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    Multilevel HfO2-based RRAM devices for low-power neuromorphic networks
    (Melville, NY : AIP Publ., 2019) Milo, V.; Zambelli, C.; Olivo, P.
    Training and recognition with neural networks generally require high throughput, high energy efficiency, and scalable circuits to enable artificial intelligence tasks to be operated at the edge, i.e., in battery-powered portable devices and other limited-energy environments. In this scenario, scalable resistive memories have been proposed as artificial synapses thanks to their scalability, reconfigurability, and high-energy efficiency, and thanks to the ability to perform analog computation by physical laws in hardware. In this work, we study the material, device, and architecture aspects of resistive switching memory (RRAM) devices for implementing a 2-layer neural network for pattern recognition. First, various RRAM processes are screened in view of the device window, analog storage, and reliability. Then, synaptic weights are stored with 5-level precision in a 4 kbit array of RRAM devices to classify the Modified National Institute of Standards and Technology (MNIST) dataset. Finally, classification performance of a 2-layer neural network is tested before and after an annealing experiment by using experimental values of conductance stored into the array, and a simulation-based analysis of inference accuracy for arrays of increasing size is presented. Our work supports material-based development of RRAM synapses for novel neural networks with high accuracy and low-power consumption. © 2019 Author(s).
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    Carbon lock-in through capital stock inertia associated with weak near-term climate policies
    (Amsterdam [u.a.] : Elsevier Science, 2013) Bertram, Christoph; Johnson, Nils; Luderer, Gunnar; Riahi, Keywan; Isaac, Morna; Eom, Jiyong
    Stringent long-term climate targets necessitate a limit on cumulative emissions in this century for which sufficient policy signals are lacking. Using nine energy-economy models, we explore how policies pursued during the next two decades impact long-term transformation pathways towards stringent long-term climate targets. Less stringent near-term policies (i.e., those with larger emissions) consume more of the long-term cumulative emissions budget in the 2010–2030 period, which increases the likelihood of overshooting the budget and the urgency of reducing GHG emissions after 2030. Furthermore, the larger near-term GHG emissions associated with less stringent policies are generated primarily by additional coal-based electricity generation. Therefore, to be successful in meeting the long-term target despite near-term emissions reductions that are weaker than those implied by cost-optimal mitigation pathways, models must prematurely retire significant coal capacity while rapidly ramping up low-carbon technologies between 2030 and 2050 and remove large quantities of CO2 from the atmosphere in the latter half of the century. While increased energy efficiency lowers mitigation costs considerably, even with weak near-term policies, it does not substantially reduce the short-term reliance on coal electricity. However, increased energy efficiency does allow the energy system more flexibility in mitigating emissions and, thus, facilitates the post-2030 transition.
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    Three-Dimensional Cobalt Hydroxide Hollow Cube/Vertical Nanosheets with High Desalination Capacity and Long-Term Performance Stability in Capacitive Deionization
    ([Beijing] : China Association for Science and Technology, 2021) Xiong, Yuecheng; Yu, Fei; Arnold, Stefanie; Wang, Lei; Presser, Volker; Ren, Yifan; Ma, Jie
    Faradaic electrode materials have significantly improved the performance of membrane capacitive deionization, which offers an opportunity to produce freshwater from seawater or brackish water in an energy-efficient way. However, Faradaic materials hold the drawbacks of slow desalination rate due to the intrinsic low ion diffusion kinetics and inferior stability arising from the volume expansion during ion intercalation, impeding the engineering application of capacitive deionization. Herein, a pseudocapacitive material with hollow architecture was prepared via template-etching method, namely, cuboid cobalt hydroxide, with fast desalination rate (3.3 mg (NaCl)·g-1 (h-Co(OH)2)·min-1 at 100 mA·g-1) and outstanding stability (90% capacity retention after 100 cycles). The hollow structure enables swift ion transport inside the material and keeps the electrode intact by alleviating the stress induced from volume expansion during the ion capture process, which is corroborated well by in situ electrochemical dilatometry and finite element simulation. Additionally, benefiting from the elimination of unreacted bulk material and vertical cobalt hydroxide nanosheets on the exterior surface, the synthesized material provides a high desalination capacity ( mg (NaCl)·g-1 (h-Co(OH)2) at 30 mA·g-1). This work provides a new strategy, constructing microscale hollow faradic configuration, to further boost the desalination performance of Faradaic materials.