Jove
Visualize
お問い合わせ
JoVE
x logofacebook logolinkedin logoyoutube logo
JoVEについて
概要リーダーシップブログJoVEヘルプセンター
著者向け
出版プロセス編集委員会範囲と方針査読よくある質問投稿
図書館員向け
推薦の声購読アクセスリソース図書館諮問委員会よくある質問
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experimentsアーカイブ
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教員リソースセンター教員サイト
利用規約
プライバシーポリシー
ポリシー

関連する概念動画

Diffusion01:12

Diffusion

218.6K
Diffusion is the passive movement of substances down their concentration gradients—requiring no expenditure of cellular energy. Substances, such as molecules or ions, diffuse from an area of high concentration to an area of low concentration in the cytosol or across membranes. Eventually, the concentration will even out, with the substance moving randomly but causing no net change in concentration. Such a state is called dynamic equilibrium, which is essential for maintaining overall...
218.6K
Diffusion01:21

Diffusion

6.4K
Diffusion is a type of passive transport. In passive transport, a substance tends to move from an area of high concentration to an area of low concentration until the concentration is equal across the space. For example, take the diffusion of substances through the air. When someone opens a perfume bottle in a room filled with people, the perfume is at its highest concentration in the bottle and is at its lowest at the edges of the room. The perfume vapor will diffuse, or spread away, from the...
6.4K
Sampling Plans01:23

Sampling Plans

985
Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
985
Planning Nursing Care I01:21

Planning Nursing Care I

5.9K
The planning phase of the nursing process helps nurses set priorities, outline patient-centered goals and expected outcomes, and tailor nursing interventions to align with the aligned care plan. Through the planning phase, the nurse applies critical thinking skills to align and develop interventions according to the patient's needs. It provides continuity of care allowing patients to receive the maximum benefit from treatment. It serves as a pilot plan for allocating individual staff to a...
5.9K
Planning Nursing Care II01:29

Planning Nursing Care II

3.8K
A nursing care plan can present in two forms: informal and formal. Informal is a care plan for the individual use of the nurse and goals they wish to accomplish during their shift. Informal care plans are not included in the patient chart. A formal nursing care plan is a written or computerized guide that organizes patient care. It is further subdivided into two: standardized and individualized care plans. Standardized care plans are pre-populated care plans for specific patient populations,...
3.8K
Behavior of Gas Molecules: Molecular Diffusion, Mean Free Path, and Effusion03:48

Behavior of Gas Molecules: Molecular Diffusion, Mean Free Path, and Effusion

31.3K
Although gaseous molecules travel at tremendous speeds (hundreds of meters per second), they collide with other gaseous molecules and travel in many different directions before reaching the desired target. At room temperature, a gaseous molecule will experience billions of collisions per second. The mean free path is the average distance a molecule travels between collisions. The mean free path increases with decreasing pressure; in general, the mean free path for a gaseous molecule will be...
31.3K

こちらも読む

関連記事

共著者、ジャーナル、引用グラフによってこの研究に関連する記事。

並び替え
Same author

Machine learning potentials for modeling alloys across compositions.

Science advances·2026
Same author

Current Understandings and Future Opportunities Related to the Structure Direction in Zeolite Synthesis.

ACS applied materials & interfaces·2026
Same author

Lignin to adipic acid in a high-yield chemical and biological redox process.

Nature·2026
Same author

Aeroallergen Sensitization Status in West China from 2024 to 2025.

Journal of clinical medicine·2026
Same author

Changes in Epidemiological Characteristics in Children with <i>Mycoplasma pneumoniae</i> Seropositivity in Southwest China from 2022 to 2023.

Journal of clinical medicine·2026
Same author

Impaired default mode network connectivity and deviated dorsal-ventral attention networks in catamenial epilepsy.

Epilepsy & behavior : E&B·2026
Same journal

Gaining biological insights through supervised data visualization.

Nature computational science·2026
Same journal

The inequalities of GPU access.

Nature computational science·2026
Same journal

Social technologies need societal alignment.

Nature computational science·2026
Same journal

The Quantum Optimization Benchmarking Library.

Nature computational science·2026
Same journal

Setting benchmarks for practical quantum utility of combinatorial optimization.

Nature computational science·2026
Same journal

Evidence of scaling advantage on an NP-complete problem with enhanced quantum solvers.

Nature computational science·2026
関連記事をすべて見る

関連する実験動画

Updated: Feb 4, 2026

Synthesis and Functionalization of 3D Nano-graphene Materials: Graphene Aerogels and Graphene Macro Assemblies
10:23

Synthesis and Functionalization of 3D Nano-graphene Materials: Graphene Aerogels and Graphene Macro Assemblies

Published on: November 5, 2015

14.5K

DiffSyn: 材料合成計画のための生成的拡散アプローチ

Elton Pan1, Soonhyoung Kwon2, Sulin Liu1

  • 1Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.

Nature computational science
|February 2, 2026
PubMed
まとめ
この要約は機械生成です。

この研究では、文献データからゼオライト合成経路を予測する生成モデルであるDiffSynを紹介します。新しいUFI材料の作成を成功裏に導き、結晶性材料の発見を最適化します。

キーワード:
材料合成ゼオライト生成モデル拡散モデル結晶性材料計算化学

さらに関連する動画

Synthesis of Cyclic Polymers and Characterization of Their Diffusive Motion in the Melt State at the Single Molecule Level
06:55

Synthesis of Cyclic Polymers and Characterization of Their Diffusive Motion in the Melt State at the Single Molecule Level

Published on: September 26, 2016

8.5K
Radiation Planning Assistant - A Streamlined, Fully Automated Radiotherapy Treatment Planning System
08:25

Radiation Planning Assistant - A Streamlined, Fully Automated Radiotherapy Treatment Planning System

Published on: April 11, 2018

15.9K

関連する実験動画

Last Updated: Feb 4, 2026

Synthesis and Functionalization of 3D Nano-graphene Materials: Graphene Aerogels and Graphene Macro Assemblies
10:23

Synthesis and Functionalization of 3D Nano-graphene Materials: Graphene Aerogels and Graphene Macro Assemblies

Published on: November 5, 2015

14.5K
Synthesis of Cyclic Polymers and Characterization of Their Diffusive Motion in the Melt State at the Single Molecule Level
06:55

Synthesis of Cyclic Polymers and Characterization of Their Diffusive Motion in the Melt State at the Single Molecule Level

Published on: September 26, 2016

8.5K
Radiation Planning Assistant - A Streamlined, Fully Automated Radiotherapy Treatment Planning System
08:25

Radiation Planning Assistant - A Streamlined, Fully Automated Radiotherapy Treatment Planning System

Published on: April 11, 2018

15.9K

科学分野:

  • 材料科学
  • 化学工学
  • 計算化学

背景:

  • ゼオライトのような結晶性材料の合成は、複雑な構造-合成関係と広大な実験空間のために困難です。
  • 既存の方法では、高次元の合成ランドスケープをナビゲートし、最適な条件を効率的に予測することが困難です。

研究 の 目的:

  • ゼオライト合成経路を予測および最適化するための高度な計算モデル、DiffSynを開発すること。
  • 合成レシピの大規模データセットを活用して、生成的拡散モデルをトレーニングすること。
  • 新しい結晶性材料を発見および合成するモデルの能力を実証すること。

主な方法:

  • 50年間の文献から23,000以上のゼオライト合成レシピでトレーニングされた生成的拡散モデルであるDiffSynを開発しました。
  • 望ましいゼオライト構造と有機テンプレートに基づいてモデルを条件付けし、可能性のある合成経路を生成しました。
  • 結合エネルギー計算を通じて予測された合成経路を合理化するために、密度汎関数理論(DFT)を利用しました。

主要な成果:

  • DiffSynは、多峰性の構造-合成関係を効果的にモデル化することにより、最先端のパフォーマンスを達成しました。
  • 競合する相を区別し、最適な合成経路を提案することに成功しました。
  • DiffSyn生成経路を使用してUFI材料が合成され、高いSi/Al比19.0が得られ、熱安定性が向上していることを示しています。

結論:

  • DiffSynは、結晶性材料の発見と合成を加速するための強力な計算アプローチを提供します。
  • 望ましい構造とテンプレートに基づいて合成経路を予測するモデルの能力は、実験的な試行錯誤を大幅に削減します。
  • UFI材料の合成の成功は、DiffSynの予測精度と材料科学を進歩させる可能性を検証しました。