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Magneto-ionics, understood as voltage-driven ion transport in magnetic materials, could represent a significant breakthrough in the search for routes to enhance energy efficiency in magnetically-actuated devices. Particularly, magneto-ionics in Co3O4 allows for voltage-controlled ON−OFF ferromagnetism, since Co3O4 (paramagnetic) can be partially reduced to Co (ferromagnetic) by voltage actuation and reversed by applying a voltage of opposite polarity [1]. This could be used to binary encode information: for example, OFF = 0 (paramagnetism) and ON = 1 (ferromagnetism). However, ion motion at room temperature is still too slow for applications. The way to apply electric field (voltage actuation) can have a strong impact on the room temperature magneto-ionic motion. Specifically, in electrolyte-gated paramagnetic Co3O4 films, the oxygen magneto-ionic motion can be increased by more than one order of magnitude by applying the electric field through an electrochemical capacitor configuration (i.e., using, as working electrode, an underlying conducting buffer layer beneath the Co3O4 film) rather than using an electric-double-layer transistor-like configuration (i.e., placing the electric contact at one side of the Co3O4 film as working electrode). This is due to a greater uniformity and strength of the electric field in the capacitor design [1,2].

[1] A. Quintana, E. Menéndez, M. O. Liedke, M. Butterling, A. Wagner, V. Sireus, P. Torruella, S. Estradé, F. Peiró, J. Dendooven, C. Detavernier, P. D. Murray, D. A. Gilbert, K. Liu, E. Pellicer, J. Nogues and J. Sort, Voltage-controlled ON−OFF ferromagnetism at room temperature in a single metal oxide film, ACS Nano 12 (2018) 10291–10300
[2] J. de Rojas, A. Quintana, A. Lopeandía, J. Salguero, J. L. Costa-Krämer, L. Abad, M. O. Liedke, M. Butterling, A. Wagner, L. Henderick, J. Dendooven, C. Detavernier, J. Sort and E. Menéndez, Boosting room-temperature magneto-ionics in a non-magnetic oxide semiconductor, Advanced Functional Materials 30 (2020) 2003704

Materials Challenges for Memory

ON-OFF magneto-ionics in Co3O4

oxygen transport

electrolyte-gating

magneto-ionics

#### Welcome to the 67th Annual Conference on Magnetism and Magnetic Materials, MMM 2022!

The Conference was held from October 31 to November 4 and offers both in-person and on-demand content.

MMM 2022 is sponsored jointly by AIP Publishing and the IEEE Magnetics Society. Members of the international scientific and engineering communities interested in recent developments in fundamental and applied magnetism are invited to attend and contribute to the technical sessions. The technical program will include invited and contributed papers in oral and poster sessions, invited symposia, a tutorial, and several special sessions. This Conference provides an outstanding opportunity for worldwide participants to meet their colleagues and collaborators and discuss developments in all areas of magnetism research.

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MMM 2022

This Conference provides an outstanding opportunity for worldwide participants to meet their colleagues and collaborators and discuss developments in all areas of magnetism research.

poster


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The energy cost of storing and moving data is enormous, and is growing at such a rapid pace that within a few years the power demand may overwhelm some developed nations. Non-volatile memory (NVM) and neuromorphic computing are enabling critical advances in this area, but there are many scientific and technological challenges. This conference will cover the materials challenges of different memory technologies, from the fundamental processes and mechanisms, to industry perspectives on materials specifications and manufacturing.

Voltage-controlled magnetism (VCM) utilizes an applied electric field to modulate magnetic properties in a material instead of current, potentially representing a sizable increase in energy savings in next-generation technology and devices. However, VCM still faces several difficult challenges: a scarcity of room-temperature multiferroics, mechanical fatigue and failure in strain-mediated piezoelectric/magnetostrictive devices, and thickness limitations in charged metallic films. Voltage-driven ionic motion (magneto-ionics) presents an alternative which does not suffer from many of these drawbacks, although translating magneto-ionics into real world devices requires significant improvements in magneto-ionic rates, cyclability, and changes in magnetization. Here, we report on room-temperature voltage-driven nitrogen magneto-ionics (via N transport) by electrolyte-gating of a CoN film using a propylene carbonate liquid electrolyte[1]. Nanocrystalline (face-centered cubic structure) CoN and Co3O4 films biased using an electrochemical capacitor configuration are compared. Both materials show reversible voltage-driven ON-OFF ferromagnetism, albeit with CoN displaying a remarkable 6-fold advantage in magneto-ionic rate. Nitrogen transport in CoN is found to occur uniformly throughout the film, creating a plane-wave-like migration front, without assistance of diffusion channels, in sharp contrast with oxygen transport in Co3O4, where ion diffusion is more inhomogeneous and preferentially occurs along grain boundaries. Nitrogen magneto-ionics in CoN is also shown to require lower onset voltages than oxygen magneto-ionics, as well as enhanced rates and cyclability due to the combination of a lower energy barrier for ion diffusion (and, hence, minimum applied voltage) and the lower electronegativity of nitrogen with respect to oxygen, consistent with ab initio calculations of N vs. O ion motion in a cobalt lattice. These promising results suggest nitrogen magneto-ionics can be tantalizing alternative for efficient voltage-driven effects and, alongside oxygen magneto-ionics, may enable the use of magneto-ionics in devices such as brain-inspired/stochastic computing or magnetic micro-electro-mechanical systems.

Nitrogen Magneto-ionics

The resistive switching (RS) is a physical phenomenon where an insulating material changes its state of resistance from high resistance state (HRS) to low resistance state (LRS) and vice versa with the application of the external electric field. Many materials has been investigated as an active material for the resistive switching based device but still lots of research is still going on in the finding of better one. Among all the existing materials, oxide materials have proven itself a best candidate for the application of the memory-based device due to its robust nature. The oxygen vacancies play a very crucial role in the oxide materials for the initiation of the resistive switching phenomena. ZnO is a semiconducting material having wide bandgap. Various attempts have been reported to improve the ZnO as a switching layer, like stacking of ZnO with different electrodes, changing the deposition parameters, doping with various elements, post thermal treating and by controlling its growth deposition. The presence of interstitial layer also play important role to enhance the RS switching characteristics. Therefore, based on above discussion, a comprehensive study has done in the resistive switching behavior of the Ag/LSMO/ZnO/ITO device to observe the effect of LSMO as an interfacial layer. The device shows bipolar RS switching type behavior with stability in the operating voltages up to 80 cycles of testing. The ION/IOFF ratio is observed around 102. The LSMO can be act as the reservoir for the oxygen vacancies, which attracts oxygen ions from the ZnO to form the conducting filament type structure by the application of positive voltage. Thus, the formation/rupture of the oxygen vacancies based conducting filament structure in the active materials helps to switch the state of resistance. The introduction of oxygen vacancies in the ZnO leads to the shifting of energy states towards the Fermi level and introducing the metallic characteristic in it. From the density functional theory (DFT) calculation, the role of oxygen vacancies is further confirmed and claimed that, it is highly responsible behind the resistive switching behavior of ZnO.

Resistive Switching behavior of ZnO in the presence of La0.7Sr0.3MnO3 as an Interfacial layer

Magnetic nanofibers can be applied for data transport and storage and are highly interesting in basic research. One of the reasons for their broad investigation is that can be produced by electrospinning [1]. Such bent nanofibers, however, show a broad spectrum of possible magnetization reversal processes and magnetization dynamics, dependent on their bending radius and diameter, the magnetic field orientation relative to the fiber axis, etc. [2].
Besides quasistatic processes, dynamic investigations are used to evaluate the possible data transport through such magnetic nanofibers. Here we report on domain wall nucleation and propagation through nanowires with different bending radii, from single nanowires to networks with multiple data inputs and outputs. In these simulations, diverse phenomena occur which have to be taken into account during these dynamic processes, like domain wall instabilities or interference between converging signals, resulting in a spectrum of possible architectures for nanowire-based logics.

[1] C. Döpke, T. Grothe, P. Steblinski, M. Klöcker, L. Sabantina, D. Kosmalska, T. Blachowicz, A. Ehrmann, Magnetic nanofiber mats for data storage and transfer, Nanomaterials 9, 92 (2019).
[2] T. Blachowicz, A. Ehrmann, Magnetization reversal in bent nanofibers of different cross-sections, J. Appl. Phys. 124, 152112 (2018).


Micromagnetic simulation of magnetization dynamics in nanofiber networks

The development of alternative brain-inspired neuromorphic computing architectures is anticipated to play a key role in addressing the strict requirements of the artificial intelligence (AI) era. In order to obtain a high degree of learning accuracy within an artificial neural network (ANN) that operates with the backpropagation algorithm, a highly symmetric synaptic weight distribution is desired. Along these lines, we present here a detailed device engineering approach that enables analog synaptic properties in completely forming free SiO2-conductive bridge memories (CBRAM). This is achieved, by either incorporating a dense layer of Pt nanoparticles (NPs) as a bottom electrode (BE) or by fabricating bilayer structures using a second switching layer of VOx. Interestingly, compared with the reference sample that manifests both threshold and bipolar switching modes, the Pt NCs sample exhibits only the threshold switching pattern whereas the bilayer configuration operates only under the bipolar switching mode as illustrated by direct current (DC) measurements. These characteristics have a direct, while different impact, on the conductance modulation pattern and determine the analog nature of the synaptic weight distribution. 


Enhancing the analog synaptic properties of forming free SiO2 memristors by materials engineering approach

We grew La2NiMnO6 (LNMO) films by radiofrequency off-axis magnetron sputtering on a variety of oxide perovskite substrates. Structural characterization indicates high crystalline quality, absence of parasitic defects and rock-salt ordering of the NiO 6 and MnO 6 octahedra with only minimal degree of antisite disorder. 
X-ray absorption spectroscopy (XAS) and confirms the stabilization of Ni 2+ and Mn 4+ valence states. When lowering the thickness of LNMO films grown on SrTiO 3 (STO) we observe a degradation of the ferromagnetic properties that is accompanied by an increase of antisite disorder at the interface between LNMO and STO. Moreover, the polarity mismatch between the film and the substrate triggers an electronic reconstruction that results in additional Mn 3+ states at the LNMO//STO interface.
Despite this occurrence, films as thin as 2 pseudocubic unit cells (0.8 nm) are still ferromagnetic, as verified by x-ray magnetic circular dichroism (XMCD). Capping the LNMO films with a LaNiO 3 layer results in the disappearing of the Mn 3+ content that is supplemented by a restoration of the Curie temperature. 
Considering the scarcity of ferromagnetic insulators, LNMO shows great potential to become a significant element for both fundamental research and promising spintronic applications.

Electronic reconstruction in ferromagnetic insulating double perovskite heterointerfaces

We report a novel delayed-electroforming process in Metal-Insulator-Metal Au/Ti/SiOx/Mo ReRAM devices; this new process allows more energy-efficient switching. For this novel process to occur, a highly resistive pristine device must be stressed under a fixed high voltage for a varying amount of time. The stress time of a device is determined by the amount of charge going through the oxide during stressing. Once a fixed amount of charge has gone through the device, a small detection voltage of 10mV is applied. The device continues to show high resistance (~MΩ) after stressing, and abruptly reaches a low resistance state (~100Ω) after a delay. We investigated the effect of charge injection during stressing, and found good correlation between charge injected during stressing and the delay time after stressing. Additionally, we found that we can modulate conductance of the formed devices by varying amount of charge injection. Based on these results, we propose a charge assisted electroforming model to explain this novel phenomenon.

A Charge-Assisted Delayed-Electroforming Phenomenon in Silicon Oxide

Logic-in-memory architectures based on resistive random access memory (RRAM) technology and the material implication (IMPLY) logic are a promising solution for the development of energy efficient computing hardware for edge computing applications. However, RRAM devices nonidealities, such as cycle-to-cycle variability and random telegraph noise, and circuit-related issues such as logic state degradation, strongly affect the reliability of these circuits and complicate their design. In this, work we use a physics-based RRAM compact model which reproduces the effect of device nonidealities (i.e., variability, Random Telegraph Noise, self-heating) and that was calibrated on three RRAM technologies from the literature to study the reliability and performance of a conventional and a recently proposed smart IMPLY architectures. Finally, we underline the importance of the physics-based RRAM compact model as a tool for implementing device-circuit co-design strategies.

Device-circuit co-design of logic-in-memory circuits using a physics-based RRAM compact model

Electrospinning can be used to produce nanofibers from magnetic materials, forming a magnetic network which may be applied in neuromorphic computing. Besides the influence of the bending radii on the magnetization reversal in such nanofibers [1], the often occurring beads along the fibers have not yet been investigated in detail. Such beads can be assumed to support domain wall formation due to a reduction of the relative impact of the shape anisotropy, in this way influencing magnetization reversal along the fiber. 
Here, we show results of simulations of magnetization reversal processes in iron, nickel, cobalt and magnetite fibers with a bead in the middle, produced in three typical dimensions gained by electrospinning [2]. Mostly, magnetization reversal occurs via a vortex state, for all materials and dimensions. Only some angular orientations of the external magnetic field result in double-vortex or meander states, usually followed by a vortex state. The simulations emphasize the impact of beads along electrospun magnetic nanofibers, making magnetization reversal highly reliable and thus such structures useful for data storage and transport in neuromorphic computing and other applications.

References
[1] T. Blachowicz, A. Ehrmann, Magnetization reversal in bent nanofibers of different cross-sections, J. Appl. Phys. 124, 152112 (2018).
[2] F. Amini, T. Blachowicz, A. Ehrmann, Systematic study of magnetization reversal in beaded fibers from different magnetic materials, J. Magn. Magn. Mater. 529, 167855 (2021)

Magnetization reversal in nanofibers with beads from different magnetic materials

Real-time tracking of high-speed objects in cognitive tasks is challenging in the present artificial intelligence techniques because the data processing and computation are time consuming, resulting in impeditive time delays. A brain-inspired continuous attractor neural network (CANN) can be used to track fast moving targets, where the time delays are intrinsically compensated if the dynamical synapses in the network have short-term plasticity. Here, we show that synapses with short-term depression can be realized by a magnetic tunnel junction, which perfectly reproduces the dynamics of the synaptic weight in a widely applied mathematical model. Then, these dynamical synapses are incorporated into one-dimensional and two-dimensional CANNs, which are demonstrated to have the ability to predict a moving object via micromagnetic simulations. This portable spintronics-based hardware for neuromorphic computing needs no training and is therefore very promising for the tracking technology of moving targets. [1]
[1] Q. Zheng, X. Zhu, Y. Mi, Z. Yuan, and K. Xia, Physical Review Applied 14, 044060 (2020).

Anticipative Tracking with the Short-Term Synaptic Plasticity of Spintronic Devices

A resistive switching ZnO homojunction diode fabricated with a stack of two dissimilar ZnO thin film shows promising characteristics necessary to address the crosstalk [1] problem in a cross-bar memory array. The device has a characteristic IV-hysteresis loop in forward bias, in conjunction with its pn junction characteristics. In the ac frequency range of 10 Hz to 15 kHz, the area inside the hysteresis loop initially increased, reaching a maximum at 1 kHz, and then decreases with increasing frequency. The maximum in the area of the hysteresis loop corresponds to the accumulation of space charge at the interface. The resistivity of the device was found to vary from 5 kΩ to 100 kΩ in the bias range 0V - 10V and in the range of 106 Ω when reverse biased the ratio of High Resistive State (HRS) to Low Resistive State (LRS) [2] has its maximum (~2.4) at 1 kHz ac signal at 3V.


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