Dongguan University of Technology

About: Dongguan University of Technology is a education organization based out in Dongguan, China. It is known for research contribution in the topics: Catalysis & Computer science. The organization has 3622 authors who have published 4281 publications receiving 52685 citations.

Observation of Electron-Antineutrino Disappearance at Daya Bay

Abstract: The Daya Bay Reactor Neutrino Experiment has measured a nonzero value for the neutrino mixing angle θ13 with a significance of 5.2 standard deviations. Antineutrinos from six 2.9 GW_(th) reactors were detected in six antineutrino detectors deployed in two near (flux-weighted baseline 470 m and 576 m) and one far (1648 m) underground experimental halls. With a 43 000 ton–GW_(th)–day live-time exposure in 55 days, 10 416 (80 376) electron-antineutrino candidates were detected at the far hall (near halls). The ratio of the observed to expected number of antineutrinos at the far hall is R=0.940± 0.011(stat.)±0.004(syst.). A rate-only analysis finds sin^22θ_(13)=0.092±0.016(stat.)±0.005(syst.) in a three-neutrino framework.

Neutrino Physics with JUNO

Abstract: The Jiangmen Underground Neutrino Observatory (JUNO), a 20 kton multi-purpose underground liquid scintillator detector, was proposed with the determination of the neutrino mass hierarchy (MH) as a primary physics goal. The excellent energy resolution and the large fiducial volume anticipated for the JUNO detector offer exciting opportunities for addressing many important topics in neutrino and astro-particle physics. In this document, we present the physics motivations and the anticipated performance of the JUNO detector for various proposed measurements. Following an introduction summarizing the current status and open issues in neutrino physics, we discuss how the detection of antineutrinos generated by a cluster of nuclear power plants allows the determination of the neutrino MH at a 3–4σ significance with six years of running of JUNO. The measurement of antineutrino spectrum with excellent energy resolution will also lead to the precise determination of the neutrino oscillation parameters ${\mathrm{sin}}^{2}{\theta }_{12}$, ${\rm{\Delta }}{m}_{21}^{2}$, and $| {\rm{\Delta }}{m}_{{ee}}^{2}| $ to an accuracy of better than 1%, which will play a crucial role in the future unitarity test of the MNSP matrix. The JUNO detector is capable of observing not only antineutrinos from the power plants, but also neutrinos/antineutrinos from terrestrial and extra-terrestrial sources, including supernova burst neutrinos, diffuse supernova neutrino background, geoneutrinos, atmospheric neutrinos, and solar neutrinos. As a result of JUNO's large size, excellent energy resolution, and vertex reconstruction capability, interesting new data on these topics can be collected. For example, a neutrino burst from a typical core-collapse supernova at a distance of 10 kpc would lead to ∼5000 inverse-beta-decay events and ∼2000 all-flavor neutrino–proton ES events in JUNO, which are of crucial importance for understanding the mechanism of supernova explosion and for exploring novel phenomena such as collective neutrino oscillations. Detection of neutrinos from all past core-collapse supernova explosions in the visible universe with JUNO would further provide valuable information on the cosmic star-formation rate and the average core-collapse neutrino energy spectrum. Antineutrinos originating from the radioactive decay of uranium and thorium in the Earth can be detected in JUNO with a rate of ∼400 events per year, significantly improving the statistics of existing geoneutrino event samples. Atmospheric neutrino events collected in JUNO can provide independent inputs for determining the MH and the octant of the ${\theta }_{23}$ mixing angle. Detection of the (7)Be and (8)B solar neutrino events at JUNO would shed new light on the solar metallicity problem and examine the transition region between the vacuum and matter dominated neutrino oscillations. Regarding light sterile neutrino topics, sterile neutrinos with ${10}^{-5}\,{{\rm{eV}}}^{2}\lt {\rm{\Delta }}{m}_{41}^{2}\lt {10}^{-2}\,{{\rm{eV}}}^{2}$ and a sufficiently large mixing angle ${\theta }_{14}$ could be identified through a precise measurement of the reactor antineutrino energy spectrum. Meanwhile, JUNO can also provide us excellent opportunities to test the eV-scale sterile neutrino hypothesis, using either the radioactive neutrino sources or a cyclotron-produced neutrino beam. The JUNO detector is also sensitive to several other beyondthe-standard-model physics. Examples include the search for proton decay via the $p\to {K}^{+}+\bar{ u }$ decay channel, search for neutrinos resulting from dark-matter annihilation in the Sun, search for violation of Lorentz invariance via the sidereal modulation of the reactor neutrino event rate, and search for the effects of non-standard interactions. The proposed construction of the JUNO detector will provide a unique facility to address many outstanding crucial questions in particle and astrophysics in a timely and cost-effective fashion. It holds the great potential for further advancing our quest to understanding the fundamental properties of neutrinos, one of the building blocks of our Universe.

Neutrino Physics with JUNO

Abstract: The Jiangmen Underground Neutrino Observatory (JUNO), a 20 kton multi-purpose underground liquid scintillator detector, was proposed with the determination of the neutrino mass hierarchy as a primary physics goal. It is also capable of observing neutrinos from terrestrial and extra-terrestrial sources, including supernova burst neutrinos, diffuse supernova neutrino background, geoneutrinos, atmospheric neutrinos, solar neutrinos, as well as exotic searches such as nucleon decays, dark matter, sterile neutrinos, etc. We present the physics motivations and the anticipated performance of the JUNO detector for various proposed measurements. By detecting reactor antineutrinos from two power plants at 53-km distance, JUNO will determine the neutrino mass hierarchy at a 3-4 sigma significance with six years of running. The measurement of antineutrino spectrum will also lead to the precise determination of three out of the six oscillation parameters to an accuracy of better than 1\%. Neutrino burst from a typical core-collapse supernova at 10 kpc would lead to ~5000 inverse-beta-decay events and ~2000 all-flavor neutrino-proton elastic scattering events in JUNO. Detection of DSNB would provide valuable information on the cosmic star-formation rate and the average core-collapsed neutrino energy spectrum. Geo-neutrinos can be detected in JUNO with a rate of ~400 events per year, significantly improving the statistics of existing geoneutrino samples. The JUNO detector is sensitive to several exotic searches, e.g. proton decay via the $p\to K^++\bar u$ decay channel. The JUNO detector will provide a unique facility to address many outstanding crucial questions in particle and astrophysics. It holds the great potential for further advancing our quest to understanding the fundamental properties of neutrinos, one of the building blocks of our Universe.

Improved Deep Embedded Clustering with Local Structure Preservation

Abstract: Deep clustering learns deep feature representations that favor clustering task using neural networks. Some pioneering work proposes to simultaneously learn embedded features and perform clustering by explicitly defining a clustering oriented loss. Though promising performance has been demonstrated in various applications, we observe that a vital ingredient has been overlooked by these work that the defined clustering loss may corrupt feature space, which leads to non-representative meaningless features and this in turn hurts clustering performance. To address this issue, in this paper, we propose the Improved Deep Embedded Clustering (IDEC) algorithm to take care of data structure preservation. Specifically, we manipulate feature space to scatter data points using a clustering loss as guidance. To constrain the manipulation and maintain the local structure of data generating distribution, an under-complete autoencoder is applied. By integrating the clustering loss and autoencoder’s reconstruction loss, IDEC can jointly optimize cluster labels assignment and learn features that are suitable for clustering with local structure preservation. The resultant optimization problem can be effectively solved by mini-batch stochastic gradient descent and backpropagation. Experiments on image and text datasets empirically validate the importance of local structure preservation and the effectiveness of our algorithm.

Fe-doped mayenite electride composite with 2D reduced Graphene Oxide: As a non-platinum based, highly durable electrocatalyst for Oxygen Reduction Reaction.

Abstract: Since the last decades, non-precious metal catalysts (NPMC), especially iron based electrocatalysts show sufficient activity, potentially applicant in oxygen reduction reaction (ORR), however they only withstand considerable current densities at low operating potentials. On the other hand iron based electrocatalysts are not stable at elevated cathode potentials, which is essential for high energy competence, and its remains difficult to deal. Therefore, via this research a simple approach is demonstrated that allows synthesis of nanosize Fe-doped mayenite electride, [Ca24Al28O64]4+·(e−)4 (can also write as, C12A7−xFex:e−, where doping level, x = 1) (thereafter, Fe-doped C12A7:e−), consist of abundantly available elements with gram level powder material production, based on simple citrate sol-gel method. The maximum achieved conductivity of this first time synthesized Fe-doped C12A7:e− composite materials was 249 S/cm. Consequently, Fe-doped C12A7:e− composite is cost-effective, more active and highly durable precious-metal free electrocatalyst, with 1.03 V onset potential, 0.89 V (RHE) half-wave potential, and ~5.9 mA/cm2 current density, which is higher than benchmark 20% Pt/C (5.65 mA/cm2, and 0.84 V). The Fe-doped C12A7:e− has also higher selectivity for desired 4e− pathway, and more stable than 20 wt% Pt/C electrode with higher immunity towards methanol poisoning. Fe-doped C12A7:e− loses was almost zero of its original activity after passing 11 h compared to the absence of methanol case, indicates that to introduce methanol has almost negligible consequence for ORR performance, which makes it highly desirable, precious-metal free electrocatalyst in ORR. This is primarily described due to coexistence of Fe-doped C12A7:e− related active sites with reduced graphene oxide (rGO) with pyridinic-nitrogen, and their strong coupling consequence along their porous morphology textures. These textures assist rapid diffusion of molecules to catalyst active sites quickly. In real system maximum power densities reached to 243 and 275 mW/cm2 for Pt/C and Fe-doped C12A7:e− composite, respectively.