jun Cao, Wei Wang, RDTM, 4 (2020) 356–361. https://doi.org/10.1007/s41605-020-00191-z https://arxiv.org/abs/2005.05034
(3) A complete optical model for liquid-scintillator detectors, Yan Zhang, Ze-Yuan Yu, Xin-Ying Li, Zi-Yan Deng, Liang-Jian Wen, Nucl.Instrum.Meth.A 967 (2020) 163860. https://doi.org/10.1016/j.nima.2020.163860 https://arxiv.org/abs/2003.12212
(4) A semi-analytical energy response model for low-energy events in JUNO, P. Kampmann, Y. Cheng, L. Ludhova, JINST 15 (2020) 10, P10007. https://doi.org/10.1088/1748-0221/15/10/P10007 https://arxiv.org/abs/2006.03461
(5) Capability of detecting low energy events in JUNO Central Detector, X. Fang, et al., JINST 15 (2020) 03, P03020. https://doi.org/10.1088/1748-0221/15/03/P03020 https://arxiv.org/abs/1912.01864
(6) Fast Muon Simulation in the JUNO Central Detector, Tao Lin, et al., Chin.Phys.C 40 (2016) 8, 086201. https://doi.org/10.1088/1674-1137/40/8/086201 https://arxiv.org/abs/1602.00056
Reconstruction
(1) Improving the machine learning based vertex reconstruction for large liquid scintillator detectors with multiple types of PMTs, Zi-Yuan Li, et al., https://arxiv.org/abs/2205.04039
(2) Reconstruction of Muon Bundle in the JUNO Central Detector, Cheng-Feng Yang, et al., https://arxiv.org/abs/2201.11321
(3) Muon reconstruction with a convolutional neural network in the JUNO detector, Yan Liu, et al., Rad.Det.Tech.Meth. 5 (2021) 3, 364-372. https://doi.org/10.1007/s41605-021-00259-4 https://arxiv.org/abs/2103.11939
(4) Vertex and energy reconstruction in JUNO with machine learning methods, Zhen Qian, et al., Nucl.Instrum.Meth.A 1010 (2021) 165527. https://doi.org/10.1016/j.nima.2021.165527 https://arxiv.org/abs/2101.04839
(5) Improving the energy uniformity for large liquid scintillator detectors, Guihong Huang, et al., Nucl.Instrum.Meth.A 1001 (2021) 165287. https://doi.org/10.1016/j.nima.2021.165287 https://arxiv.org/abs/2102.03736
(6) Event vertex and time reconstruction in large-volume liquid scintillator detectors, Zi-Yuan Li, et al., Nucl.Sci.Tech. 32 (2021) 5, 49. https://doi.org/10.1007/s41365-021-00885-z https://arxiv.org/abs/2101.08901
(7) Particle Identification at MeV Energies in JUNO, H. Rebber, L. Ludhova, B. Wonsak and Y. Xu, JINST 16 (2021) 01, P01016. https://doi.org/10.1088/1748-0221/16/01/P01016 https://arxiv.org/abs/2007.02687
(8) Comparison on PMT Waveform Reconstructions with JUNO Prototype, H.Q. Zhang, et al., JINST 14 (2019) 08, T08002. https://doi.org/10.1088/1748-0221/14/08/T08002 https://arxiv.org/abs/1905.03648
(9) A new method of energy reconstruction for large spherical liquid scintillator detectors, W. Wu, M. He, X. Zhou and H. Qiao, JINST 14 (2019) 03, P03009. https://doi.org/10.1088/1748-0221/14/03/P03009 https://arxiv.org/abs/1812.01799
(10) Muon Tracking with the fastest light in the JUNO Central Detector, Kun Zhang, Miao He, Weidong Li, Jilei Xu, Radiat Detect Technol Methods 2 (2018) 13. https://doi.org/10.1007/s41605-018-0040-8 https://arxiv.org/abs/1803.10407
(11) A vertex reconstruction algorithm in the central detector of JUNO, Q. Liu, et al., JINST 13 (2018) 09, T09005. https://doi.org/10.1088/1748-0221/13/09/T09005 https://arxiv.org/abs/1803.09394
(12) Muon reconstruction with a geometrical model in JUNO C. Genster, et al., JINST 13 (2018) 03, T03003. https://doi.org/10.1088/1748-0221/13/03/T03003 https://arxiv.org/abs/1906.01912
(13) Charge reconstruction in large-area photomultipliers, M. Grassi, et al., JINST 13 (2018) 02, P02008. https://doi.org/10.1088/1748-0221/13/02/P02008 https://arxiv.org/abs/1801.08690
