Tunneling Resistance Research Articles

From nano to macro in graphene-polymer nanocomposites: A new methodology for conductivity prediction

A two-step approach is proposed to forecast the conductivity of graphene polymer composites using simple models reflecting the tunneling mechanism and interphase part. Firstly, graphene and the adjacent interphase are presumed as figurative particles, and their conductivity is estimated. In the second stage, the conductivity of the nanocomposite containing figurative particles is predicted, considering the tunneling size between adjacent particles. The advanced methodology is used to forecast the conductivity for real examples. Additionally, the implications of all terms on the nanocomposite conductivity are assessed and explained. The estimations of conductivity acceptably agree with the measured data, which justifies the predictability of the suggested methodology. Thick interphase and short tunnels produce desirable conductivity, because they positively influence the net dimensions and tunneling resistance. Among the studied parameters, the thicknesses of graphene nanosheets and interphase have the highest impacts on the nanocomposite conductivity. The highest conductivity of nanocomposite as 7 S/m is obtained by the thickest interphase (ti = 10 nm) and the thinnest nanosheets (t = 1 nm), while t > 2 nm or ti < 5.5 nm cannot improve the conductivity. Furthermore, graphene volume fraction of 0.03 with the graphene diameter of 4 μm maximizes the nanocomposite conductivity to 3 S/m, but less filler amount and shorter nanosheets weaken the conductivity of nanocomposites.

Experimental investigation on damage development and failure mechanism of shield tunnel lining under internal blast considering stratum-structure interaction

With the expansion of international terrorism and the potential threat of attacks against civil infrastructure, the dynamic response and failure modes of underground tunnels under explosive loads have become a prominent research topic. The high cost and inherent danger associated with explosion experiments have limited current research on tunnel internal explosions, particularly in the context of scaled model tests of shield tunnels. This study presents a series of scaled model tests under 1 g-condition simulating internal blast events within a shield tunnel based on the prototype of the Shantou Bay Tunnel, considering the influences of surrounding stratum and equivalent explosive yield. Three different TNT explosive yields are considered in the model tests, namely 0.2, 0.4, and 1.0 kg. The model tests focus on the damage behavior and collapse modes of the shield tunnel lining under internal explosive loads. The model tests reveal that the shield tunnel is prone to damage at the joints of the tunnel crown and shoulder when subjected to internal explosive loads, with the upper half of the tunnel lining experiencing segment collapse, while the lower half remains largely undamaged. As the TNT equivalent increases, the damage area at the tunnel joints expands, and the number of segment failures in the upper half of the tunnel rises, transitioning from a damaged state to a collapsed state. The influence of “stratum-structure” interaction is investigated by comparing two models, one with overburden soil and the other positioned at the ground surface. The model tests reveal that the presence of soil pressure and confinement can significantly enhance the tunnel resistance to internal blast loads. Based on the observation of the model tests, five different damage modes of segment joints under internal explosion are proposed in this study.

Mechanical and piezoresistive performance of polymethyl methacrylate modified with carbon nanotubes for sensitive road surface

Piezoresistive materials, known for their mechanical adaptability and sensing capacity, hold the potential to be used as the materials for the sensitive surface layer in the digital twin of road systems. This study aims to investigate the mechanical and piezoresistive performance of a novel pavement material, a composite that comprises Polymethyl methacrylate (PMMA) as the matrix and carbon nanotubes (CNTs) as the conductive filler. Firstly, the composition and preparation process of CNTs-modified PMMA (CMP) were optimized via investigation on curing time, dispersion methods, and initiator content. Subsequently, the piezoresistive responses of CMP were analyzed within a loading range of 0 to 10 MPa by conducting linear increase compressive stress tests. Additionally, dynamic modulus tests and dynamic creep tests were employed to assess the mechanical and piezoresistive responses of CMP under equivalent vehicle loads. Results show that optimal properties are achieved when using ultrasonic methods to disperse CNTs, with a curing period of 72 h and an initiator content of 1.6 wt%. PMMA exhibits a lower modulus, reduced elasticity recovery and temperature sensitivity after modification with CNTs. And varying the CNTs content from 0.8 wt% to 1.2 wt% does not significantly affect the viscoelastic properties of CMP. The piezoresistive response of CMP under equivalent vehicle loads occurs in the first stage of the fractional change in resistance curve and is exclusively correlated with the tunneling resistance of adjacent CNTs. In this stage, CMP demonstrates higher sensitivity to heavy loads at lower CNTs content. The developed piezoresistive model based on tunneling resistance aligns with the experimental results. This study provides a basis for the performance study of CMP as a piezoresistive material in pavements, contributing to the design and development of sensitive surface layers in road systems.

Giant tunneling resistance and robust switching behavior in ferroelectric tunnel junctions of WS2/Ga2O3 heterostructures: The influence of metal–semiconductor contacts

The ferroelectric tunneling junctions (FTJs) are widely recognized as one of the non-volatile memories with significant potential. Ferroelectricity usually fades away as materials are thinned down below a critical value, and this problem is particularly acute in the case of shrinking device sizes, thus attracting attention to two-dimensional ferroelectric materials (2DFEMs). In this work, we designed 2D ferroelectric Ga2O3-based FTJs with out-of-plane polarization, and the influence of metal–semiconductor contact in the electrode region on the system is considered. Here, using density functional theory combined with the non-equilibrium Green's function approach to quantum transport calculations, we demonstrate robust ferroelectric polarization-controlled switching behavior between metallic and semiconducting states in Ga2O3/WS2 ferroelectric heterostructures. The potential barrier of the metal–semiconductor contact in the electrode region is lower than that of the intrinsic material, thereby resulting in an increased probability of electron tunneling. Our results reveal the crucial role of 2DFEMs in the construction of FTJs and highlight the significant impact of electrode contact types on performance. This provides a promising approach for developing high-density ferroelectric memories based on 2D ferroelectric semiconductor heterostructures.

Macroscopic tunneling probe of Moiré spin textures in twisted CrI3

Various noncollinear spin textures and magnetic phases have been predicted in twisted two-dimensional CrI3 due to competing ferromagnetic (FM) and antiferromagnetic (AFM) interlayer exchange from moiré stacking—with potential spintronic applications even when the underlying material possesses a negligible Dzyaloshinskii–Moriya or dipole–dipole interaction. Recent measurements have shown evidence of coexisting FM and AFM layer order in small-twist-angle CrI3 bilayers and double bilayers. Yet, the nature of the magnetic textures remains unresolved and possibilities for their manipulation and electrical readout are unexplored. Here, we use tunneling magnetoresistance to investigate the collective spin states of twisted double-bilayer CrI3 under both out-of-plane and in-plane magnetic fields together with detailed micromagnetic simulations of domain dynamics based on magnetic circular dichroism. Our results capture hysteretic and anisotropic field evolutions of the magnetic states and we further uncover two distinct non-volatile spin textures (out-of-plane and in-plane domains) at ≈1° twist angle, with a different global tunneling resistance that can be switched by magnetic field.

Influences of defective interphase and contact region among nanosheets on the electrical conductivity of polymer graphene nanocomposites

In the current article, a defective interface is characterized by “Dc,” representing the smallest diameter of nanosheets crucial for effective conduction transfer from the conductive filler to the medium, and by “ψ” as interfacial conduction. These parameters define the effective aspect ratio and operational volume fraction of graphene in the samples. The resistances of the graphene and polymer layer in contact zones are also considered to determine the contact resistance between adjacent nanosheets. Subsequently, a model for the tunneling conductivity of composites is proposed based on these concepts. This innovative model is validated by experimental data. Additionally, the effects of various factors on the conductivity of the composites and contact resistance are analyzed. Certain parameters such as filler concentration, graphene conductivity, interfacial conduction, and “Dc” do not affect the contact resistance due to the superconductivity of the nanosheets. However, factors like thin and large nanosheets, short tunneling distance (d), high interfacial conduction (ψ), low “Dc,” and low tunnel resistivity (ρ) contribute to increased conductivity in nanocomposites. The maximum conductivity of 0.09 is obtained at d = 2 nm and ψ = 900 S/m, but d > 6 nm and ψ < 200 S/m produce an insulated sample. Additionally, the highest conductivity of 0.11 S/m is achieved with Dc = 100 nm and ρ = 100 Ω m, whereas the conductivity approaches 0 at Dc = 500 nm and ρ = 600 Ω m.

Hydrogen-Bonding Integrated Low-Dimensional Flexible Electronics Beyond the Limitations of van der Waals Contacts.

Van der Waals (vdW) integration enables clean contacts for low-dimensional electronic devices. The limitation remains; however, that an additional tunneling contact resistance occurs owing to the inherent vdW gap between the metal and the semiconductor. Here, it is demonstrated from theoretical calculations that stronger non-covalent hydrogen-bonding interactions facilitate electron tunneling and significantly reduce the contact resistance; thus, promising to break the limitations of the vdW contact. π-plane hydrogen-bonding contacts in surface-engineered MXene/carbon nanotube metal/semiconductor heterojunctions are realized, and an anomalous temperature-dependent tunneling resistance is observed. Low-dimensional flexible thin-film transistors integrated by hydrogen-bonding contacts exhibit both excellent flexibility and carrier mobility orders of magnitude higher than their counterparts with vdW contacts. This strategy demonstrates a scalable solution for realizing high-performance and low-power flexible electronics beyond vdW contacts.

Transmissions in Gapped Graphene Exposed to Tilting and Oscillating Barriers

AbstractThe transmissions of fermions are investigated through gapped graphene structures by employing a combination of double barrier tilting and a time‐oscillating potential. The latter introduces additional sidebands into the transmission probability that manifest at energy levels determined by the frequency and incident energy. These sidebands arise from the absorption or emission of photons generated by the oscillating potential. It is demonstrated that the tilting and positioning of the scattering events within the barriers play a crucial role in determining the peak of tunneling resistance. In particular, the presence of a mid‐barrier‐embedded scatter leads to a transition from a peak to a cusp when the incident energy reaches the Dirac point within a barrier. Additionally, it is that introducing a time‐varying potential results in transmissions dispersing across both the central band and the sidebands.

Surface effects for half-metallic Heusler alloy CrYCoAl

Magnetic tunnel junctions are the core component of spintronic devices, and good magnetic tunnel junctions require high tunnel resistance, which is determined by the spin polarization of the thin films of ferromagnetic layers that make up their structure. Therefore, the design of ferromagnetic films with high spin polarization is a current research hotspot in this field. In the current study, we taken the half-metallic CrYCoAl as an object, and studied the influence of surface effect on the half-metallic behavior. Especially, we constructed the CrYCoAl (100), (110), and (111) surfaces to study their stability, electronic and magnetic properties. Results show that the YY and YAl (100) surfaces, and Co (111) surface retain the half-metallic behavior and structural stability of bulk, which provide a basis for CrYCoAl application as a thin films in magnetic tunnel junctions thus, they are likely to be used in the spintronic devices.

Tunnel resistivity deep learning inversion method based on physics‐driven and signal interpretability

AbstractData‐driven deep learning technology has a strong non‐linear mapping ability and has good development potential in geophysical inversion problems. Traditional inversion techniques offer broad generality, but they can remain trapped in local minima, particularly for three‐dimensional tunnelling resistivity inversion. In this work, we present an inversion methodology that combines traditional physics‐driven and deep learning data‐driven inversion approaches. To further support deep neural networks' dependability on unseen data, the interpretability of their working mechanism is explored. We execute migration learning based on small sample data after identifying the critical parameters that restrict the effectiveness of inversion by analysing the feature maps of various model data. We demonstrate, using both synthetic examples and field data, that the proposed method can improve the accuracy in detecting water‐bearing anomalies (caves and faults), which are typically encountered during tunnel excavation.

Enhanced tunneling electroresistance through polarization-controlled band alignments in α-In2Se3-based ferroelectric tunnel junctions

The manipulation of tunneling resistance is of paramount importance in the realm of ferroelectric tunnel junction (FTJ) devices. In this work, we propose a novel mechanism that enables the manipulation of tunneling resistance through polarization-controlled band alignments in α-In2Se3-based FTJs. This mechanism exploits the transition between metallic and insulating states, induced by polarization-controlled band alignments, thus resulting in the emergence of a significant tunneling electroresistance (TER) effect. To investigate this intriguing possibility, we have designed two-dimensional (2D) FTJs based on a PtTe2/α-In2Se3 van der Waals heterostructures. By employing first-principles calculations, we demonstrate that the manipulation of band alignments between insulating and metallic states can be achieved via ferroelectric polarization. Leveraging nonequilibrium Green's function methods, we have successfully achieved a remarkably large TER effect with a ratio reaching up to 2.40 × 104. This work unveils substantial potential for the development of nano-field high-density memories and ferroelectric field-effect transistors utilizing 2D layered ferroelectric/semiconductor heterostructures.

Spin dependent tunneling and strain sensitivity in a Co2MnSb/HfIrSb magnetic tunneling junction: a first-principles study.

Half-metallic Co-based full Heusler alloys have captured considerable attention of researchers in the realm of spintronic applications, owing to their remarkable characteristics such as exceptionally high spin polarization at the Fermi level, ultra-low Gilbert damping, and a high Curie temperature. In this comprehensive study, employing the density functional theory, we delve into the electronic stability and ballistic spin transport properties of a magnetic tunneling junction (MTJ) comprising a Co2MnSb/HfIrSb interface. An in-depth investigation of k-dependent spin transmissions uncovers the occurrence of coherent tunneling for the Mn-Mn/Ir interface, particularly when a spacer layer beyond a certain thickness is employed. It has been found that the Co-terminated Co2MnSb/HfIrSb interface shows perpendicular magnetic anisotropy, while those with Mn-Sb and Mn-Mn termination exhibit in-plane magnetic anisotropy. Furthermore, our spin-dependent transmission calculations demonstrate that the Mn-Mn/Ir interface manifests strain-sensitive transmission properties under both compressive and tensile strain and yields a remarkable three-fold increase in majority spin transmission under tensile strain conditions. We find a tunnel magnetoresistance of ∼500% under a bi-axial strain of -3%, beyond which the tunnel resistance is found to be theoretically infinite. These compelling outcomes place the Co2MnSb/HfIrSb junction among the highly promising candidates for nanoscale spintronic devices, emphasizing the potential significance of the system in the advancement of the field.

Giant tunnel resistance effect in (SrTiO3)2/(BaTiO3)4/(CaTiO3)2 asymmetric superlattice with enhanced polarization.

In this work, we report the effectively enhanced tunneling electroresistance effect in Au/(SrTiO3)2/(BaTiO3)4/(CaTiO3)2/Nb:SrTiO3 superlattice ferroelectric tunnel junction (FTJ). The stable polarization switching and enhanced ferroelectricity were achieved in the nanoscale thickness high-quality epitaxial superlattice. A high ON/OFF current ratio of more than 105 was obtained at room temperature, which is an order of magnitude larger than the BaTiO3 FTJ with the same structure. Nonvolatile resistance switching controlled by nonvolatile polarization switching was observed in the superlattice FTJ. Driven by increased polarization and intrinsic asymmetric ferroelectricity, a highly asymmetric depolarization field is generated compared with the Au/BaTiO3/Nb:SrTiO3 FTJ, resulting in an enhanced tunneling electroresistance effect. These results provide a potential way to construct FTJ memory devices by constructing asymmetric three-component ferroelectric superlattices.

Enhanced tunneling electroresistance through interfacial charge-modulated barrier in α-In2Se3-based ferroelectric tunnel junction

The manipulation of tunneling resistance is critical for ferroelectric tunnel junction (FTJ) devices. In this work, we propose a mechanism to manipulate tunneling resistance through interfacial charge-modulated barrier in two-dimensional (2D) n-type semiconductor/ferroelectric FTJs. Driven by ferroelectric reversal, different effective tunneling barriers are realized by the depletion or accumulation of electrons near the n-type semiconductor surface in such devices. Thus, the tunneling resistance in FTJs undergoes significant changes for different polarization orientations, resulting in a giant tunneling electroresistance (TER) effect. To illustrate this idea, we construct 2D FTJs based on n-InSe/α-In2Se3 van der Waals (vdW) heterostructures. Based on the electronic transport calculations, it is found that TER ratio can reach 4.20 × 103% in the designed FTJs. The physical origin of the giant TER effect is verified through analysis of the effective potential energy of the n-InSe/α-In2Se3 vdW heterostructures and the real-space transmission eigenstates of the designed FTJs. This work contributes to the knowledge of carrier tunneling mechanisms at the interface of semiconductor/In2Se3 vdW heterostructures, and providing a significant insight into the TER effect of this FTJ systems, also presenting an alternative approach for the design of FTJ-based devices.

Nonvolatile Memristive Effect in Few-Layer CrI3 Driven by Electrostatic Gating.

The potential of memristive devices for applications in nonvolatile memory and neuromorphic computing has sparked considerable interest, particularly in exploring memristive effects in two-dimensional (2D) magnetic materials. However, the progress in developing nonvolatile, magnetic field-free memristive devices using 2D magnets has been limited. In this work, we report an electrostatic-gating-induced nonvolatile memristive effect in CrI3-based tunnel junctions. The few-layer CrI3-based tunnel junction manifests notable hysteresis in its tunneling resistance as a function of gate voltage. We further engineered a nonvolatile memristor using the CrI3 tunneling junction with low writing power and at zero magnetic field. We show that the hysteretic transport observed is not a result of trivial effects or inherent magnetic properties of CrI3. We propose a potential association between the memristive effect and the newly predicted ferroelectricity in CrI3 via gating-induced Jahn-Teller distortion. Our work illuminates the potential of 2D magnets in developing next-generation advanced computing technologies.

Gradient optimization method for tunnel resistivity and chargeability joint inversion based on deep learning

The water inrush hazards have become one of the bottleneck problems that constrain tunnel construction. Ahead geological prospecting is the major tool to avoid geo-hazards and ensure safe, economical and efficient tunnelling. This work proposes a novel deep learning-based electrical method, which jointly inverses resistivity and chargeability to estimate water-bearing structures and water volume. Specifically, we design an encoder–decoder network, with one shared encoder to extract features from input data, two encoders to output resistivity and chargeability models, respectively, and an elaborate collinear regularization on the two outputs to reduce solution multiplicity. Moreover, our input is first transformed to the gradient domain to address the spatial incorrespondence issue between observation data and the electrical model. Compared with traditional linear inversion methods, our proposed method demonstrates superiority in locating and delineating anomalous bodies. The ablation study also shows that joint inversion of two parameters could benefit and outperform independent parameter inversion.

Electric vehicle wireless charging system for the foreign object detection with the inducted coil with magnetic field variation

Abstract Foreign object detection is one of the most critical issues in electric vehicle wireless charging systems. This article proposes a foreign object detection scheme with an induced coil in the charging system. The proposed method uses a multifunctional tunneling resistance sensor matrix to detect the presence of a foreign metal object between the coils. An asymmetrical induction coil design scheme is proposed to eliminate the blind area. The suggested method utilizes size-modulated c-shaped coil units to remove invisible zones that result from the magnetic field’s axial uniformity. The induced voltage in the transmission coil is measured using ANSYS/MAXWELL software. The experimental results show that the suggested method has a number of benefits over regular even-sensing coils, including higher uniformity in the induced current, position-dependent detection sensitivity, and detection accuracy. It provides a feasible and affordable way to get around the drawbacks of the traditional detecting coil.

Stepwise percolation behavior induced by nano-interconnection in electrical conductivity of polymer composites

The electrical conductivity of polymer composites incorporating a continuous nanocarbon network is reported to be 1–2 logarithmic orders higher than that of the saturation region in a typical percolation model, indicating the existence of an undiscovered region. In this study, polymer composites with high filler content (∼50 vol%) are fabricated by powder mixing and in situ polymerization including sophisticated humidity control by promoting heat convection using an air fryer. Stepwise percolation behavior is observed, wherein the electrical conductivity of the composite with a high filler content exceeds that of the percolation plateau and further increases (3828% increase at 40 vol% multi-walled carbon nanotube (MWCNT) compared to 35 vol%), and the stepwise behavior is caused by the connected filler network (nano-interconnection). A novel stepwise percolation model that describes the behavior by considering both the tunneling resistance and the nano-interconnection is proposed. In addition, the stepwise percolation behavior induces high levels of electromagnetic interference shielding (236.36% increase at 50 vol% graphene nanoplatelet relative to 40 vol%) and humidity sensing (55.59% improvement at 40 vol% MWCNT compared to 35 vol%) properties. Therefore, derivation of the stepwise percolation behavior based on the nano-interconnection can be a new breakthrough in applications of conductive composites.

Simulation of the role of agglomerations in the tunneling conductivity of polymer/carbon nanotube piezoresistive strain sensors

A 3D Monte Carlo method paired with a percolation model is carried out to predict the electrical resistivity and piezoresistive sensitivity of carbon nanotube (CNT)-polymer piezoresistive sensors. CNTs are randomly dispersed into the insulating layer of a polymer matrix having agglomerated morphologies in some parts. The electrical resistivity of nanocomposite with a defined agglomeration state is determined by considering the tunneling effect between each connected pair of CNTs. The influence of various parameters such as agglomeration radius, percentage, intrinsic properties and geometries of CNTs are investigated. A comparison was made between the analytical results and experimental data. Considering the tunneling behavior in the vicinity of the percolation transition, a good agreement is obtained between the analytical results and experimental data. Monte Carlo simulations indicated that the tunneling resistance with a random distribution of CNTs depends on the level of agglomeration. Results revealed that piezoresistive sensitivity was diminished by larger agglomerations.

Flexible pressure sensor enhanced by polydimethylsiloxane and microstructured conductive networks with positive resistance-pressure response and wide working range

Improving the performance of flexible pressure sensors has received increasing attention owing to their numerous applications in advanced technologies. However, many approaches that yield exceptional performance often involve complex manufacturing processes and high costs, which are not conducive to the large-scale production and application of flexible pressure sensors. Therefore, this paper presents a simple and efficient method, combining a pre-strain strategy with polydimethylsiloxane infiltration, for manufacturing flexible pressure sensors with a wide working range, enhanced sensitivity, and good stability. Sensors fabricated using this method exhibit an improved sensitivity of 0.0331 kPa−1 within the broad working range of 0.11–1250 kPa, ultra-fast response time of 8 ms, and good stability as well as repeatability over 2500 cycles of 15% strain loading. The sensing mechanism and resistance model of the sensor were investigated, and a sensing model based on the tunneling effect and resistance model was developed. The coefficient of determination between the model and the experimental data exceeded 0.99, thereby verifying its validity. Finally, a sensor array was tested to locate the pressure and recognize the object shape within a large pressure range, demonstrating its potential applications in engineering fields with high-pressure requirements. This study provides a reference for the simple and cost-effective manufacturing of advanced flexible sensors and offers valuable insights into the large-scale production of flexible sensors.