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1. An observable effect of spin inertia in slow magneto-dynamics: Increase of the switching error rates in nanoscale ferromagnets

   https://doi.org/10.1088/1361-648X/ac0cb4  

   Rahman, Rahnuma ; Bandyopadhyay, Supriyo ( June 2021 , Journal of Physics: Condensed Matter)

   null (Ed.)

   The Landau-Lifshitz-Gilbert (LLG) equation, used to model magneto-dynamics in ferromagnets, tacitly assumes that the angular momentum associated with spin precession can relax instantaneously when the real or effective magnetic field causing the precession is turned off. This neglect of “spin inertia” is unphysical and would violate energy conservation. Recently, the LLG equation was modified to account for inertia effects. The consensus, however, seems to be that such effects would be unimportant in slow magneto-dynamics that take place over time scales much longer that the relaxation time of the angular momentum, which is typically few fs to perhaps ~100 ps in ferromagnets. Here, we show that there is at least one very serious and observable effect of spin inertia even in slow magneto-dynamics. It involves the switching error probability associated with flipping the magnetization of a nanoscale ferromagnet with an external agent, such as a magnetic field. The switching may take ~ns to complete when the field strength is close to the threshold value for switching, which is much longer than the angular momentum relaxation time, and yet the effect of spin inertia is felt in the switching error probability. This is because the ultimate fate of a switching trajectory, i.e. whether it results in success or failure, is influenced by what happens in the first few ps of the switching action when nutational dynamics due to spin inertia holds sway. Spin inertia increases the error probability, which makes the switching more error-prone. This has vital technological significance because it relates to the reliability of magnetic logic and memory. 

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2. Hypothetical Efficiency of Electrical to Mechanical Energy Transfer during Individual Stochastic Molecular Switching Events

   https://doi.org/10.1021/acsnano.0c04082  

   Larson, Amanda M. ; Balema, Tedros A. ; Zahl, Percy ; Schilling, Alex C. ; Stacchiola, Dario J. ; Sykes, E. Charles ( September 2020 , ACS Nano)

   There are now many examples of single molecule rotors, motors, and switches in the literature that, when driven by photons, electrons, or chemical reactions, exhibit well-defined motions. As a step toward using these single molecule devices to perform useful functions, one must understand how they interact with their environment and quantify their ability to perform work on it. Using a single molecule rotary switch, we examine the transfer of electrical energy, delivered via electron tunneling, to mechanical motion and measure the forces the switch experiences with a noncontact q-plus atomic force microscope. Action spectra reveal that the molecular switch has two stable states and can be excited resonantly between them at a bias of 100 mV via a one-electron inelastic tunneling process which corresponds to an energy input of 16 zJ. While the electrically induced switching events are stochastic and no net work is done on the cantilever, by measuring the forces between the molecular switch and the AFM cantilever, we can derive the maximum hypothetical work the switch could perform during a single switching event, which is ∼55 meV, equal to 8.9 zJ, which translates to a hypothetical efficiency of ∼55% per individual inelastic tunneling electron-induced switching event. When considering the total electrical energy input, this drops to 1 × 10–7% due to elastic tunneling events that dominate the tunneling current. However, this approach constitutes a general method for quantifying and comparing the energy input and output of molecular-mechanical devices. 

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3. (Digital Presentation) Oxide Memristors Based on SiO 2 with Cu/Ag Alloy Metallization for Neuromorphic Computing

   https://doi.org/10.1149/MA2022-0215808mtgabs  

   Qin, Fei ; Song, Han Wook ; Qin, Fei ( October 2022 , ECS Meeting Abstracts)

   By mimicking biomimetic synaptic processes, the success of artificial intelligence (AI) has been astounding with various applications such as driving automation, big data analysis, and natural-language processing.[1-4] Due to a large quantity of data transmission between the separated memory unit and the logic unit, the classical computing system with von Neumann architecture consumes excessive energy and has a significant processing delay.[5] Furthermore, the speed difference between the two units also causes extra delay, which is referred to as the memory wall.[6, 7] To keep pace with the rapid growth of AI applications, enhanced hardware systems that particularly feature an energy-efficient and high-speed hardware system need to be secured. The novel neuromorphic computing system, an in-memory architecture with low power consumption, has been suggested as an alternative to the conventional system. Memristors with analog-type resistive switching behavior are a promising candidate for implementing the neuromorphic computing system since the devices can modulate the conductance with cycles that act as synaptic weights to process input signals and store information.[8, 9]

   The memristor has sparked tremendous interest due to its simple two-terminal structure, including top electrode (TE), bottom electrode (BE), and an intermediate resistive switching (RS) layer. Many oxide materials, including HfO₂, Ta₂O₅, and IGZO, have extensively been studied as an RS layer of memristors. Silicon dioxide (SiO₂) features 3D structural conformity with the conventional CMOS technology and high wafer-scale homogeneity, which has benefited modern microelectronic devices as dielectric and/or passivation layers. Therefore, the use of SiO₂as a memristor RS layer for neuromorphic computing is expected to be compatible with current Si technology with minimal processing and material-related complexities.

   In this work, we proposed SiO₂-based memristor and investigated switching behaviors metallized with different reduction potentials by applying pure Cu and Ag, and their alloys with varied ratios. Heavily doped p-type silicon was chosen as BE in order to exclude any effects of the BE ions on the memristor performance. We previously reported that the selection of TE is crucial for achieving a high memory window and stable switching performance. According to the study which compares the roles of Cu (switching stabilizer) and Ag (large switching window performer) TEs for oxide memristors, we have selected the TE materials and their alloys to engineer the SiO₂-based memristor characteristics. The Ag TE leads to a larger memory window of the SiO₂memristor, but the device shows relatively large variation and less reliability. On the other hand, the Cu TE device presents uniform gradual switching behavior which is in line with our previous report that Cu can be served as a stabilizer, but with small on/off ratio.[9] These distinct performances with Cu and Ag metallization leads us to utilize a Cu/Ag alloy as the TE. Various compositions of Cu/Ag were examined for the optimization of the memristor TEs. With a Cu/Ag alloying TE with optimized ratio, our SiO₂based memristor demonstrates uniform switching behavior and memory window for analog switching applications. Also, it shows ideal potentiation and depression synaptic behavior under the positive/negative spikes (pulse train).

   In conclusion, the SiO₂memristors with different metallization were established. To tune the property of RS layer, the sputtering conditions of RS were varied. To investigate the influence of TE selections on switching performance of memristor, we integrated Cu, Ag and Cu/Ag alloy as TEs and compared the switch characteristics. Our encouraging results clearly demonstrate that SiO₂with Cu/Ag is a promising memristor device with synaptic switching behavior in neuromorphic computing applications.

   Acknowledgement

   This work was supported by the U.S. National Science Foundation (NSF) Award No. ECCS-1931088. S.L. and H.W.S. acknowledge the support from the Improvement of Measurement Standards and Technology for Mechanical Metrology (Grant No. 22011044) by KRISS.

   References

   [1] Younget al.,IEEE Computational Intelligence Magazine,vol. 13, no. 3, pp. 55-75, 2018.

   [2] Hadsellet al.,Journal of Field Robotics,vol. 26, no. 2, pp. 120-144, 2009.

   [3] Najafabadiet al.,Journal of Big Data,vol. 2, no. 1, p. 1, 2015.

   [4] Zhaoet al.,Applied Physics Reviews,vol. 7, no. 1, 2020.

   [5] Zidanet al.,Nature Electronics,vol. 1, no. 1, pp. 22-29, 2018.

   [6] Wulfet al.,SIGARCH Comput. Archit. News,vol. 23, no. 1, pp. 20–24, 1995.

   [7] Wilkes,SIGARCH Comput. Archit. News,vol. 23, no. 4, pp. 4–6, 1995.

   [8] Ielminiet al.,Nature Electronics,vol. 1, no. 6, pp. 333-343, 2018.

   [9] Changet al.,Nano Letters,vol. 10, no. 4, pp. 1297-1301, 2010.

   [10] Qinet al., Physica Status Solidi (RRL) - Rapid Research Letters, pssr.202200075R1, In press, 2022.

    

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4. Random Linear Streaming Codes in the Finite Memory Length and Decoding Deadline Regime

   https://doi.org/10.1109/ISIT45174.2021.9518162  

   Su, Pin-Wen ; Huang, Yu-Chih ; Lin, Shih-Chun ; Wang, I-Hsiang ; Wang, Chih-Chun ( July 2021 , 2021 IEEE International Symposium on Information Theory (ISIT))

   Streaming codes take a string of source symbols as input and output a string of coded symbols in real time, which effectively eliminate the queueing delay and are regarded as a promising scheme for low latency communications. Aiming at quantifying the fundamental latency performance of random linear streaming codes (RLSCs) over i.i.d. symbol erasure channels, this work derives the exact error probability under, simultaneously, the finite memory length and finite decoding deadline constraints. The result is then used to examine the tradeoff among memory length (complexity), decoding deadline (delay), and error probability (reliability) of RLSCs for the first time in the literature. Two critical observations are made: (i) Too much memory can adversely impact the performance under a finite decoding deadline constraint, a surprising finding not captured by the traditional wisdom that large memory length monotonically improves the performance in the asymptotic regime; (ii) The end-to-end delay of the RLSC is roughly 50% of that of the MDS block code when under identical code rate and error probability requirements. This implies that switching from block codes to RLSCs not only eliminates the queueing delay (thus 50%) but also has little negative impact on the error probability. 

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5. Application of An Active Gate Driver for Paralleling Operation of Si IGBT and SiC MOSFET

   https://doi.org/10.1109/ECCE-Asia49820.2021.9479254  

   Wei, Yuqi ; Du, Xia ; Woldegiorgis, Dereje ; Mantooth, Alan ( May 2021 , IEEE 12th Energy Conversion Congress Exposition - Asia)

   Wide band gap (WBG) devices feature high switching frequency operation and low switching loss. They have been widely adopted in tremendous applications. Nevertheless, the manufacture cost for SiC MOSFET greater than that of the Si IGBT. To achieve a trade off between cost and efficiency, the hybrid switch, which includes the paralleling operation of Si IGBT and SiC MOSFET, is proposed. In this article, an active gate driver is used for the hybrid switch to optimize both the switching and thermal performances. The turn-on and turn-off delays between two individual switches are controlled to minimize the switching loss of traditional Si IGBT. In this way, a higher switching frequency operation can be achieved for the hybrid switch to improve the converter power density. On the other hand, the gate source voltages are adjusted to achieve an optimized thermal performance between two individual switches, which can improve the reliability of the hybrid switch. The proposed active gate driver for hybrid switch is validated with a 2 kW Boost converter. 

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