Dynamic Conductance Research Articles

Organic heterojunction memristors with enhanced tunable resistive states for artificial synapses

Tunable and uniform evolution of conductance is the key performance metric for neuromorphic computing leveraging memristors. Nonetheless, the stochastic conductance update associated with limited material composition and uncontrollable filament distribution has restricted the tunability that can be customized for targeted synaptic properties. Here, we introduce organic heterojunction memristors utilizing the C60/P3HT bilayer, demonstrating analog switching characteristics with multilevel conductance states. We demonstrate that both conventional bipolar and unipolar voltages can achieve synaptic plasticity modulation for potentiation and depression, offering enhanced tunability. Through in situ Raman spectroscopy and impedance spectroscopy, we directly observe the dynamic alterations within the active layers during switching processes. The reversible migration of ions diminishes the barrier within the polymer layer, leading to highly uniform resistive switching behavior. The C60 layer functions as a confined transport medium, mitigating critical current variability issues. Moreover, we introduce a shunt resistor approach, furnishing analog memristors with selectively adjustable uniformity, enhanced linearity, and expanded dynamic conductance range, providing a general solution adaptable to various memristive hardware architectures.

Exploring natural genetic diversity in a bread wheat multi-founder population: dual imaging of photosynthesis and stomatal kinetics.

Recent research has shown that optimizing photosynthetic and stomatal traits holds promise for improved crop performance. However, standard phenotyping tools such as gas exchange systems have limited throughput. In this work, a novel approach based on a bespoke gas exchange chamber allowing combined measurement of the quantum yield of PSII (Fq'/Fm'), with an estimation of stomatal conductance via thermal imaging was used to phenotype a range of bread wheat (Triticum aestivum L.) genotypes. Using the dual-imaging methods and traditional approaches, we found broad and significant variation in key traits, including photosynthetic CO2 uptake at saturating light and ambient CO2 concentration (Asat), photosynthetic CO2 uptake at saturating light and elevated CO2 concentration (Amax), the maximum velocity of Rubisco for carboxylation (Vcmax), time for stomatal opening (Ki), and leaf evaporative cooling. Anatomical analysis revealed significant variation in flag leaf adaxial stomatal density. Associations between traits highlighted significant relationships between leaf evaporative cooling, leaf stomatal conductance, and Fq'/Fm', highlighting the importance of stomatal conductance and stomatal rapidity in maintaining optimal leaf temperature for photosynthesis in wheat. Additionally, gsmin and gsmax were positively associated, indicating that potential combinations of preferable traits (i.e. inherently high gsmax, low Ki, and maintained leaf evaporative cooling) are present in wheat. This work highlights the effectiveness of thermal imaging in screening dynamic gs in a panel of wheat genotypes. The wide phenotypic variation observed suggested the presence of exploitable genetic variability in bread wheat for dynamic stomatal conductance traits and photosynthetic capacity for targeted optimization within future breeding programmes.

Advanced iontronic spiking modes with multiscale diffusive dynamics in a fluidic circuit

Fluidic iontronics is emerging as a distinctive platform for implementing neuromorphic circuits, characterised by its reliance on the same aqueous medium and ionic signal carriers as the brain. Drawing upon recent theoretical advancements in both iontronic spiking circuits and in dynamic conductance of conical ion channels, which form fluidic memristors, we expand the repertoire of proposed neuronal spiking dynamics in iontronic circuits. Through a modelled circuit containing channels that carry a bipolar surface charge, we extract phasic bursting, mixed-mode spiking, tonic bursting, and threshold variability, all with spike voltages and frequencies within the typical range for mammalian neurons. These features are possible due to the strong dependence of the typical conductance memory retention time on the channel length, enabling timescales varying from individual spikes to bursts of multiple spikes within a single circuit. These advanced forms of neuronal-like spiking support the exploration of aqueous iontronics as an interesting platform for neuromorphic circuits.

Transit‐Time Instability Mechanism in Lateral Graphene n+‐i‐n‐i‐n+ Structure with Transverse Terahertz Pasmonic Resonant Cavity

The terahertz (THz) plasmonic instability in the lateral graphene structure (LGS) with the n+‐i‐n‐i‐n+ junction in its graphene channel (GC) is analyzed. The i‐regions in the LGS n+‐i‐n‐i‐n+ GC plays the role of the transit spaces of the electrons emitted from the n+‐regions (the emitters) and collected by the gated n‐region (collector) and the side contact to the latter. The interband Zener–Klein tunneling (ZKT) in the i‐regions also contributes to the currents received by the n‐region. Simultaneously, the n‐region constitutes the transverse resonant plasmonic cavity, in which the plasmons with the wave vector directed perpendicular to the electron propagation direction are excited. The plasmonic instability in the LGSs is associated with the transit‐time negative dynamic conductance of the i‐regions supported by the plasmonic resonances in the n‐region. The self‐excitation of plasmonic oscillations associated with the instability in the LGS with sub‐micrometer i‐regions and supplied with a proper antenna can lead to the emission of THz radiation. The LGS can form periodic arrays, which can serve as an active distributed antenna.

Alleviation of the on-state dynamic conductance decline in a GaN high electron mobility transistor with heavy carbon doping

Carbon doping is a standard blocking-voltage-enhancing technique for commercial silicon substrate-based AlGaN/GaN power switching transistors, although the incorporation of carbon into GaN may deteriorate the dynamic on-state resistance (dy-R on) properties of the device. Commonly, researchers have believed that the greater the carbon doping, the greater the deterioration in dy-R on. Surprisingly, in this work, the opposite was observed: the dy-R on value decreased as the carbon concentration increased, particularly when the density exceeded several 1017 cm−3. This phenomenon is explained by the effect of electric field-induced band-to-band electron tunneling into the two-dimensional electron gas (2DEG) conduction channel, originating from the ionization of acceptor-like nitrogen site carbon atoms (CN) in the device off-state with large drain bias. Simulation data indicated that negatively ionized CN may generate a much larger electric field in samples with higher carbon doping, which may induce a narrower 2DEG back energy band barrier that increases the possibility of electron band-to-band tunneling.

Real-time imaging of individual electropores proves their longevity in cells

With over 50 years of electroporation research, the nature of cell membrane permeabilization remains elusive. The lifetime of electropores in molecular models is limited to nano- or microseconds, whereas the permeabilization of electroporated cells can last minutes. This study aimed at resolving a longstanding debate on whether the prolonged permeabilization is due to the formation of long-lived pores in cells. We developed a method for dynamic monitoring and conductance measurements of individual electropores. This was accomplished by time-lapse total internal reflection fluorescence (TIRF) imaging in HEK cells loaded with CAL-520 dye and placed on an indium tin oxide (ITO) surface. Applying a 1-ms, 0 to −400 mV pulse between the patch pipette and ITO evoked focal Ca2+ transients that identified individual electropores. Some transients disappeared in milliseconds but others persisted for over a minute. Persistent transients (“Ca2+ plumes”) faded over time to a stable or a randomly fluctuating level that could include periods of full quiescence. Single pore conductance, measured by 0 to −50 mV, 50 ms steps at 30 and 60 s after the electroporation, ranged from 80 to 200 pS. These experiments proved electropore longevity in cells, in stark contrast to molecular simulations and many findings in lipid bilayers.

Effect of Grain Size on Resistivity and Voltage-Dependent Dynamic Conductance in Nano-crystalline Nd$$_{0.6}$$Sr$$_{0.4}$$CoO$$_3$$

Effect of Grain Size on Resistivity and Voltage-Dependent Dynamic Conductance in Nano-crystalline Nd$$_{0.6}$$Sr$$_{0.4}$$CoO$$_3$$

Negative dynamic conductance of a quantum wire with unscreened Coulomb interaction

Negative dynamic conductance of a quantum wire with unscreened Coulomb interaction

Multi-step depth model predictive control for photovoltaic maximum power point tracking under partial shading conditions

This work avoids the photovoltaic array operating point falling into local maximum power points (MPPs) and optimizes the dynamic process of photovoltaic array global MPP tracking under partial shading conditions (PSCs) by the proposed multi-step depth model predictive control (MDMPC). The MDMPC updates the dynamic conductance at different moments to achieve multi-step accurate predictions of the system state. Combining deep neural networks and the global MPP calculation model can rapidly estimate the global MPP under different topologies. The proposed two-stage optimization adaptively adjusts the optimization function according to the purpose of different stages. The simulated system response curves and performance indexes under different PSCs show that the MDMPC can avoid the operating point falling into local MPPs and accurately rapidly track to the global MPP with higher power generation efficiency. In addition, the hardware-in-the-loop experimental results verify that MDMPC can rapidly and accurately track the global MPP under three PSCs.

Coupling coefficient analysis of composite bar: A new idea for the design of multi-resonant longitudinal transducer

Multi-resonant longitudinal transducers are widely used in sonar technology by exciting multiple resonant modes to extend the operating bandwidth. However, the existing design methods of multi-resonant longitudinal transducers lack unified and effective theoretical guidance, and usually require extensive parameter searches and calculations, so it is not universal and difficult to popularize. Based on the one-dimensional longitudinal vibration theory, the mode analysis and harmonic analysis of the single piezoelectric bar and the composite bar are carried out, and the physical mechanism of the modes not being excited is revealed. Then, starting with the original definition of electromechanical coupling coefficient, the effective coupling coefficients of the composite bar at different resonant modes are given. Finally, a method to adjust the relative strength of resonant modes is proposed based on the relationship between dynamic conductance and effective coupling coefficient. In this paper, electromechanical coupling coefficient is taken as the core factor of transducer design, which holds the key point and provides a new idea for the design of multi-resonant longitudinal broadband transducers.

Leaves as bottlenecks: The contribution of tree leaves to hydraulic resistance within the soil-plant-atmosphere continuum.

Within vascular plants, the partitioning of hydraulic resistance along the soil-to-leaf continuum affects transpiration and its response to environmental conditions. In trees, the fractional contribution of leaf hydraulic resistance (Rleaf ) to total soil-to-leaf hydraulic resistance (Rtotal ), or fRleaf (=Rleaf /Rtotal ), is thought to be large, but this has not been tested comprehensively. We compiled a multibiome data set of fRleaf using new and previously published measurements of pressure differences within trees in situ. Across 80 samples, fRleaf averaged 0.51 (95% confidence interval [CI] = 0.46-0.57) and it declined with tree height. We also used the allometric relationship between field-based measurements of soil-to-leaf hydraulic conductance and laboratory-based measurements of leaf hydraulic conductance to compute the average fRleaf for 19 tree samples, which was 0.40 (95% CI = 0.29-0.56). The in situ technique produces a more accurate descriptor of fRleaf because it accounts for dynamic leaf hydraulic conductance. Both approaches demonstrate the outsized role of leaves in controlling tree hydrodynamics. A larger fRleaf may help stems from loss of hydraulic conductance. Thus, the decline in fRleaf with tree height would contribute to greater drought vulnerability in taller trees and potentially to their observed disproportionate drought mortality.

A new method for solving arcs of pantograph network based on Newton’s iterative method

It has been verified that the discharge pulse generated by the pantograph-catenary system has the biggest impact on the high-speed EMU as the electromagnetic interference source. But the spectrum obtained from the existing pantograph discharge model does not contain high frequencies and is far from the measurement results. In this paper, a novel scheme based on Newton’s method and finite difference time domain (FDTD) algorithm was presented to solve this problem. Firstly, Newton’s method was utilized to solve the Habedank model, and the dynamic conductance of the arc was obtained. Then, the equivalent distributed parameter circuit model of the traction power supply system was established, which was solved by the FDTD and state variable method to obtain the time-domain waveform of the arc voltage. The significant features of this scheme are that it can realize the synchronous calculations of the arc dynamic conductance and the voltage responses along the catenary. Through this scheme, a stable arc voltage time domain waveform can be obtained, and the arc voltage spectrum is highly consistent with the test results.

An efficient deep neural network accelerator using controlled ferroelectric domain dynamics

The current work reports an efficient deep neural network (DNN) accelerator, where analog synaptic weight elements are controlled by ferroelectric (FE) domain dynamics. An integrated device-to-algorithm framework for benchmarking novel synaptic devices is used. In poly(vinylidene fluoride-trifluoroethylene)-based ferroelectric tunnel junctions (FTJs), analog conductance states are measured using a custom pulsing protocol, and associated control circuits and array architectures for DNN training are simulated. Our results show that precise control of polarization switching dynamics in multi-domain polycrystalline FE thin films can produce considerable weight-update linearity in metal–ferroelectric–semiconductor (MFS) tunnel junctions. Ultrafast switching and low junction currents in these devices offer extremely energy-efficient operation. Via an integrated platform of hardware development, characterization and modeling, we predict the available conductance range, where linearity is expected under identical potentiating and depressing pulses for efficient DNN training and inference tasks. As an example, an analog crossbar-based DNN accelerator with MFS junctions as synaptic weight elements showed >93% training accuracy on a large MNIST handwritten digit dataset while, for cropped images, >95% accuracy is achieved. One observed challenge is the rather limited dynamic conductance range while operating under identical potentiating and depressing pulses below 1 V. Investigation is underway to improve the FTJ dynamic conductance range, maintaining the weight-update linearity under an identical pulse scheme.

Transit-time resonances enabling amplification and generation of terahertz radiation in periodic graphene p-i-n structures with the Zener–Klein interband tunneling

The Zener–Klein (ZK) interband tunneling in graphene layers (GLs) with the lateral n-i-n and p-i-n junctions results in the specific characteristics that can be used for the rectification, detection, amplification, and generation of the terahertz (THz) signals. The transit-time delay of the tunneling electrons and holes in the depletion regions leads to the phase shift between the THz current and THz voltage causing the negative dynamic conductance in a certain frequency range and resulting in the so-called transit-time (TT) instability. The combination of the ZK tunneling and the TT negative dynamic conductance enables resonant THz the amplification and generation of THz radiation. We propose the THz devices based on periodic cascade GL p-i-n structures exhibiting the TT resonances and evaluate their potential performance. Such structures can serve as THz amplifiers and, being placed in a Fabry–Pérot cavity, or coupled to a THz antenna or using a ring oscillator connection, as THz radiation sources.

Real-Time Anticipation and Prevention of Hot Spots by Monitoring the Dynamic Conductance of Photovoltaic Panels

Hot spotting in photovoltaic (PV) panels causes physical damage, power loss, reduced lifetime reliability, and increased manufacturing costs. The problem arises routinely in defect-free standard panels; any string of cells that receives uneven illumination can develop hot spots, and the temperature rise often exceeds 100 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^\circ$</tex-math></inline-formula> C in conventional monocrystalline-silicon panels despite on-panel bypass diodes, the standard mitigation technique. Bypass diodes limit the power dissipated in a cell subjected to reverse bias, but they do not prevent hot spots from forming. An alternative control method has been suggested by Kernahan (Kernahan, 2015) that senses in real time the dynamic conductance <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$|$</tex-math></inline-formula> d <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">I</i> /d <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">V</i> <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$|$</tex-math></inline-formula> of a string of cells and adjusts its operating current so that a partially shaded cell is never forced into reverse bias. We start by exploring the behavior of individual illuminated PV cells when externally forced into reverse bias. We observe that cells can suffer significant heating and structural damage, with desoldering of cell-tabbing and discolorations on the front cell surface. Then we test PV panels and confirm Kernahan’s proposed panel-level solution that anticipates and prevents hot spots in real time. Simulations of cells and panels confirm our experimental observations and provide insights into both the operation of Kernahan’s method and panel performance.

Temperature dependence of tunnel magnetoresistance in serial magnetic tunnel junctions

Magnetic tunnel junctions have been widely used in various applications, such as magnetic sensors and magnetic random-access memories. In the practical application of MTJs, they are usually used in series toward high sensitivity and high stability, especially for sensor applications. In this paper, serial MTJs devices on 8 in. wafers were fabricated. The temperature dependence of the tunnel magnetoresistance ratio, resistances in parallel and antiparallel configurations, and dynamic conductance were systematically investigated. The results of serial MTJs devices are consistent with a single MTJ device. This research suggests that serial MTJs can be directly used to investigate the magnetic tunneling properties of MTJ stacks.

Ion Density-Dependent Dynamic Conductance Switching in Biomimetic Graphene Nanopores.

Gating in ion transport is at the center of many vital living-substance transmission processes, and understanding how gating works at an atomic level is essential but intricate. However, our understanding and finite experimental findings of subcontinuum ion transport in subnanometer nanopores are still limited, which is out of reach of the classical continuum nanofluidics. Moreover, the influence of ion density on subcontinuum ion transport is poorly understood. Here we report the ion density-dependent dynamic conductance switching process in biomimetic graphene nanopores and explain the phenomenon by a reversible ion absorption mechanism. Our molecular dynamics simulations demonstrate that the cations near the graphene nanopore can interact with the surface charges on the nanopore, thereby realizing the switching of high- and low-conductance states. This work has deepened the understanding of gating in ion transport.

Origin of photo-enhanced hysteretic electrical conductance in nanostructured silicon-based heterojunction

Photo-enhanced hysteretic I–V curves have been observed under reverse bias in a p-i-n structure containing electrochemically etched nanostructured silicon (Si) sandwiched between p-Si and n-type a-Si:H layers. These curves have been found to depend on intensity of incident illumination and structural morphology of the nanostructured Si layer. The conductance in trace path is lower than that in retrace path. Charge transport mechanism in this structure has been interpreted using microscopic description of charge trapping and detrapping in the defect states present at the interface of nanocrystalline silicon core and oxide shell in the active layer. An applied voltage dependent probability distribution of trapping and detrapping has been calculated in light of classical random walk problem. The trapping/detrapping of charges leading to development/destruction of potential barriers in the path of charge flow shows an analogy with the river bed deposition/erosion. The rate of trapping has been considered to depend on the empty defect states whereas the rate of detrapping depends on the already filled defects. Moreover, the rate of both trapping and detrapping is expected to depend on the charge flow rate. All these considerations lead the I–V relations for trace and retrace paths in reverse bias fitting nicely with experimental I–V loops. The observed peaks in the voltage dependent dynamic conductance in trace and retrace paths have been explained as a consequence of development and destruction of two barriers in the active layer for electrons and holes separately. Best fit values of the fitting parameters indicates that the trace path is dominated by holes whereas the retrace path is dominated by electronic transport. The difference in mobility of electron and hole leads to different trapping and detrapping rates in the two paths resulting in the observed hysteresis.

Collisions of random walks in dynamic random environments

We study dynamic random conductance models on Z2 in which the environment evolves as a reversible Markov process that is stationary under space-time shifts. We prove under a second moment assumption that two conditionally independent random walks in the same environment collide infinitely often almost surely. These results apply in particular to random walks on dynamical percolation.

Dynamic Self-Rectifying Liquid Metal-Semiconductor Heterointerfaces: A Platform for Development of Bioinspired Afferent Systems.

The assembly of geometrically complex and dynamically active liquid metal/semiconductor heterointerfaces has drawn extensive attention in multidimensional electronic systems. In this study the chemovoltaic driven reactions have enabled the microfluidity of hydrophobic galinstan into a three-dimensional (3D) semiconductor matrix. A dynamic heterointerface is developed between the atomically thin surface oxide of galinstan and the TiO2-Ni interface. Upon the growth of Ga2O3 film at the Ga2O3-TiO2 heterointerface, the partial reduction of the TiO2 film was confirmed by material characterization techniques. The conductance imaging spectroscopy and electrical measurements are used to investigate the charge transfer at heterointerfaces. Concurrently, the dynamic conductance in artificial synaptic junctions is modulated to mimic the biofunctional communication characteristics of multipolar neurons, including slow and fast inhibitory and excitatory postsynaptic responses. The self-rectifying characteristics, femtojoule energy processing, tunable synaptic events, and notably the coordinated signal recognition are the main characteristics of this multisynaptic device. This novel 3D design of liquid metal-semiconductor structure opens up new opportunities for the development of bioinspired afferent systems. It further facilitates the realization of physical phenomena at liquid metal-semiconductor heterointerfaces.