Direct measurement of nanoscale filamentary hot spots in resistive memory devices

Optical super-resolution nanothermometry via stimulated emission depletion imaging of upconverting nanoparticles

From engineering improved device performance to unraveling the breakdown of classical heat transfer laws, far-field optical temperature mapping with nanoscale spatial resolution would benefit diverse areas. However, these attributes are traditionally in opposition because conventional far-field optical temperature mapping techniques are inherently diffraction limited. Optical super-resolution imaging techniques revolutionized biological imaging, but such approaches have yet to be applied to thermometry. Here, we demonstrate a super-resolution nanothermometry technique based on highly doped upconverting nanoparticles (UCNPs) that enable stimulated emission depletion (STED) super-resolution imaging. We identify a ratiometric thermometry signal and maintain imaging resolution better than ~120 nm for the relevant spectral bands. We also form self-assembled UCNP monolayers and multilayers and implement a detection scheme with scan times >0.25 μm2/min. We further show that STED nanothermometry reveals a temperature gradient across a joule-heated microstructure that is undetectable with diffraction limited thermometry, indicating the potential of this technique to uncover local temperature variation in wide-ranging practical applications.

Memristive Switching Mechanism in Colloidal InP/ZnSe/ZnS Quantum Dot-Based Synaptic Devices for Neuromorphic Computing

Quantum dots (QDs) have garnered a significant amount of attention as promising memristive materials owing to their size-dependent tunable bandgap, structural stability, and high level of applicability for neuromorphic computing. Despite these advantageous properties, the development of QD-based memristors has been hindered by challenges in understanding and adjusting the resistive switching (RS) behavior of QDs. Herein, we propose three types of InP/ZnSe/ZnS QD-based memristors to elucidate the RS mechanism, employing a thin poly(methyl methacrylate) layer. This approach not only allows us to identify which carriers (electron or hole) are trapped within the QD layer but also successfully demonstrates QD-based synaptic devices. Furthermore, to utilize the QD memristor as a synapse, long-term potentiation/depression (LTP/LTD) characteristics are measured, resulting in a low nonlinearity of LTP/LTD at 0.1/1. On the basis of the LTP/LTD characteristics, single-layer perceptron simulations were performed using the Extended Modified National Institute of Standards and Technology, verifying a maximum recognition rate of 91.46%.

Thermal Compact Modeling and Resistive Switching Analysis in Titanium Oxide-Based Memristors

Resistive switching devices based on the Au/Ti/TiO2/Au stack were developed. In addition to standard electrical characterization by means of I-V curves, scanning thermal microscopy was employed to localize the hot spots on the top device surface (linked to conductive nanofilaments, CNFs) and perform in-operando tracking of temperature in such spots. In this way, electrical and thermal responses can be simultaneously recorded and related to each other. In a complementary way, a model for device simulation (based on COMSOL Multiphysics) was implemented in order to link the measured temperature to simulated device temperature maps. The data obtained were employed to calculate the thermal resistance to be used in compact models, such as the Stanford model, for circuit simulation. The thermal resistance extraction technique presented in this work is based on electrical and thermal measurements instead of being indirectly supported by a single fitting of the electrical response (using just I-V curves), as usual. Besides, the set and reset voltages were calculated from the complete I-V curve resistive switching series through different automatic numerical methods to assess the device variability. The series resistance was also obtained from experimental measurements, whose value is also incorporated into a compact model enhanced version.

Spatially-Resolved Thermometry of Filamentary Nanoscale Hot Spots in TiO2 Resistive Random Access Memories to Address Device Variability

Resistive random access memories (RRAM), based on the formation and rupture of conductive nanoscale filaments, have attracted increased attention for application in neuromorphic and in-memory computing. However, this technology is, in part, limited by its variability, which originates from the stochastic formation and extreme heating of its nanoscale filaments. In this study, we used scanning thermal microscopy (SThM) to assess the effect of filament-induced heat spreading on the surface of metal oxide RRAMs with different device designs. We evaluate the variability of TiO2 RRAM devices with area sizes of 2 × 2 and 5 × 5 μm2. Electrical characterization shows that the variability indicated by the standard deviation of the forming voltage is ∼2 times larger for 5 × 5 μm2 devices than for the 2 × 2 μm2 ones. Further knowledge on the reason for this variability is gained through the SThM thermal maps. These maps show that for 2 × 2 μm2 devices the formation of one filament, i.e., hot spot at the device surface, happens reliably at the same location, while the filament location varies for the 5 × 5 μm2 devices. The thermal information, combined with the electrical, interfacial, and geometric characteristics of the device, provides additional insights into the operation and variability of RRAMs. This work suggests thermal engineering and characterization routes to optimize the efficiency and reliability of these devices.

Thermal Management in Neuromorphic Materials, Devices, and Networks

Machine learning has experienced unprecedented growth in recent years, often referred to as an "artificial intelligence revolution." Biological systems inspire the fundamental approach for this new computing paradigm: using neural networks to classify large amounts of data into sorting categories. Current machine-learning schemes implement simulated neurons and synapses on standard computers based on a von Neumann architecture. This approach is inefficient in energy consumption, and thermal management, motivating the search for hardware-based systems that imitate the brain. Here, the present state of thermal management of neuromorphic computing technology and the challenges and opportunities of the energy-efficient implementation of neuromorphic devices are considered. The main features of brain-inspired computing and quantum materials for implementing neuromorphic devices are briefly described, the brain criticality and resistive switching-based neuromorphic devices are discussed, the energy and electrical considerations for spiking-based computation are presented, the fundamental features of the brain's thermal regulation are addressed, the physical mechanisms for thermal management and thermoelectric control of materials and neuromorphic devices are analyzed, and challenges and new avenues for implementing energy-efficient computing are described.

Realizing the Accurate Measurements of Thermal Conductivity over a Wide Range by Scanning Thermal Microscopy Combined with Quantitative Prediction of Thermal Contact Resistance

Quantitative thermal performance measurements and thermal management at the micro-/nano scale are becoming increasingly important as the size of electronic components shrinks. Scanning thermal microscopy (SThM) is an emerging method with high spatial resolution that accurately reflects changes in local thermal signals based on a thermally sensitive probe. However, because of the unclear thermal resistance at the probe-sample interface, quantitative characterization of thermal conductivity for different kinds of materials still remains limited. In this paper, the heat transfer process considering the thermal contact resistance between the probe and sample surface is analyzed using finite element simulation and thermal resistance network model. On this basis, a mathematical empirical function is developed applicable to a variety of material systems, which depicts the relationship between the thermal conductivity of the sample and the probe temperature. The proposed model is verified by measuring ten materials with a wide thermal conductivity range, and then further validated by two materials with unknown thermal conductivity. In conclusion, this work provides the prospect of achieving quantitative characterization of thermal conductivity over a wide range and further enables the mapping of local thermal conductivity to microstructures or phases of materials.

Temperature Distribution in TaO x Resistive Switching Devices Assessed In Operando by Scanning Thermal Microscopy

Understanding the physical changes during electroformation and switching processes in transition-metal-oxide-based non-volatile memory devices is important for advancing this technology. Relatively few characteristics of these devices have been assessed in operando. In this work, we present scanning thermal microscopy measurements in vacuum on TaO _x -based memory devices electroformed in both positive and negative polarities and high- and low-resistance states. The observed surface temperature footprints of the filament showed higher peak temperatures and narrower temperature distributions when the top electrode served as the anode in the electroformation process. This is consistent with a model in which a hot spot is created by a gap in the conducting filament that forms closest to the anode. A similar behavior was seen on comparing the high-resistance state to the low-resistance state, with the low-resistance footprint showing a lower peak and a larger width, consistent with the gap disappearing when the device is switched from high resistance to low resistance.

Nanoscale temperature sensing of electronic devices with calibrated scanning thermal microscopy

Heat dissipation threatens the performance and lifetime of many electronic devices. As the size of devices shrinks to the nanoscale, we require spatially and thermally resolved thermometry to observe their fine thermal features. Scanning thermal microscopy (SThM) has proven to be a versatile measurement tool for characterizing the temperature at the surface of devices with nanoscale resolution. SThM can obtain qualitative thermal maps of a device using an operating principle based on a heat exchange process between a thermo-sensitive probe and the sample surface. However, the quantification of these thermal features is one of the most challenging parts of this technique. Developing reliable calibration approaches for SThM is therefore an essential aspect to accurately determine the temperature at the surface of a sample or device. In this work, we calibrate a thermo-resistive SThM probe using heater-thermometer metal lines with different widths (50 nm to 750 nm), which mimic variable probe-sample thermal exchange processes. The sensitivity of the SThM probe when scanning the metal lines is also evaluated under different probe and line temperatures. Our results reveal that the calibration factor depends on the probe measuring conditions and on the size of the surface heating features. This approach is validated by mapping the temperature profile of a phase change electronic device. Our analysis provides new insights on how to convert the thermo-resistive SThM probe signal to the scanned device temperature more accurately.

Thermal Characterization of Conductive Filaments in Unipolar Resistive Memories

A methodology to estimate the device temperature in resistive random access memories (RRAMs) is presented. Unipolar devices, which are known to be highly influenced by thermal effects in their resistive switching operation, are employed to develop the technique. A 3D RRAM simulator is used to fit experimental data and obtain the maximum and average temperatures of the conductive filaments (CFs) that are responsible for the switching behavior. It is found that the experimental CFs temperature corresponds to the maximum simulated temperatures obtained at the narrowest sections of the CFs. These temperature values can be used to improve compact models for circuit simulation purposes.

Nanoscale heat transport analysis by scanning thermal microscopy: from calibration to high-resolution measurements

Scanning thermal microscopy (SThM) is a powerful technique for thermal characterization. However, one of the most challenging aspects of thermal characterization is obtaining quantitative information on thermal conductivity with nanoscale lateral resolution. We used this technique with the cross-point calibration method to obtain the thermal contact resistance, R _c, and thermal exchange radius, b, using thermo-resistive Pd/Si₃N₄ probes. The cross-point curves correlate the dependence of R _c and b with the sample's thermal conductivity. We implemented a 3ω-SThM method in which reference samples with known thermal conductivity were used in the calibration and validation process to guarantee optimal working conditions. We achieved values of R _c = 0.94 × 10⁶ ± 0.02 K W^-1 and b = 2.41 × 10^-7 ± 0.02 m for samples with a low thermal conductivity (between 0.19 and 1.48 W m^-1 K^-1). These results show a large improvement in spatial resolution over previously reported data for the Wollaston probes (where b ∼ 2.8 μm). Furthermore, the contact resistance with the Pd/Si₃N₄ is ∼20× larger than reported for a Wollaston wire probe (with 0.45 × 10⁵ K W^-1). These thermal parameters were used to determine the unknown thermal conductivity of thermoelectric films of Ag₂Se, Ag_2-x Se, Cu₂Se (smooth vs. rough surface), and Bi₂Te₃, obtaining, in units of W m^-1 K^-1, the values of 0.63 ± 0.07, 0.69 ± 0.15, 0.79 ± 0.03, 0.82 ± 0.04, and 0.93 ± 0.12, respectively. To the best of our knowledge, this is the first time these microfabricated probes have been calibrated using the cross-point method to perform quantitative thermal analysis with nanoscale resolution. Moreover, this work shows high-resolution thermal images of the V _1ω and V _3ω signals, which can offer relevant information on the material's heat dissipation.

High Spatial Resolution Thermal Mapping of Volatile Switching in NbOx-Based Memristor Using In Situ Scanning Thermal Microscopy

Temperature mapping by in situ thermoreflectance thermal imaging (TRTI) or midwave infrared spectroscopy has played an important role in understanding the origins of threshold switching and the effect of insulator-metal transitions in oxide-based memrsitive devices. In this study, we use scanning thermal microscopy (SThM) as an alternative thermal mapping technique that offers high spatial resolution imaging (∼100 nm) and is independent of material. Specifically, SThM is used to map the temperature distribution in NbO_x-based cross-bar and nanovia devices with Pt top electrodes. The measurements on cross-bar devices reproduce the current redistribution and confinement processes previously observed by TRTI but without the need to coat the electrodes with a material of high thermo-reflectance coefficient (e.g., Au), while those on the nanovia devices highlight the spatial resolution of the technique. The measured temperature distributions are compared with those obtained from physics-based finite-element simulations and suggest that thermal boundary resistance plays an important role in heat transfer between the active device volume and the top electrode.