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Results of measurements on the thermoelectric power of 45 nm diameter interconnected nanowire networks consisting of pure Fe, dilute FeCu and FeCr alloys and Fe/Cu multilayers are presented. The thermopower values of Fe nanowires are very close to those found in bulk materials, at all temperatures studied between 70 and 320 K. For pure Fe, the diffusion thermopower at room temperature, estimated to be around - 15 [Formula: see text]V/K from our data, is largely supplanted by the estimated positive magnon-drag contribution, close to 30 [Formula: see text]V/K. In dilute FeCu and FeCr alloys, the magnon-drag thermopower is found to decrease with increasing impurity concentration to about 10 [Formula: see text]V/K at 10[Formula: see text] impurity content. While the diffusion thermopower is almost unchanged in FeCu nanowire networks compared to pure Fe, it is strongly reduced in FeCr nanowires due to pronounced changes in the density of states of the majority spin electrons. Measurements performed on Fe(7 nm)/Cu(10 nm) multilayer nanowires indicate a dominant contribution of charge carrier diffusion to the thermopower, as previously found in other magnetic multilayers, and a cancellation of the magnon-drag effect. The magneto-resistance and magneto-Seebeck effects measured on Fe/Cu multilayer nanowires allow the estimation of the spin-dependent Seebeck coefficient in Fe, which is about - 7.6 [Formula: see text]V/K at ambient temperature.
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Thermoelectric energy conversion based on flexible materials has great potential for applications in the fields of low-power heat harvesting and solid-state cooling. Here, we show that three-dimensional networks of interconnected ferromagnetic metal nanowires embedded in a polymer film are effective flexible materials as active Peltier coolers. Thermocouples based on Co-Fe nanowires exhibit much higher power factors and thermal conductivities near room temperature than other existing flexible thermoelectric systems, with a power factor for Co-Fe nanowire-based thermocouples of about 4.7 mW/K2m at room temperature. The effective thermal conductance of our device can be strongly and rapidly increased by active Peltier-induced heat flow, especially for small temperature differences. Our investigation represents a significant advance in the fabrication of lightweight flexible thermoelectric devices, and it offers great potential for the dynamic thermal management of hot spots on complex surfaces.
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A network of silver nanowires (Ag-NWs) is grown by electrodeposition in a nanoporous membrane with interconnected nanopores. This bottom-up approach fabrication method gives a conducting network with a 3D architecture and a high density of Ag-NWs. The network is then functionalized during the etching process, which leads to a high initial resistance as well as memristive behavior. The latter is expected to arise from the creation and the destruction of conducting silver filaments in the functionalized Ag-NW network. Moreover, after several cycles of measurement, the resistance of the network switches from a high-resistance regime in the GΩ range with tunnel conduction to a low-resistance regime presenting negative differential resistance in the kΩ range.
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We investigate the impact of the DC current-induced Ampère-Oersted field on the dynamics of a vortex based spin-torque nano-oscillator. In this study we compare micromagnetic simulations performed using mumax[Formula: see text] and our analytical model based on the Thiele equation approach. The latter is improved by adding two important corrections to the Thiele equation approach. The first is related to the magneto-static contribution and depends on the aspect ratio of the magnetic dot. The second is a full analytical description of the Ampère-Oersted field contribution. The model describes quantitatively the simulation results in the resonant regime as well as the impact of the Ampère-Oersted field. Depending on the relative orientation between the vortex in-plane curling magnetisation (chirality) and the Ampère-Oersted field a strong splitting phenomenon appears in the fundamental properties (frequency and vortex core position) of the nano-oscillator. Thus, we show that the Ampère-Oersted field should not be neglected as it has a high impact on the spin-torque vortex oscillator dynamics.
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The versatility of the template-assisted electrodeposition technique to fabricate complex three-dimensional networks made of interconnected nanowires allows one to easily stack ferromagnetic and non-magnetic metallic layers along the nanowire axis. This leads to the fabrication of unique multilayered nanowire network films showing giant magnetoresistance effect in the current-perpendicular-to-plane configuration that can be reliably measured along the macroscopic in-plane direction of the films. Moreover, the system also enables reliable measurements of the analogous magneto-thermoelectric properties of the multilayered nanowire networks. Here, three-dimensional interconnected NixFe1-x/Cu multilayered nanowire networks (with 0.60≤x≤0.97) are fabricated and characterized, leading to large magnetoresistance and magneto-thermopower ratios up to 17% and -25% in Ni80Fe20/Cu, respectively. A strong contrast is observed between the amplitudes of magnetoresistance and magneto-thermoelectric effects depending on the Ni content of the NiFe alloys. In particular, for the highest Ni concentrations, a strong increase in the magneto-thermoelectric effect is observed, more than a factor of 7 larger than the magnetoresistive effect for Ni97Fe3/Cu multilayers. This sharp increase is mainly due to an increase in the spin-dependent Seebeck coefficient from -7 µV/K for the Ni60Fe40/Cu and Ni70Fe30/Cu nanowire arrays to -21 µV/K for the Ni97Fe3/Cu nanowire array. The enhancement of the magneto-thermoelectric effect for multilayered nanowire networks based on dilute Ni alloys is promising for obtaining a flexible magnetic switch for thermoelectric generation for potential applications in heat management or logic devices using thermal energy.
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Electrochemical deposition of interconnected nanowires and nanotubes made of ferromagnetic metals into track-etched polycarbonate templates with crossed nanochannels has been revealed suitable for the fabrication of mechanically stable three-dimensional magnetic nanostructures with large surface area. These 3D networks embedded into flexible polymer membranes are also planar and lightweight. This fabrication technique allows for the control of the geometric characteristics and material composition of interconnected magnetic nanowire or nanotube networks, which can be used to fine-tune their magnetic and magneto-transport properties. The magnetostatic contribution to the magnetic anisotropy of crossed nanowire networks can be easily controlled using the diameter, packing density, or angle distribution characteristics. Furthermore, the fabrication of Co and Co-rich NiCo alloy crossed nanowires with textured hcp phases leads to an additional significant magnetocrystalline contribution to the magnetic anisotropy that can either compete or add to the magnetostatic contribution. The fabrication of an interconnected nanotube network has also been demonstrated, where the hollow core and the control over the tube wall thickness add another degree of freedom to control the magnetic properties and magnetization reversal mechanisms. Finally, three-dimensional networks made of interconnected multilayered nanowire with a succession of ferromagnetic and non-magnetic layers have been successfully fabricated, leading to giant magnetoresistance responses measured in the current-perpendicular-to-plane configuration. These interconnected nanowire networks have high potential as integrated, reliable, and stable magnetic field sensors; magnetic devices for memory and logic operations; or neuromorphic computing.
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Recently, interconnected nanowire networks have been found suitable as flexible macroscopic spin caloritronic devices. The 3D nanowire networks are fabricated by direct electrodeposition in track-etched polymer templates with crossed nano-channels. This technique allows the fabrication of crossed nanowires consisting of both homogeneous ferromagnetic metals and multilayer stack with successive layers of ferromagnetic and non-magnetic metals, with controlled morphology and material composition. The networks exhibit extremely high, magnetically modulated thermoelectric power factors. Moreover, large spin-dependent Seebeck coefficients were directly extracted from experimental measurements on multilayer nanowire networks. This work provides a simple and cost-effective way to fabricate large-scale flexible and shapeable thermoelectric devices exploiting the spin degree of freedom.
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NiFe alloy and NiFe/Cu multilayered nanowire (NW) networks were grown using a template-assisted electrochemical synthesis method. The NiFe alloy NW networks exhibit large thermopower, which is largely preserved in the current perpendicular-to-plane geometry of the multilayered NW structure. Giant magneto-thermopower (MTP) effects have been demonstrated in multilayered NiFe/Cu NWs with a value of 25% at 300 K and reaching 60% around 100 K. A large spin-dependent Seebeck coefficient of -12.3 µV/K was obtained at room temperature. The large MTP effects demonstrate a magnetic approach to control thermoelectric properties of flexible devices based on NW networks.
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The reservoir computing neural network architecture is widely used to test hardware systems for neuromorphic computing. One of the preferred tasks for bench-marking such devices is automatic speech recognition. This task requires acoustic transformations from sound waveforms with varying amplitudes to frequency domain maps that can be seen as feature extraction techniques. Depending on the conversion method, these transformations sometimes obscure the contribution of the neuromorphic hardware to the overall speech recognition performance. Here, we quantify and separate the contributions of the acoustic transformations and the neuromorphic hardware to the speech recognition success rate. We show that the non-linearity in the acoustic transformation plays a critical role in feature extraction. We compute the gain in word success rate provided by a reservoir computing device compared to the acoustic transformation only, and show that it is an appropriate bench-mark for comparing different hardware. Finally, we experimentally and numerically quantify the impact of the different acoustic transformations for neuromorphic hardware based on magnetic nano-oscillators.
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Spin caloritronics has recently emerged from the combination of spintronics and thermoelectricity. Here, we show that flexible, macroscopic spin caloritronic devices based on large-area interconnected magnetic nanowire networks can be used to enable controlled Peltier cooling of macroscopic electronic components with an external magnetic field. We experimentally demonstrate that three-dimensional CoNi/Cu multilayered nanowire networks exhibit an extremely high, magnetically modulated thermoelectric power factor up to 7.5 mW/K2m and large spin-dependent Seebeck and Peltier coefficients of -11.5 µV/K and -3.45 mV at room temperature, respectively. Our investigation reveals the possibility of performing efficient magnetic control of heat flux for thermal management of electronic devices and constitutes a simple and cost-effective pathway for fabrication of large-scale flexible and shapeable thermoelectric coolers exploiting the spin degree of freedom.
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In recent years, artificial neural networks have become the flagship algorithm of artificial intelligence1. In these systems, neuron activation functions are static, and computing is achieved through standard arithmetic operations. By contrast, a prominent branch of neuroinspired computing embraces the dynamical nature of the brain and proposes to endow each component of a neural network with dynamical functionality, such as oscillations, and to rely on emergent physical phenomena, such as synchronization2-6, for solving complex problems with small networks7-11. This approach is especially interesting for hardware implementations, because emerging nanoelectronic devices can provide compact and energy-efficient nonlinear auto-oscillators that mimic the periodic spiking activity of biological neurons12-16. The dynamical couplings between oscillators can then be used to mediate the synaptic communication between the artificial neurons. One challenge for using nanodevices in this way is to achieve learning, which requires fine control and tuning of their coupled oscillations17; the dynamical features of nanodevices can be difficult to control and prone to noise and variability18. Here we show that the outstanding tunability of spintronic nano-oscillators-that is, the possibility of accurately controlling their frequency across a wide range, through electrical current and magnetic field-can be used to address this challenge. We successfully train a hardware network of four spin-torque nano-oscillators to recognize spoken vowels by tuning their frequencies according to an automatic real-time learning rule. We show that the high experimental recognition rates stem from the ability of these oscillators to synchronize. Our results demonstrate that non-trivial pattern classification tasks can be achieved with small hardware neural networks by endowing them with nonlinear dynamical features such as oscillations and synchronization.
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Phase coupling between auto-oscillators is central for achieving coherent responses such as synchronization. Here we present an experimental approach to probe it in the case of two dipolarly coupled spin-torque vortex nano-oscillators using an external microwave field. By phase locking one oscillator to the external source, we observe frequency pulling on the second oscillator. From coupled phase equations we show analytically that this frequency pulling results from concerted actions of oscillator-oscillator and source-oscillator couplings. The analysis allows us to determine the strength and phase shift of coupling between two oscillators, yielding important information for the implementation of large interacting oscillator networks.
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With conventional transistor technologies reaching their limits, alternative computing schemes based on novel technologies are currently gaining considerable interest. Notably, promising computing approaches have proposed to leverage the complex dynamics emerging in networks of coupled oscillators based on nanotechnologies. The physical implementation of such architectures remains a true challenge, however, as most proposed ideas are not robust to nanotechnology devices' non-idealities. In this work, we propose and investigate the implementation of an oscillator-based architecture, which can be used to carry out pattern recognition tasks, and which is tailored to the specificities of nanotechnologies. This scheme relies on a weak coupling between oscillators, and does not require a fine tuning of the coupling values. After evaluating its reliability under the severe constraints associated to nanotechnologies, we explore the scalability of such an architecture, suggesting its potential to realize pattern recognition tasks using limited resources. We show that it is robust to issues like noise, variability and oscillator non-linearity. Defining network optimization design rules, we show that nano-oscillator networks could be used for efficient cognitive processing.
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Due to their nonlinear properties, spin transfer nano-oscillators can easily adapt their frequency to external stimuli. This makes them interesting model systems to study the effects of synchronization and brings some opportunities to improve their microwave characteristics in view of their applications in information and communication technologies and/or to design innovative computing architectures. So far, mutual synchronization of spin transfer nano-oscillators through propagating spinwaves and exchange coupling in a common magnetic layer has been demonstrated. Here we show that the dipolar interaction is also an efficient mechanism to synchronize neighbouring oscillators. We experimentally study a pair of vortex-based spin transfer nano-oscillators, in which mutual synchronization can be achieved despite a significant frequency mismatch between oscillators. Importantly, the coupling efficiency is controlled by the magnetic configuration of the vortices, as confirmed by an analytical model and micromagnetic simulations highlighting the physics at play in the synchronization process.