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Synergy of in situ generated Cu0 and Lewis acid sites for efficient and selective hydrodeoxygenation of vanillin to 4-methylguaiacol 认领 引用
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作者 Tingting Wang Jinwen Hu +9 位作者 Wenzhe Shang Siying Zhou Yueying Zhao Bo Pang Jie Lu Jian Du Yehan Tao Yanna Lv Chenglong Fu Haisong Wang 《Journal of Energy Chemistry》 SCIE EI CAS CSCD 2026年第3期781-790,共10页
Hydrodeoxygenation represents a promising route for upgrading lignin-derived bio-oil into value-added fine chemicals,but it is challenging to obtain high yield and selectivity due to the varying dissociation energy of... Hydrodeoxygenation represents a promising route for upgrading lignin-derived bio-oil into value-added fine chemicals,but it is challenging to obtain high yield and selectivity due to the varying dissociation energy of different oxygen-containing functional groups.Here,we strategically engineered a robust Cu-based catalyst for catalyzing vanillin to 4-methylguaiacol in a H-donor solvent under an inert N2 atmosphere,achieving simultaneously>99.9%conversion and near-theoretical selectivity(99.6%),as well as excellent cycling durability.First-principles calculations and control catalytic experiments confirmed the enhanced performance originated from(i)the downshifted d-band center of in situ generated Cu0 species induced by Al Lewis acid sites and(ii)the synergistic interplay between these Cu0 centers and adjacent Al Lewis acid sites,facilitated by isopropanol-mediated hydrogen transfer.This study demonstrates the feasibility of rationally designing high-performance catalysts featuring synergistic nonnoble metals with Lewis acid sites,enabling efficient and selective upgrade of renewable peroxidized compounds into value-added products with enhanced cost-effectiveness and process safety. 展开更多
关键词 Biomass conversion Lignin derivatives Vanillin Hydrodeoxygenation mechanism
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Cross-domain few-shot learning:A new perspective on overcoming bottlenecks in clinical artificial intelligence tumor diagnosis 认领 引用
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作者 Ziyao Chen Chenglong Fu +4 位作者 Chuang Wang Cheng Chen Xiang Pan Jian Yao Pengjiang Qian 《Chinese Journal of Cancer Research》 SCIE CAS CSCD 2026年第2期204-208,共5页
Introduction One of the leading causes of death globally is cancer.Although early screening and accurate diagnosis may reduce the mortality of patients significantly, the existing clinical practice is confronted by a ... Introduction One of the leading causes of death globally is cancer.Although early screening and accurate diagnosis may reduce the mortality of patients significantly, the existing clinical practice is confronted by a formidable obstacle: a significant discrepancy between the rapidly increasing annual number of suspected cases and the acute lack of specialist physicians. According to the most recent report in the reputable medical publication CA: A Cancer Journal for Clinicians titled Cancer Statistics, 2025, more than 2.04million new cases of cancer are projected in 2025 along in the United States, and the prevalence of cancer among the young population will increase significantly(1).Considering such high number of patients, conventional testing methods are inadequate because they are expensive and slow, in addition to requiring extensive involvement of skilled pathology and radiology specialists, which is a major bottleneck in the clinical setting. 展开更多
关键词 accurate diagnosis specialist physicians discrepancy clinical artificial intelligence tumor diagnosis global cancer mortality early screening cross domain few shot learning
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3D printed organohydrogel-based strain sensors with enhanced sensitivity and stability via structural design 认领 引用 被引量：2
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作者 Binbin Guo Chengyu Lin +8 位作者 Haitao Ye Yu Xue Jiewen Mo Jiawei Chen Yangfeng Cui Chenglong Fu Jiaming Bai Qi Ge Hui Ying Yang 《International Journal of Extreme Manufacturing》 SCIE EI CAS CSCD 2025年第5期464-479,共16页
Organohydrogel-based strain sensors are gaining attention for real-time health services and human-machine interactions due to their flexibility,stretchability,and skin-like compliance.However,these sensors often have ... Organohydrogel-based strain sensors are gaining attention for real-time health services and human-machine interactions due to their flexibility,stretchability,and skin-like compliance.However,these sensors often have limited sensitivity and poor stability due to their bulk structure and strain concentration during stretching.In this study,we designed and fabricated diamond-,grid-,and peanut-shaped organohydrogel based on positive,near-zero,and negative Poisson’s ratios using digital light processing(DLP)-based 3D printing technology.Through structural design and optimization,the grid-shaped organohydrogel exhibited record sensitivity with gauge factors of 4.5(0–200%strain,ionic mode)and 13.5/1.5×106(0-2%/2%-100%strain,electronic mode),alongside full resistance recovery for enhanced stability.The 3D-printed grid structure enabled direct wearability and breathability,overcoming traditional sensor limitations.Integrated with a robotic hand system,this sensor demonstrated clinical potential through precise monitoring of paralyzed patients’grasping movements(with a minimum monitoring angle of 5°).This structural design paradigm advanced flexible electronics by synergizing high sensitivity,stability,wearability,and breathability for healthcare,and human-machine interfaces. 展开更多
关键词 3D printing organohydrogel sensitivity stability structural design
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Directional Point Net:3D Environmental Classification for Wearable Robots 认领 引用 被引量：2
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作者 Kuangen ZHANG Jing WANG Chenglong FU 《Instrumentation》 EI 2019年第1期25-33,共9页
A subject who wears a suitable robotic device will be able to walk in complex environments with the aid of environmental recognition schemes that provide reliable prior information of the human motion intent.Researche... A subject who wears a suitable robotic device will be able to walk in complex environments with the aid of environmental recognition schemes that provide reliable prior information of the human motion intent.Researchers have utilized 1 D laser signals and 2 D depth images to classify environments,but those approaches can face the problems of self-occlusion.In comparison,3 D point cloud is more appropriate for depicting the environments.This paper proposes a directional PointNet to directly classify the 3 D point cloud.First,an inertial measurement unit(IMU)is used to offset the orientation of point cloud.Then the directional PointNet can accurately classify the daily commuted terrains,including level ground,climbing up stairways,and walking down stairs.A classification accuracy of 98%has been achieved in tests.Moreover,the directional PointNet is more efficient than the previously used PointNet because the T-net,which is utilized to estimate the transformation of the point cloud,is not used in the present approach,and the length of the global feature is optimized.The experimental results demonstrate that the directional PointNet can classify the environments in robust and efficient manner. 展开更多
关键词 PointNet 3D environmental classification point cloud wearable robots
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Stability and control of dynamic walking for a five-link planar biped robot with feet 认领 引用 被引量：2
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作者 Chenglong FU Ken CHEN +1 位作者 Jing XIONG Leon XU 《控制理论与应用（英文版）》 2007年第2期113-120,共8页
During dynamic walking of biped robots, the underactuated rotating degree of freedom （DOF） emerges between the support foot and the ground, which makes the biped model hybrid and dimension-variant. This paper addres... During dynamic walking of biped robots, the underactuated rotating degree of freedom （DOF） emerges between the support foot and the ground, which makes the biped model hybrid and dimension-variant. This paper addresses the asymptotic orbit stability for dimension-variant hybrid systems （DVHS）. Based on the generalized Poincare map, the stability criterion for DVHS is also presented, and the result is then used to study dynamic walking for a five-link planar biped robot with feet. Time-invariant gait planning and nonlinear control strategy for dynamic walking with fiat feet is also introduced. Simulation results indicate that an asymptotically stable limit cycle of dynamic walking is achieved by the proposed method. 展开更多
关键词 Biped robot Dynamic walking Orbit stability Dimension-variant hybrid systems Nonlinear control
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Joint moment estimation for hip exoskeleton control:A generalized moment feature generation method 认领 引用 被引量：1
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作者 Yuanwen Zhang Jingfeng Xiong +5 位作者 Haolan Xian Chuheng Chen Xinxing Chen Haipeng Liang Chenglong Fu Yuquan Leng 《Biomimetic Intelligence & Robotics》 EI CSCD 2025年第4期51-63,共13页
Hip joint moments during walking are the key foundation for hip exoskeleton assistance control.Most recent studies have shown estimating hip joint moments instantaneously offers a lot of advantages compared to generat... Hip joint moments during walking are the key foundation for hip exoskeleton assistance control.Most recent studies have shown estimating hip joint moments instantaneously offers a lot of advantages compared to generating assistive torque profiles based on gait estimation,such as simple sensor requirements and adaptability to variable walking speeds.However,existing joint moment estimation methods still suffer from a lack of personalization,leading to estimation accuracy degradation for new users.To address the challenges,this paper proposes a hip joint moment estimation method based on generalized moment features(GMF).A GMF generator is constructed to learn GMF of the joint moment which is invariant to individual variations while remaining decodable into joint moments through a dedicated decoder.Utilizing this well-featured representation,a GRU-based neural network is used to predict GMF with joint kinematics data,which can easily be acquired by hip exoskeleton encoders.The proposed estimation method achieves a root mean square error of 0.1180±0.0021 Nm/kg under 28 walking speed conditions on a treadmill dataset,improved by 6.5%compared to the model without body parameter fusion,and by 8.3%for the conventional fusion model with body parameter.Furthermore,the proposed method was employed on a hip exoskeleton with only encoder sensors and achieved an average 20.5%metabolic reduction(p<0.01)for users compared to assist-off condition in level-ground walking. 展开更多
关键词 Lower-limb exoskeleton Hip joint moment estimation Deep learning
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