Research paperComputational AimdComputational MLIPComputational MDTheoreticalSignificantly Enhanced Interfacial Thermal Transport between Single-layer Graphene and Water Through Basal-plane OxidationHaoran Cui, Iyyappa Rajan Panneerselvam, Pranay Chakraborty, Qiong Nian et al.arXiv·2024·10.1016/j.carbon.2024.119910·arXiv:2408.16998AbstractHeat transfer between graphene and water is pivotal for various applications, including solar-thermal vapor generation and the advanced manufacturing of graphene-based hierarchical structures in solution. In this study, we employ a deep-neural network potential derived from ab initio molecular dynamics to conduct extensive simulations of single-layer graphene-water systems with different levels of oxidation (carbon/oxygen ratio) of the graphene layer. Remarkably, our findings reveal a one-order-of-magnitude enhancement in heat transfer upon oxidizing graphene with hydroxyl or epoxide groups at the graphene surface, underscoring the significant tunability of heat transfer within this system. Given the same oxidation ratio, more dispersed locations of functional groups on graphene surface leads to faster heat dissipation to water.Read more
Pristine single-layer graphene system used in AIMD data generation for ML potential training.No measurements recordedSimulated Supercell DftCStudied MaterialExpand
Graphene-water interfacial system used in AIMD data generation and transient MD simulations.No measurements recordedSimulatedCStudied MaterialH₂OStudied MaterialExpand
Oxidized graphene (GO) supercell with approximately 25% O/C ratio used in AIMD training data.No measurements recordedSimulated Supercell DftCStudied MaterialExpand
GO-water interfacial system used in AIMD training data and transient MD simulations, including different oxidation configurations.No measurements recordedSimulatedCStudied MaterialH₂OStudied MaterialExpand
Oxidized carbon nanotube-water interfacial system with 5% O/C ratio and diameter 0.55 nm used in AIMD training data.No measurements recordedSimulatedCStudied MaterialH₂OStudied MaterialExpand
Research paperComputational AimdComputational MLIPComputational MDTheoreticalSignificantly Enhanced Interfacial Thermal Transport between Single-layer Graphene and Water Through Basal-plane OxidationHaoran Cui, Iyyappa Rajan Panneerselvam, Pranay Chakraborty, Qiong Nian et al.arXiv·2024·10.1016/j.carbon.2024.119910·arXiv:2408.16998AbstractHeat transfer between graphene and water is pivotal for various applications, including solar-thermal vapor generation and the advanced manufacturing of graphene-based hierarchical structures in solution. In this study, we employ a deep-neural network potential derived from ab initio molecular dynamics to conduct extensive simulations of single-layer graphene-water systems with different levels of oxidation (carbon/oxygen ratio) of the graphene layer. Remarkably, our findings reveal a one-order-of-magnitude enhancement in heat transfer upon oxidizing graphene with hydroxyl or epoxide groups at the graphene surface, underscoring the significant tunability of heat transfer within this system. Given the same oxidation ratio, more dispersed locations of functional groups on graphene surface leads to faster heat dissipation to water.Read more
Pristine single-layer graphene system used in AIMD data generation for ML potential training.No measurements recordedSimulated Supercell DftCStudied MaterialExpand
Graphene-water interfacial system used in AIMD data generation and transient MD simulations.No measurements recordedSimulatedCStudied MaterialH₂OStudied MaterialExpand
Oxidized graphene (GO) supercell with approximately 25% O/C ratio used in AIMD training data.No measurements recordedSimulated Supercell DftCStudied MaterialExpand
GO-water interfacial system used in AIMD training data and transient MD simulations, including different oxidation configurations.No measurements recordedSimulatedCStudied MaterialH₂OStudied MaterialExpand
Oxidized carbon nanotube-water interfacial system with 5% O/C ratio and diameter 0.55 nm used in AIMD training data.No measurements recordedSimulatedCStudied MaterialH₂OStudied MaterialExpand
Research paperComputational AimdComputational MLIPComputational MDTheoreticalSignificantly Enhanced Interfacial Thermal Transport between Single-layer Graphene and Water Through Basal-plane OxidationHaoran Cui, Iyyappa Rajan Panneerselvam, Pranay Chakraborty, Qiong Nian et al.arXiv·2024·10.1016/j.carbon.2024.119910·arXiv:2408.16998AbstractHeat transfer between graphene and water is pivotal for various applications, including solar-thermal vapor generation and the advanced manufacturing of graphene-based hierarchical structures in solution. In this study, we employ a deep-neural network potential derived from ab initio molecular dynamics to conduct extensive simulations of single-layer graphene-water systems with different levels of oxidation (carbon/oxygen ratio) of the graphene layer. Remarkably, our findings reveal a one-order-of-magnitude enhancement in heat transfer upon oxidizing graphene with hydroxyl or epoxide groups at the graphene surface, underscoring the significant tunability of heat transfer within this system. Given the same oxidation ratio, more dispersed locations of functional groups on graphene surface leads to faster heat dissipation to water.Read more
Pristine single-layer graphene system used in AIMD data generation for ML potential training.No measurements recordedSimulated Supercell DftCStudied MaterialExpand
Graphene-water interfacial system used in AIMD data generation and transient MD simulations.No measurements recordedSimulatedCStudied MaterialH₂OStudied MaterialExpand
Oxidized graphene (GO) supercell with approximately 25% O/C ratio used in AIMD training data.No measurements recordedSimulated Supercell DftCStudied MaterialExpand
GO-water interfacial system used in AIMD training data and transient MD simulations, including different oxidation configurations.No measurements recordedSimulatedCStudied MaterialH₂OStudied MaterialExpand
Oxidized carbon nanotube-water interfacial system with 5% O/C ratio and diameter 0.55 nm used in AIMD training data.No measurements recordedSimulatedCStudied MaterialH₂OStudied MaterialExpand
Research paperComputational AimdComputational MLIPComputational MDTheoreticalSignificantly Enhanced Interfacial Thermal Transport between Single-layer Graphene and Water Through Basal-plane OxidationHaoran Cui, Iyyappa Rajan Panneerselvam, Pranay Chakraborty, Qiong Nian et al.arXiv·2024·10.1016/j.carbon.2024.119910·arXiv:2408.16998AbstractHeat transfer between graphene and water is pivotal for various applications, including solar-thermal vapor generation and the advanced manufacturing of graphene-based hierarchical structures in solution. In this study, we employ a deep-neural network potential derived from ab initio molecular dynamics to conduct extensive simulations of single-layer graphene-water systems with different levels of oxidation (carbon/oxygen ratio) of the graphene layer. Remarkably, our findings reveal a one-order-of-magnitude enhancement in heat transfer upon oxidizing graphene with hydroxyl or epoxide groups at the graphene surface, underscoring the significant tunability of heat transfer within this system. Given the same oxidation ratio, more dispersed locations of functional groups on graphene surface leads to faster heat dissipation to water.Read more
Pristine single-layer graphene system used in AIMD data generation for ML potential training.No measurements recordedSimulated Supercell DftCStudied MaterialExpand
Graphene-water interfacial system used in AIMD data generation and transient MD simulations.No measurements recordedSimulatedCStudied MaterialH₂OStudied MaterialExpand
Oxidized graphene (GO) supercell with approximately 25% O/C ratio used in AIMD training data.No measurements recordedSimulated Supercell DftCStudied MaterialExpand
GO-water interfacial system used in AIMD training data and transient MD simulations, including different oxidation configurations.No measurements recordedSimulatedCStudied MaterialH₂OStudied MaterialExpand
Oxidized carbon nanotube-water interfacial system with 5% O/C ratio and diameter 0.55 nm used in AIMD training data.No measurements recordedSimulatedCStudied MaterialH₂OStudied MaterialExpand