| 1. |
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- 2019
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Tidskriftsartikel (refereegranskat)
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| 2. |
- Wang, Wei, 1995-, et al.
(författare)
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Mesoporous Ni-N-C as an efficient electrocatalyst for reduction of CO2 into CO in a flow cell
- 2022
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Ingår i: Applied Materials Today. - : Elsevier BV. - 2352-9407. ; 29
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Tidskriftsartikel (refereegranskat)abstract
- Recently, nitrogen-doped porous carbon materials containing non-precious metals (termed “M-N-C”) have formed a group of functional materials to replace precious metal-based catalysts for electrochemical CO2 reduction reaction. Here, a series of mesoporous Ni-N-C electrocatalysts (termed “mp-Ni-N-Cs”) were prepared via a gel-template method, and could effectively reduce CO2 into CO in a flow cell. The result in gas sorption tests exhibited a typical mesoporous structure, which would bring both sufficient exposed active sites and convenient mass transfer channels. Electrochemical tests showed excellent performance at an applied potential of -1.3 V (vs. RHE), e.g., a CO Faradaic efficiency (FECO) of 95.85 %, and a CO reduction current (jCO) of -21.29 mA cm−2. Significantly, its FECO exceeded 93 % in a wide range of potentials from -1.0 to -1.5 V, showing great tolerance to fluctuation in potential. The mp-Ni-N-C electrocatalysts have satisfactory features in terms of catalytic activity, facile preparation, and economic feasibility, and will offer a valuable reference for next exploration of cost-effective electrocatalysts for CO2 conversion.
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| 3. |
- Wang, Wei, et al.
(författare)
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Metal-Free SeBN Ternary-Doped Porous Carbon as Efficient Electrocatalysts for CO2 Reduction Reaction
- 2022
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Ingår i: ACS Applied Energy Materials. - : American Chemical Society (ACS). - 2574-0962. ; 5:9, s. 10518-10525
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Tidskriftsartikel (refereegranskat)abstract
- Cost-effective heteroatom-doped porous carbons are considered promising electrocatalysts for CO2 reduction reaction (CO2RR). Traditionally porous carbons with N doping or N/X codoping (X denotes the second type of heteroatom) have been widely studied, leaving ternary doping a much less studied yet exciting topic to be explored. Herein, a series of electrocatalysts based on metal-free Se, B, and N ternary-doped porous carbons (termed “SeBN-Cs”) were synthesized and tested as metal-free electrocatalysts in CO2RR. Our study indicates that the major product of CO2RR on the SeBN-C electrocatalysts was CO with a small fraction (<5%) of H2 as the byproduct. The optimal electrocatalyst sample SeBN-C-1100 prepared at 1100 °C exhibits a high CO selectivity with a Faradaic efficiency of CO reaching 95.2%. After 10 h of continuous electrolysis operation, the Faradaic efficiency and the current density are maintained high at 97.6 and 84.7% of the initial values, respectively, indicative of a long-term operational stability. This study provides an excellent reference to deepen our understanding of the properties and functions of multi-heteroatom-doped porous carbon electrocatalysts in CO2RR.
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| 4. |
- Wang, Zhenwu, et al.
(författare)
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A novel bayesian network-based ensemble classifier chains for multi-label classification
- 2024
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Ingår i: Complex & Intelligent Systems. - : Springer Berlin/Heidelberg. - 2199-4536 .- 2198-6053.
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Tidskriftsartikel (refereegranskat)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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| 5. |
- Xu, Shiqi, et al.
(författare)
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Imaging Dynamics Beneath Turbid Media via Parallelized Single-Photon Detection
- 2022
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Ingår i: Advanced Science. - : Wiley. - 2198-3844. ; 9:24
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Tidskriftsartikel (refereegranskat)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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| 6. |
- Xu, Shiqi, et al.
(författare)
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Transient Motion Classification Through Turbid Volumes via Parallelized Single-Photon Detection and Deep Contrastive Embedding
- 2022
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Ingår i: Frontiers in Neuroscience. - : Frontiers Media SA. - 1662-4548 .- 1662-453X. ; 16
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Tidskriftsartikel (refereegranskat)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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| 7. |
- Zhang, Qiyue, et al.
(författare)
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Integrated CFD and MBD methods for dynamic performance analysis of a high-speed train transitioning through varied windbreak corridor designs
- 2024
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Ingår i: Journal of Wind Engineering and Industrial Aerodynamics. - 0167-6105. ; 250
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Tidskriftsartikel (refereegranskat)abstract
- With increasing train speeds, the wind environment along routes has become complex, variable, and extreme. Constructing windbreak facilities is an effective strategy to enhance train operational safety in windy zones. Various windbreak designs exhibit notable differences in improving train dynamic performance, and economic considerations are also crucial. Utilizing the non-constant compressible Reynolds time-averaged equation URANS (Unsteady Reynold-averaged Navier–Stokes) alongside the shear-stress transport (SST) k-ω turbulence model, this study simulates the non-constant aerodynamic characteristics of a 350 km/h high-speed train traversing through different forms of windbreak corridors in a 30 m/s wind zone. The train's dynamic response was captured using a combined CFD–MBD (Computational Fluid Dynamics and Multi-Body Dynamics) offline time-domain simulation, the accuracy of which was verified experimentally. Results indicate that vortices of various positions and shapes form in the flow field along the windbreak corridor depending on the size of the openings. Using the no-windbreak corridor (Case 1) and the fully enclosed corridor (Case 4) as control groups, it was observed that smaller openings lead to more stable airflow, enhancing peak damping and fluctuation effects, albeit with varying stages of aerodynamic load fluctuation. The 1/3-opening windbreak corridor (Case 3) effectively mitigated the sudden aerodynamic load changes at the wind zone transition of the 2/3-opening windbreak corridor (Case 2), with the primary fluctuation area in Case 3 being the wind section. Dynamic analyses revealed that Case 2 exhibited insufficient lateral aerodynamic performance, raising derailment concerns. In contrast, Case 3 ensured travel safety and comfort effectively, while Case 4 offered excessive protective capacity. This study's findings serve as a valuable reference for designing windbreak corridors and ensuring the safe operation of trains in windy regions.
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| 8. |
- Zhou, Shiqi, 1994-, et al.
(författare)
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CO2-philic poly(ionic liquid)-assisted local enrichment strategy for enhancedelectrochemical CO2 reduction
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Electrochemical CO2 reduction reaction (ECO2RR) to produce valuable chemicals and fuels is a promising way to make use of excessive CO2 as one of the major green-house gases debatably responsible for climate change. The chemically inert feature of CO2 molecules makes the first-step elementary reaction with one electron reduction challenging in thermodynamics, leading to a high overpotential for this step and the overall ECO2RR as well. Herein, we reported the successful fabrication of CO2-philic PIL-modified Au model catalyst with enhanced ECO2RR performance by a local CO2 enrichment strategy. The modified gas diffusion electrode exhibited ~ 100% Faradaic efficiency for CO2-to-CO conversion (FECO) in a wide potential window of -0.2 ~ -1.0 V (versus reversible hydrogen electrode. RHE) with pure CO2 feeding, and notablymaintained the FECO > 90% even at a low CO2 concentration of 20 % vol..
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| 9. |
- Zhou, Shiqi, 1994-, et al.
(författare)
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Engineering interfacial hydrogen-bond network via cage-enabled soft confinement of Pt for facilitated hydrogen evolution kinetics
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- The sluggish HER kinetics under alkaline conditions largely limit the development of alkaline water electrolysis. Decades of efforts have been reported to elucidate the origin of the pH dependence of HER kinetics and facilitate the alkaline HER kinetics. Apart from the widely concerned thermodynamic factors, the electrode process also depends unignorably on the kinetics of the electrochemical interface. Herein, we presented the facilitated HER kinetics by introducing porous amine cage-enabled confinement to Ptcatalyst to engineer the interface between the Pt surface and the aqueous electrolyte. In situ electrochemical surface-enhanced Raman spectra (SERS) measurements and ab initio molecular dynamics (AIMD) simulation jointly unveiled the fundamental interfacial interaction between water and cage that its -NH- moiety largely reduces the rigidity of the net of interfacial water H-bonds at negative HER potentials, which makes the net flexible enough to reorganize for better charge transfer. Our in-depth investigation pinpointed that the -NH- moiety acted as a proton pump and generated hydroxide transfer by forming and breaking H-bonds with interfacial water, refreshing the reactive water layer on the Pt surface. Our results address the crucial role of controllable interfacial kinetics during electrocatalytic reactions, and our strategy of establishing a soft-confining interfacial regulator offers a promising roadmap for manipulating electrocatalytic interfacial kinetics.
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| 10. |
- Zhou, Shiqi, 1994-
(författare)
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Multiscale interfacial engineering of heterogeneous electrocatalysts : From structural design to mechanistic study
- 2024
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- In a typical heterogeneous electrocatalytic reaction, for the given active sites, the electronic structure plays a determining role in electron transfer between the active sites and reactant molecules, which impacts the reaction efficiency. Besides the electronic properties of the electrocatalysts, the reaction interface at which the charge transfer occurs plays an important role in the reaction kinetics. Moreover, the accessibility of the active sites to the reactant molecules also affects the reaction efficiency. However, a well-balanced effective strategy for electronic structure optimization that improves not only the activity but also stability and cost-effectiveness is needed. Besides, a robust model specifically tailored to investigate the kinetics of the electrocatalytic reaction is required to exclude the interference of thermodynamic factors. A feasible characterization technique for probing the complex interfacial process is also required. To address these remaining challenges in the three aspects above, this thesis proposed the strategies to optimize the electrocatalytic reaction processes as follows: (1) Tuning the electronic structure of the active sites by engineering coordination environment and introducing strain effect. Specifically, Ni single atom was constructed to engineer the coordination environment, and the electrocatalytic performance with the tuned electronic structure was examined towards hydrazine oxidation reaction. The strain effect was created by introducing Cu single atom to BiOCl substrate, and the optimized electronic structure was investigated;(2) Optimizing the interfacial HER kinetics targeted by proposing a specific Pt model catalyst with a channel-opening modifier. The interfacial water structure was studied by in situ surface-enhanced Raman technique, and the role of this promoting modifier was elucidated by ab initio molecular dynamic simulation;(3) Improving the local concentration of CO2 for electrochemical CO2 reduction reaction with a poly(ionic liquid) modifier, with Au as the model catalyst and the targeted characterization techniques.
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