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- 2019
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Journal article (peer-reviewed)
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| 2. |
- Peng, Liming, et al.
(author)
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Phase-modulated mechanical and thermoelectric properties of Ag2S1-x Tex ductile semiconductors
- 2022
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In: Journal of Materiomics. - : Elsevier. - 2352-8478 .- 2352-8486. ; 8:3, s. 656-661
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Journal article (peer-reviewed)abstract
- By virtue of the excellent plasticity and tunable transport properties, Ag2S-based materials demonstrate an intriguing prospect for flexible or hetero-shaped thermoelectric applications. Among them, Ag(2)S1-xTex exhibits rich and interesting variations in crystal structure, mechanical and thermoelectric transport properties. However, Te alloying obviously introduces extremely large order-disorder distributions of cations and anions, leading to quite complicated crystal structures and thermoelectric properties. Detailed composition-structure-performance correlation of Ag2S1-xTex still remains to be established. In this work, we designed and prepared a series of Ag2S1-xTex (x = 0-0.3) materials with low Te content. We discovered that the monoclinic-to-cubic phase transition occurs around x = 0.16 at room temperature. Te alloying plays a similar role as heating in facilitating this monoclinic-to-cubic phase transition, which is analyzed based on the thermodynamic principles. Compared with the monoclinic counterparts, the cubic-structured phases are more ductile and softer in mechanical properties. In addition, the cubic phases show a degenerately semiconducting behavior with higher thermoelectric performance. A maximum zT = 0.8 at 600 K and bending strain larger than 20% at room temperature were obtained in Ag2S0.7Te0.3. This work provides a useful guidance for designing Ag2S-based alloys with enhanced plasticity and high thermoelectric performance.
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| 3. |
- Wang, Zhenwu, et al.
(author)
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A novel bayesian network-based ensemble classifier chains for multi-label classification
- 2024
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In: Complex & Intelligent Systems. - : Springer Berlin/Heidelberg. - 2199-4536 .- 2198-6053.
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Journal article (peer-reviewed)abstract
- In this paper, we address the challenges of random label ordering and limited interpretability associated with Ensemble Classifier Chains (ECC) by introducing a novel ECC method, ECC-MOO&BN, which integrates Bayesian Networks (BN) and Multi-Objective Optimization (MOO). This approach is designed to concurrently overcome these ECC limitations. The ECC-MOO&BN method focuses on extracting diverse and interpretable label orderings for the ECC classifier. We initiated this process by employing mutual information to investigate label relationships and establish the initial structures of the BN. Subsequently, an enhanced NSGA-II algorithm was applied to develop a series of Directed Acyclic Graphs (DAGs) that effectively balance the likelihood and complexity of the BN structure. The rationale behind using the MOO method lies in its ability to optimize both complexity and likelihood simultaneously, which not only diversifies DAG generation but also helps avoid overfitting during the production of label orderings. The DAGs, once sorted topologically, yielded a series of label orderings, which were then seamlessly integrated into the ECC framework for addressing multi-label classification (MLC) problems. Experimental results show that when benchmarked against eleven leading-edge MLC algorithms, our proposed method achieves the highest average ranking across seven evaluation criteria on nine out of thirteen MLC datasets. The results of the Friedman test and Nemenyi test also indicate that the performance of the proposed method has a significant advantage compared to other algorithms.
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| 4. |
- Yang, Qingyu, et al.
(author)
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Flexible thermoelectrics based on ductile semiconductors
- 2022
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In: Science. - : American Association for the Advancement of Science (AAAS). - 0036-8075 .- 1095-9203. ; 377, s. 854-858
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Journal article (peer-reviewed)abstract
- Flexible thermoelectrics provide a different solution for developing portable and sustainable flexiblepower supplies. The discovery of silver sulfide–based ductile semiconductors has driven a shift in thepotential for flexible thermoelectrics, but the lack of good p-type ductile thermoelectric materials hasrestricted the reality of fabricating conventional cross-plane p-shaped flexible devices. We report aseries of high-performance p-type ductile thermoelectric materials based on the composition-performance phase diagram in AgCu(Se,S,Te) pseudoternary solid solutions, with high figure-of-meritvalues (0.45 at 300 kelvin and 0.68 at 340 kelvin) compared with other flexible thermoelectricmaterials. We further demonstrate thin and flexible p-shaped devices with a maximum normalizedpower density that reaches 30 mW cm−2 K−2. This output is promising for the use of flexiblethermoelectrics in wearable electronics.
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| 5. |
- Abbasi, Rasha, et al.
(author)
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IceCube search for neutrinos from GRB 221009A
- 2023
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In: Proceedings of 38th International Cosmic Ray Conference (ICRC 2023). - : Sissa Medialab Srl.
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Conference paper (peer-reviewed)abstract
- GRB 221009A is the brightest Gamma Ray Burst (GRB) ever observed. The observed extremelyhigh flux of high and very-high-energy photons provide a unique opportunity to probe the predictedneutrino counterpart to the electromagnetic emission. We have used a variety of methods to searchfor neutrinos in coincidence with the GRB over several time windows during the precursor, promptand afterglow phases of the GRB. MeV scale neutrinos are studied using photo-multiplier ratescalers which are normally used to search for galactic core-collapse supernovae neutrinos. GeVneutrinos are searched starting with DeepCore triggers. These events don’t have directionallocalization, but instead can indicate an excess in the rate of events. 10 GeV - 1 TeV and >TeVneutrinos are searched using traditional neutrino point source methods which take into accountthe direction and time of events with DeepCore and the entire IceCube detector respectively. The>TeV results include both a fast-response analysis conducted by IceCube in real-time with timewindows of T0 − 1 to T0 + 2 hours and T0 ± 1 day around the time of GRB 221009A, as well asan offline analysis with 3 new time windows up to a time window of T0 − 1 to T0 + 14 days, thelongest time period we consider. The combination of observations by IceCube covers 9 ordersof magnitude in neutrino energy, from MeV to PeV, placing upper limits across the range forpredicted neutrino emission.
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| 6. |
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| 7. |
- Xu, Shiqi, et al.
(author)
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Imaging Dynamics Beneath Turbid Media via Parallelized Single-Photon Detection
- 2022
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In: Advanced Science. - : Wiley. - 2198-3844. ; 9:24
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Journal article (peer-reviewed)abstract
- Noninvasive optical imaging through dynamic scattering media has numerous important biomedical applications but still remains a challenging task. While standard diffuse imaging methods measure optical absorption or fluorescent emission, it is also well-established that the temporal correlation of scattered coherent light diffuses through tissue much like optical intensity. Few works to date, however, have aimed to experimentally measure and process such temporal correlation data to demonstrate deep-tissue video reconstruction of decorrelation dynamics. In this work, a single-photon avalanche diode array camera is utilized to simultaneously monitor the temporal dynamics of speckle fluctuations at the single-photon level from 12 different phantom tissue surface locations delivered via a customized fiber bundle array. Then a deep neural network is applied to convert the acquired single-photon measurements into video of scattering dynamics beneath rapidly decorrelating tissue phantoms. The ability to reconstruct images of transient (0.1–0.4 s) dynamic events occurring up to 8 mm beneath a decorrelating tissue phantom with millimeter-scale resolution is demonstrated, and it is highlighted how the model can flexibly extend to monitor flow speed within buried phantom vessels.
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| 8. |
- Xu, Shiqi, et al.
(author)
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Transient Motion Classification Through Turbid Volumes via Parallelized Single-Photon Detection and Deep Contrastive Embedding
- 2022
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In: Frontiers in Neuroscience. - : Frontiers Media SA. - 1662-4548 .- 1662-453X. ; 16
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Journal article (peer-reviewed)abstract
- Fast noninvasive probing of spatially varying decorrelating events, such as cerebral blood flow beneath the human skull, is an essential task in various scientific and clinical settings. One of the primary optical techniques used is diffuse correlation spectroscopy (DCS), whose classical implementation uses a single or few single-photon detectors, resulting in poor spatial localization accuracy and relatively low temporal resolution. Here, we propose a technique termed Classifying Rapid decorrelation Events via Parallelized single photon dEtection (CREPE), a new form of DCS that can probe and classify different decorrelating movements hidden underneath turbid volume with high sensitivity using parallelized speckle detection from a 32 × 32 pixel SPAD array. We evaluate our setup by classifying different spatiotemporal-decorrelating patterns hidden beneath a 5 mm tissue-like phantom made with rapidly decorrelating dynamic scattering media. Twelve multi-mode fibers are used to collect scattered light from different positions on the surface of the tissue phantom. To validate our setup, we generate perturbed decorrelation patterns by both a digital micromirror device (DMD) modulated at multi-kilo-hertz rates, as well as a vessel phantom containing flowing fluid. Along with a deep contrastive learning algorithm that outperforms classic unsupervised learning methods, we demonstrate our approach can accurately detect and classify different transient decorrelation events (happening in 0.1–0.4 s) underneath turbid scattering media, without any data labeling. This has the potential to be applied to non-invasively monitor deep tissue motion patterns, for example identifying normal or abnormal cerebral blood flow events, at multi-Hertz rates within a compact and static detection probe.
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| 9. |
- Yang, Haibo, et al.
(author)
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Coupling Downscaling and Calibrating Methods for Generating High-Quality Precipitation Data with Multisource Satellite Data in the Yellow River Basin
- 2024
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In: Remote Sensing. - 2072-4292. ; 16:8
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Journal article (peer-reviewed)abstract
- Remote sensing precipitation data have the characteristics of wide coverage and revealing spatiotemporal information, but their spatial resolution is low. The accuracy of the data is obviously different in different study areas and hydrometeorological conditions. This study evaluated four precipitation products in the Yellow River basin from 2001 to 2019, constructed the optimal combined product, conducted downscaling with various machine algorithms, and performed corrections using meteorological station precipitation data to analyze the spatiotemporal trends of precipitation. The results showed that (1) GPM and MSWEP had the best four evaluation indicators, with R2 values of 0.93 and 0.90, respectively, and the smallest FSE and RMSE, with a BIAS close to 0. A high-precision mixed precipitation dataset, GPM-MSWEP, was constructed. (2) Among the three methods, the downscaling results of DFNN showed higher accuracy. (3) The results, after correction with GWR, could more effectively enhance the accuracy of the data. (4) Precipitation in the Yellow River Basin showed a decreasing trend in January, September, and December, while it exhibited an increasing trend in other months and seasons, with 2002 and 2016 being points of abrupt change. This study provides a reference for the production of high-precision satellite precipitation products in the Yellow River basin.
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| 10. |
- You, Yintao, et al.
(author)
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An organic multilevel non-volatile memory device based on multiple independent switching modes
- 2014
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In: Organic electronics. - : Elsevier BV. - 1566-1199 .- 1878-5530. ; 15:9, s. 1983-1989
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Journal article (peer-reviewed)abstract
- The demand for higher data density memory structures is greater today than ever before. Multilevel resistive organic memory devices (OMD) provide an ideal solution, in being easily fabricated, cost-effective and at the same time promising high storage capacity. However, conventional methods for multilevel OMDs impose demanding requirements on material properties and attain only limited performance. We hereby provide an alternative design concept that combines multiple switching modes in one device to realize multilevel function. The device possesses a simple structure by using a ferroelectric phase-separated blend as the active layer. Two switching modes, the ferroelectric switching and the metallic filament switching, are realized simultaneously in this device, and enable a ternary storage function. The cross-section scanning electron microscope (SEM) images provide a strong evidence of the formation and annihilation of the metallic filament.
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