arXiv subjects

Jianbo Tang

Publications and source records attributed to Jianbo Tang.

8 recordsLinked to original sources

arXiv2026

Centimeter-scale fully suspended metal and metal oxide thin films by one-step transfer-free liquid metal capillary forming

Fully suspended thin films can decouple substrate effects and provide additional tuning degrees of freedom compared with their substrate-supported counterparts, making them unique platforms for next-generation thin film devices. Here we report one-step, transfer-free and substrate-free fabrication of centimeter-scale ultrathin fully suspended metal and metal oxide film structures via liquid metal capillary forming. We show that, analogous to soap film formation, the instantaneously developed few-nanometer-thick native surface oxide can laminate various liquid metals into micrometer-thick metallic films. Surprisingly, the surfactant-like metal oxide bilayer can survive dewetting-induced liquid metal drainage, forming suspended two-dimensional films featuring an enormous lateral size-to-thickness ratio on the order of 10^7. We further demonstrate rapid prototyping of metallic minimal-surface thin-walled structures and ultra-sensitive acoustic wave detection with these suspended thin film platforms.

cond-mat.mtrl-sci↗

arXiv2022

Brain-inspired Graph Spiking Neural Networks for Commonsense Knowledge Representation and Reasoning

How neural networks in the human brain represent commonsense knowledge, and complete related reasoning tasks is an important research topic in neuroscience, cognitive science, psychology, and artificial intelligence. Although the traditional artificial neural network using fixed-length vectors to represent symbols has gained good performance in some specific tasks, it is still a black box that lacks interpretability, far from how humans perceive the world. Inspired by the grandmother-cell hypothesis in neuroscience, this work investigates how population encoding and spiking timing-dependent plasticity (STDP) mechanisms can be integrated into the learning of spiking neural networks, and how a population of neurons can represent a symbol via guiding the completion of sequential firing between different neuron populations. The neuron populations of different communities together constitute the entire commonsense knowledge graph, forming a giant graph spiking neural network. Moreover, we introduced the Reward-modulated spiking timing-dependent plasticity (R-STDP) mechanism to simulate the biological reinforcement learning process and completed the related reasoning tasks accordingly, achieving comparable accuracy and faster convergence speed than the graph convolutional artificial neural networks. For the fields of neuroscience and cognitive science, the work in this paper provided the foundation of computational modeling for further exploration of the way the human brain represents commonsense knowledge. For the field of artificial intelligence, this paper indicated the exploration direction for realizing a more robust and interpretable neural network by constructing a commonsense knowledge representation and reasoning spiking neural networks with solid biological plausibility.

cs.NE↗

arXiv2021

Quantized orbital-chasing liquid metal heterodimers directed by an integrated pilot-wave field

A millimetric bouncing droplet sustained on a vibrating bath becomes a moving wave source (particle) through periodically interacting with the local wave field it generates during the droplet-bath impact. By virtue of such particle-wave duality, the macroscopic hydrodynamic system imitates enigmatic behaviors of the quantum realm. Here we show that it is possible to create an integrated pilot-wave field to better prescribe the droplet trajectories, via amplified bath capillarity. This is demonstrated with a liquid metal droplet-bath system in which the local wave field generated by droplet bouncing is superposed by the global wave field induced by bath meniscus oscillation. The resulting dual pilot-wave configuration enables a class of directional chasing motions of two bound dissimilar droplets (heterodimers) in multilevel hydrodynamic traps (orbits), featuring two quantized regime parameters, namely the interdroplet binding level and the orbit level. We investigate the dynamics of the vibrating liquid metal bath, with its level-split ring wave field and its peculiar vortex field being highlighted. We also rationalize the exotic droplet motions by considering the interdroplet particle-wave interactions mediated by the integrated pilot-wave field. It is revealed that a temporal bouncing phase shift between the two droplets in the heterodimers, due to size mismatch, gives rise to their horizontal propulsion, while their spatial binding regime exclusively determines the collective chasing direction. It is further evidenced that the horizontal in-orbit chasing motion is directly related to vertical droplet bouncing. Our findings unveil the integrated pilot-wave field as a trail towards improved droplet guiding, thereby extending the hydrodynamic particle-wave analogy to optical systems and beyond.

physics.flu-dyn↗

arXiv2021

LICHEE: Improving Language Model Pre-training with Multi-grained Tokenization

Language model pre-training based on large corpora has achieved tremendous success in terms of constructing enriched contextual representations and has led to significant performance gains on a diverse range of Natural Language Understanding (NLU) tasks. Despite the success, most current pre-trained language models, such as BERT, are trained based on single-grained tokenization, usually with fine-grained characters or sub-words, making it hard for them to learn the precise meaning of coarse-grained words and phrases. In this paper, we propose a simple yet effective pre-training method named LICHEE to efficiently incorporate multi-grained information of input text. Our method can be applied to various pre-trained language models and improve their representation capability. Extensive experiments conducted on CLUE and SuperGLUE demonstrate that our method achieves comprehensive improvements on a wide variety of NLU tasks in both Chinese and English with little extra inference cost incurred, and that our best ensemble model achieves the state-of-the-art performance on CLUE benchmark competition.

cs.CL↗

arXiv2018

Tubeless Siphon Flow of Room Temperature Liquid Metal

Tubeless siphon flow of liquid metal was made possible by way of sucking the fluid via a syringe pump with a rubber tube. Through adjusting the flow rate and tube diameter, the liquid column height and diameter can be changed accordingly. A theoretical model was derived to predict the flow configuration thus enabled. Adding micro copper particles evidently increased the extensional viscosity of liquid metal. With the increase of particle concentration, the enhancement of tubeless siphon becomes more remarkable. The intermetallic compound CuGa2 produced by corrosion was considered as the reason for the variation of rheological property of liquid metal.

physics.flu-dyn↗

arXiv2017

Transformable Soft Quantum Device based on Liquid Metals with Sandwiched Liquid Junctions

Quantum tunneling effect has been an important issue in both fundamental science and practical applications. Classical quantum tunneling devices are generally rigid in structures which may encounter technical difficulties during fabrication, functional tuning and shape adapting. Here through introducing the room-temperature liquid metals as two conductive electrodes and a soft even liquid insulating layer sandwiched between them, we proposed a conceptually innovative all-soft or liquid quantum device which would help realize a couple of unconventional quantum capabilities such as flexibility, deformability, transformability, and reconfigurability, etc. which may not be easily offered by a rigid quantum device. Representative structural configurations to make such transformable quantum devices via sandwiching various liquid metal-insulating layer-liquid metal (LM-IL-LM) components are suggested. The feasibility for making such an all-soft quantum device is interpreted through experimental evidences and theoretical evaluations. Potential future applications of the proposed devices in a group of emerging fields including intelligent quantum systems and quantum computing are prospected.

physics.app-ph↗

arXiv2017

Gas Eruption Phenomenon Happening from Ga-In Alloy in Electrolyte

We report a gas eruption phenomenon caused by electrolysis of liquid Ga-In alloy in an electrolyte, especially NaOH solution. A volcanic eruption-like blowout of gas occurred from the orifice on the alloy surface. In addition to gas plume, large gas bubbles were also generated and the total gas yield increased as In ratio was increased. It is found that destructiveness of the passivation layer on the Ga-In alloy is critical to gas generation. The mechanism of gas eruption can be ascribed to a galvanic interaction happens owing to passivation film and alloy with different activity connected as electrode in electrolyte. Further investigation demonstrated that the lattice of the film expands because of the incorporation of indium, which brings about the decrease in band gap and finally enhances more gas generation. These findings regain the basic understanding of room temperature liquid metal inside electrolyte.

physics.chem-ph↗

arXiv2017

Surfing Liquid Metal Droplet on the Same Metal Bath via Electrolyte Interface

We reported a phenomenon that when exerting an electric field gradient across a liquid metal/electrolyte interface, a droplet of the same liquid metal can persistently surf on the interface without coalescence. A thin layer of the intermediate solution, which separates the droplet from direct metallic contacting and provides the levitating force, is responsible for such surfing effect. The electric resistance of this solution film is measured and the film thickness is further theoretically calculated. The fact that the levitating state can be switched on and off via a controlled manner paves a way for reliable manipulation of liquid metal droplet.

physics.flu-dyn↗