Interest in resistive random access memory (RRAM) has grown rapidly in recent years for realizing ultrahigh density data storage devices. However, sneak currents in these devices can result in misreading of the data, thus limiting the applicability of RRAM. Complementary resistive switching (CRS) memory consisting of two antiserial RRAMs can considerably reduce sneak currents; however, complicated device architectures and manufacturing processes still remain as challenges. Herein, an effective and simple approach for fabricating CRS memory devices using self-assembled block copolymer micelles is reported. Cu ions are selectively placed in the core of polystyrene-block-poly(2-vinylpyridine) spherical micelles, and a hexagonally packed micelle monolayer is prepared through spin-coating. The micelle monolayer can be a symmetrical resistive switching layer, because the micelles and Cu act as dielectric and active metals in memory devices, respectively. The locally enhanced electric field and Joule heating achieved by the structured Cu atoms inside the micelles promote metal ionization and ion migration in a controlled manner, thus allowing for position selectivity during resistive switching. The micelle-based memory device exhibits stable and reliable CRS behavior, with a nonoverlapping and narrow distribution of threshold voltages. Therefore, this approach is promising for fabricating CRS memory devices for high-performance and ultrahigh-density RRAM applications.
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http://dx.doi.org/10.1002/marc.202100686 | DOI Listing |
ACS Nano
January 2025
IBM Research Europe - Zurich, 8803 Rüschlikon, Switzerland.
Devices with a highly nonlinear resistance-voltage relationship are candidates for neuromorphic computing, which can be achieved by highly temperature dependent processes like ion migration. To explore the thermal properties of such devices, Scanning Thermal Microscopy (SThM) can be employed. However, due to the nonlinearity, the high resolution and quantitative method of AC-modulated SThM cannot readily be used.
View Article and Find Full Text PDFEndocrinol Diabetes Metab Case Rep
January 2025
Summary: A 17-year-old girl presented with recurrent attacks of acute pancreatitis, associated with severe hyperglycemia and hypertriglyceridemia, despite being on intensive insulin therapy for the last 10 years. She had severe acanthosis nigricans, generalized loss of subcutaneous fat and prominent veins over extremities. The serum levels of glucose and triglyceride did not reduce significantly, even with maximally tolerated doses of metformin (2 g), pioglitazone (45 mg) and fenofibrate (160 mg), not uncommonly seen in poor rural families in West Bengal, India.
View Article and Find Full Text PDFInt J Surg
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Department of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai, China.
Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal diseases. Although several chemotherapy regimens have been developed over the past decades, few targeted therapies have shown a significant improvement in overall survival, partly due to the identification of PDAC as a single disease.
Methods: Combining metabolomic analysis and immunohistochemistry staining with Oil Red O staining, analysis for the oxygen consumption rate and extracellular acidification rate, we stratified pancreatic cancer cells into two subtypes.
Molecular junctions (MJs) are celebrated nanoelectronic devices for mimicking conventional electronic functions, including rectifiers, sensors, wires, switches, transistors, negative differential resistance, and memory, following an understanding of charge transport mechanisms. However, capacitive nanoscale molecular junctions are rarely seen. The present work describes electrochemically (E-Chem) grown covalently attached molecular thin films of 10, 14.
View Article and Find Full Text PDFRecent Pat Nanotechnol
January 2025
Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence, University of Groningen, Nijenborgh 9, 9747 AG Groningen, The Netherlands.
The increase in computational power demand led by the development of Artificial Intelligence is rapidly becoming unsustainable. New paradigms of computation, which potentially differ from digital computation, together with novel hardware architecture and devices, are anticipated to reduce the exorbitant energy demand for data-processing tasks. Memristive systems with resistive switching behavior are under intense research, given their prominent role in the fabrication of memory devices that promise the desired hardware revolution in our intensive data-driven era.
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