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関連する概念動画

Ionic Radii03:10

Ionic Radii

33.4K
Ionic radius is the measure used to describe the size of an ion. A cation always has fewer electrons and the same number of protons as the parent atom; it is smaller than the atom from which it is derived. For example, the covalent radius of an aluminum atom (1s22s22p63s23p1) is 118 pm, whereas the ionic radius of an Al3+ (1s22s22p6) is 68 pm. As electrons are removed from the outer valence shell, the remaining core electrons occupying smaller shells experience a greater effective nuclear...
33.4K
Ionic Bonds00:42

Ionic Bonds

129.6K
Overview
When atoms gain or lose electrons to achieve a more stable electron configuration they form ions. Ionic bonds are electrostatic attractions between ions with opposite charges. Ionic compounds are rigid and brittle when solid and may dissociate into their constituent ions in water. Covalent compounds, by contrast, remain intact unless a chemical reaction breaks them.
Opposing Charges Hold Ions Together in Ionic Compounds
Ionic bonds are reversible electrostatic interactions between ions...
129.6K
Molecular and Ionic Solids02:54

Molecular and Ionic Solids

20.0K
Crystalline solids are divided into four types: molecular, ionic, metallic, and covalent network based on the type of constituent units and their interparticle interactions.
Molecular Solids
Molecular crystalline solids, such as ice, sucrose (table sugar), and iodine, are solids that are composed of neutral molecules as their constituent units. These molecules are held together by weak intermolecular forces such as London dispersion forces, dipole-dipole interactions, or hydrogen bonds, which...
20.0K
Solubility of Ionic Compounds02:55

Solubility of Ionic Compounds

68.1K
Solubility is the measure of the maximum amount of solute that can be dissolved in a given quantity of solvent at a given temperature and pressure. Solubility is usually measured in molarity (M) or moles per liter (mol/L). A compound is termed soluble if it dissolves in water.
68.1K
Ionic Crystal Structures02:42

Ionic Crystal Structures

16.9K
Ionic crystals consist of two or more different kinds of ions that usually have different sizes. The packing of these ions into a crystal structure is more complex than the packing of metal atoms that are the same size.
Most monatomic ions behave as charged spheres, and their attraction for ions of opposite charge is the same in every direction. Consequently, stable structures for ionic compounds result (1) when ions of one charge are surrounded by as many ions as possible of the opposite...
16.9K
Ionic Compounds: Formulas and Nomenclature03:34

Ionic Compounds: Formulas and Nomenclature

86.4K
An element composed of atoms that readily lose electrons (a metal) can react with an element composed of atoms that readily gain electrons (a nonmetal) to produce ions through complete electron transfer. The compound formed by this transfer is stabilized by the electrostatic attractions (ionic bonds) between the oppositely charged ions.
86.4K

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Ambient Method for the Production of an Ionically Gated Carbon Nanotube Common Cathode in Tandem Organic Solar Cells
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Ambient Method for the Production of an Ionically Gated Carbon Nanotube Common Cathode in Tandem Organic Solar Cells

Published on: November 5, 2014

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スケーラブルニューロモルフィックコンピューティングのためのイオン浮動ゲートメモリ配列の並列プログラミング

Elliot J Fuller1, Scott T Keene2, Armantas Melianas2

  • 1Sandia National Laboratories, Livermore, CA, USA.

Science (New York, N.Y.)
|April 27, 2019
PubMed
まとめ
この要約は機械生成です。

研究者はニューロモルフィックコンピューティングのための新しいイオン浮動ゲートメモリ配列を開発しました. このシステムは効率的な平行重量アップデートと 低電流の読み取りを可能にし 人工知能のハードウェアを進歩させています

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Ambient Method for the Production of an Ionically Gated Carbon Nanotube Common Cathode in Tandem Organic Solar Cells
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Ambient Method for the Production of an Ionically Gated Carbon Nanotube Common Cathode in Tandem Organic Solar Cells

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Identifying Coronary Artery Calcification on Non-gated Computed Tomography Scans
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科学分野:

  • 材料科学
  • コンピュータ工学
  • 神経科学

背景:

  • 従来のコンピューティングは,特に人工ニューラルネットワークでは,効率の限界に直面しています.
  • ニューロモルフィックコンピューティングは,並列処理と特殊なメモリを通じて効率を改善することを目的としています.
  • 効率的な学習を達成するには,選択的で線形的な重量アップデートと低読み電流 (<10 nA) が必要です.

研究 の 目的:

  • 新しいイオン浮遊ゲートメモリ配列を導入し 効率的な神経形コンピューティングを行います
  • 人工ニューラルネットワークの重さの選択的および線形プログラミングを実証する.
  • 10ナノアンペア未満の電流でシナプス重量読み取りを達成する.

主な方法:

  • 導電ブリッジメモリ (CBM) と統合されたポリマーリドックストランジスタを使用した.
  • 選択的な重量アップデートのためのCBMブリッジングスリーフ電圧を克服することによって並列プログラミングを実行します.
  • 導電性ポリマーを絶縁剤で薄めることで低読電流が得られる.

主要な成果:

  • レドックストランジスタ配列の選択的および線形プログラミングを並行して実証した.
  • 10ナノアンペア未満の電流でシナプス重量読み取りを達成しました.
  • メモリ配列は高い耐久性 (>10億回) と高い周波数 (>1MHz) を示した.

結論:

  • 開発されたイオン浮遊ゲートメモリ配列は 効率的な神経形学習の重要な要件を満たしています
  • この技術は AI アプリケーションで従来のコンピューティング効率を 超越する道を示しています
  • このシステムは頑丈で高速な ニューロモルフィックハードウェアを 実現する見込みです