We report our observation of the training effect on dc electrical properties in a nanochain of BiFeO3 as a result of large scale migration of defects under the combined influence of electric field and Joule heating. We show that an optimum number of cycles of electric field within the range zero to ~1.0 MV cm(-1) across a temperature range 80-300 K helps in reaching the stable state via a glass-transition-like process in the defect structure. Further treatment does not give rise to any substantial modification. We conclude that such a training effect is ubiquitous in pristine nanowires or chains of oxides and needs to be addressed for applications in nanoelectronic devices.
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http://dx.doi.org/10.1088/0957-4484/24/13/135705 | DOI Listing |
Vis Intell
December 2024
Department of Information Technology and Electrical Engineering, ETH Zurich, Sternwartstrasse 7, Zürich, Switzerland.
The LLaMA family, a collection of foundation language models ranging from 7B to 65B parameters, has become one of the most powerful open-source large language models (LLMs) and the popular LLM backbone of multi-modal large language models (MLLMs), widely used in computer vision and natural language understanding tasks. In particular, LLaMA3 models have recently been released and have achieved impressive performance in various domains with super-large scale pre-training on over 15T tokens of data. Given the wide application of low-bit quantization for LLMs in resource-constrained scenarios, we explore LLaMA3's capabilities when quantized to low bit-width.
View Article and Find Full Text PDFChemphyschem
January 2025
Changchun University of Technology, No. 3000, Beiyuanda Street, Gaoxinbei District, Changchun, Jilin, China, CHINA.
With the rapid advancement of information technology, the need to achieve ultra-high-density data storage has become a pressing necessity. This study synthesized three hyperbranched polyimides (HBPI-TAPP, HBPI-(Zn)TAPP, and HBPI-(Cu)TAPP) by polymerizing 5,10,15,20-tetrakis(4-aminophenyl)porphyrin (TAPP), which features a cavity for metal ion coordination, with 4,4'-(hexafluoroisopropylidene)diphthalic anhydride (6FDA), to systematically investigate the effect of metal ion species on storage performance. According to the results, memory devices based on HBPI-(Zn)TAPP exhibit volatile SRAM (static random-access memory) characteristics, whereas devices employing HBPI-TAPP and HBPI-(Cu)TAPP demonstrate non-volatile WORM (write-once, read-many) characteristics.
View Article and Find Full Text PDFAdv Mater
January 2025
Department of Physics, Pohang University of Science and Technology, 77, Cheongam-ro, Nam-gu, Pohang, 37673, Korea (the Republic of).
Janus materials, a novel class of materials with two faces of different chemical compositions and electronic polarities, offer significant potential for various applications with catalytic reactions, chemical sensing, and optical or electronic responses. A key aspect for such functionalities is face-dependent electronic bipolarity, which is usually limited by the chemical distinction of terminated surfaces and has not been exploited in the semiconducting regime. Here, it is showed that a Janus and Kagome van der Waals (vdW) material NbTeI has ferroelectric-like coherent stacking of the Janus layers and hosts strong electronic bipolar states in the semiconducting regime.
View Article and Find Full Text PDFSci Rep
January 2025
Institute of Atmospheric Physics, LAGEO, Chinese Academy of Sciences, Beijing, China.
Quickly identifying and classifying lightning waveforms is the foundation of lightning forecasting and early warning. In this paper, based on the electric field observation of the Beijing lightning location website of the Institute of Atmospheric Physics, Chinese Academy of Sciences, a recognition and classification method of pulse signal waveform based on Convolutional Neural Network(CNN) algorithm is designed and implemented. The CNN network model and its parameters were optimized from three aspects: dataset, model parameters, and network structure, achieving a recognition rate of over 90%.
View Article and Find Full Text PDFSci Rep
January 2025
Media Technology and Interaction Design, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, Lindstedtsv. 3-5, Stockholm, 100 44, Sweden.
Energy poverty affects 550,000 homes in the Netherlands yet policy interventions to alleviate this issue are rare. Therefore, we test two energy coaching interventions in Amsterdam: a static information group (n = 67) which received energy efficient products and one energy-use report, and a smart information group (n = 50), which also had a display providing real-time feedback on energy-use. Results across both groups, show a 75% success rate for alleviating energy poverty.
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