Check engineering papers: citations, claims and retractions

A review on wearable photoplethysmography sensors and their potential future applications in health care

Ghamari, M. (2018) · International Journal of Biosensors & Bioelectronics

Non-Invasive Vital Sign MonitoringHeart Rate Variability and Autonomic Control

Cited by 945

Hydrogel bioprinted microchannel networks for vascularization of tissue engineering constructs

Bertassoni, L. E., Cecconi, M., Manoharan, V., Nikkhah, M., Hjortnaes, J., Cristino, A. L., Barabaschi, G., Demarchi, D., Dokmeci, M. R., Yang, Y., et al. (2014) · Lab Chip

3D Printing in Biomedical ResearchHydrogels: synthesis, properties, applications

Cited by 944

A compute-in-memory chip based on resistive random-access memory

Wan, W., Kubendran, R., Schaefer, C., Eryilmaz, S. B., Zhang, W., Wu, D., Deiss, S., Raina, P., Qian, H., Gao, B., et al. (2022) · Nature

Advanced Memory and Neural ComputingFerroelectric and Negative Capacitance Devices

Cited by 943

High-entropy materials for catalysis: A new frontier

Sun, Y., & Dai, S. (2021) · Science Advances

High Entropy Alloys StudiesCatalytic Processes in Materials Science

Cited by 942

LX. On the equilibrium of vapour at a curved surface of liquid

Thomson, W. (1871) · The London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science

Fluid Dynamics and Heat TransferChemical Thermodynamics and Molecular Structure

Cited by 942

Second near-infrared photothermal materials for combinational nanotheranostics

Xu, C., & Pu, K. (2021) · Chemical Society Reviews

Nanoplatforms for cancer theranosticsPhotodynamic Therapy Research Studies

Cited by 941

Industry 4.0 implies lean manufacturing: Research activities in industry 4.0 function as enablers for lean manufacturing

Sanders, A., Elangeswaran, C., & Wulfsberg, J. (2016) · Journal of Industrial Engineering and Management

Digital Transformation in IndustryQuality and Supply Management

Cited by 938

Experimental Demonstration and Tolerancing of a Large-Scale Neural Network (165 000 Synapses) Using Phase-Change Memory as the Synaptic Weight Element

Burr, G. W., Shelby, R. M., Sidler, S., di Nolfo, C., Jang, J., Boybat, I., Shenoy, R. S., Narayanan, P., Virwani, K., Giacometti, E. U., et al. (2015) · IEEE Transactions on Electron Devices

Advanced Memory and Neural ComputingNeural Networks and Applications

Cited by 936

Toward ubiquitous blood pressure monitoring via pulse transit time: Theory and practice

Mukkamala, R., Hahn, J.-O., Inan, O. T., Mestha, L. K., Kim, C.-S., Toreyin, H., & Kyal, S. (2015) · IEEE Transactions on Biomedical Engineering

Non-Invasive Vital Sign MonitoringCardiovascular Health and Disease Prevention

Cited by 935

Underpotential Deposition at Single Crystal Surfaces of Au, Pt, Ag and Other Materials

Herrero, E., Buller, L. J., & Abruña, H. D. (2001) · Chemical Reviews

Electrodeposition and Electroless CoatingsSurface and Thin Film Phenomena

Cited by 934

Method for generation of homogeneous multicellular tumor spheroids applicable to a wide variety of cell types

Kelm, J. M., Timmins, N. E., Brown, C. J., Fussenegger, M., & Nielsen, L. K. (2003) · Biotechnology and Bioengineering

3D Printing in Biomedical ResearchCancer Cells and Metastasis

Cited by 934

Climate change and the world's river basins: anticipating management options

Palmer, M. A., Reidy Liermann, C. A., Nilsson, C., Flörke, M., Alcamo, J., Lake, P. S., & Bond, N. (2008) · Frontiers in Ecology and the Environment

Water resources management and optimizationHydrology and Watershed Management Studies

Cited by 934

Heterogeneity of biochar properties as a function of feedstock sources and production temperatures

Zhao, L., Cao, X., Mašek, O., & Zimmerman, A. (2013) · Journal of Hazardous Materials

Thermochemical Biomass Conversion ProcessesSoil Carbon and Nitrogen Dynamics

Cited by 933

A reliability perspective of the smart grid

Moslehi, K., & Kumar, R. (2010) · IEEE Transactions on Smart Grid

Smart Grid and Power SystemsPower System Reliability and Maintenance

Cited by 932

Blockchain-based decentralized trust management in vehicular networks

Yang, Z., Yang, K., Lei, L., Zheng, K., & Leung, V. C. M. (2019) · IEEE Internet of Things Journal

Vehicular Ad Hoc Networks (VANETs)Blockchain Technology Applications and Security

Cited by 932

Extended-phase-shift control of isolated bidirectional DC–DC converter for power distribution in microgrid

Zhao, B., Yu, Q., & Sun, W. (2012) · IEEE Transactions on Power Electronics

Advanced DC-DC ConvertersMicrogrid Control and Optimization

Cited by 932

Ambient Backscatter Communications: A Contemporary Survey

Van Huynh, N., Hoang, D. T., Lu, X., Niyato, D., Wang, P., & Kim, D. I. (2018) · IEEE Communications Surveys & Tutorials

Energy Harvesting in Wireless NetworksWireless Communication Security Techniques

Cited by 932

Efficient and self-adaptive in-situ learning in multilayer memristor neural networks

Li, C., Belkin, D., Li, Y., Yan, P., Hu, M., Ge, N., Jiang, H., Montgomery, E., Lin, P., Wang, Z., et al. (2018) · Nature Communications

Advanced Memory and Neural ComputingFerroelectric and Negative Capacitance Devices

Cited by 931

Taxel-Addressable Matrix of Vertical-Nanowire Piezotronic Transistors for Active and Adaptive Tactile Imaging

Wu, W., Wen, X., & Wang, Z. L. (2013) · Science

Advanced Sensor and Energy Harvesting MaterialsNanowire Synthesis and Applications

Cited by 931

Critical interventions into the corporate smart city

Hollands, R. G. (2015) · Cambridge Journal of Regions, Economy and Society

Smart Cities and TechnologiesUrban Planning and Governance

Cited by 931

Structural Design for Fire Safety

Buchanan, A. H., & Abu, A. K. (2016) · Wiley eBooks

Fire effects on concrete materialsFire dynamics and safety research

Cited by 929

Min-max feedback model predictive control for constrained linear systems

Scokaert, P. O. M., & Mayne, D. Q. (1998) · IEEE Transactions on Automatic Control

Advanced Control Systems OptimizationAdvanced Optimization Algorithms Research

Cited by 929

Data-Driven Grasp Synthesis—A Survey

Bohg, J., Morales, A., Asfour, T., & Kragic, D. (2014) · IEEE Transactions on Robotics

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 929

Feedstock choice, pyrolysis temperature and type influence biochar characteristics: a comprehensive meta-data analysis review

Ippolito, J. A., Cui, L., Kammann, C., Wrage-Mönnig, N., Estavillo, J. M., Fuertes-Mendizabal, T., Cayuela, M. L., Sigua, G., Novak, J., Spokas, K., et al. (2020) · Biochar

Thermochemical Biomass Conversion ProcessesSoil Carbon and Nitrogen Dynamics

Cited by 927