搜尋
首頁科技週邊人工智慧比原始材料強8倍,清華、武漢理工團隊用AI篩選高熵電介質材料

比原始材料強8倍,清華、武漢理工團隊用AI篩選高熵電介質材料

Editor | Radish skin dielectric materials can store and release charges and are widely used in capacitors, electronics and power systems. Due to their extremely high power density and fast response characteristics, they are used in fields such as hybrid electric vehicles, portable electronic devices and pulse power systems, but their energy density still needs to be further improved. High-entropy strategies have become an effective method to improve energy storage performance. However, discovering new high-entropy systems in high-dimensional composition spaces is a huge challenge for traditional trial-and-error experiments. Based on phase field simulations and limited experimental data, research teams from Wuhan University of Technology, Tsinghua University, and Pennsylvania State University proposed a generative learning method to accelerate the discovery of high-level learning in an infinite exploration space of more than 10^11combinations. Entropic dielectric materials (HED). This work provides an effective and innovative way to design high-entropy dielectric materials, significantly reducing the experimental cycle. The research was titled "Generative learning facilitated discovery of high-entropyceramic dielectrics for capacitive energy storage" and was published in "Nature Communications" on June 10, 2024. Dielectric materials can store and release charges and are the core

component in capacitors. They are widely used in hybrid electric vehicles, portable electronic devices, and pulsed power systems due to their high power density and fast response characteristics. Additionally, dielectric materials are critical in modern electronic and power systems, supporting the 比原始材料強8倍,清華、武漢理工團隊用AI篩選高熵電介質材料miniaturization

and high-efficiency operation of devices. However, traditional dielectric materials have limitations in energy density and thermal stability. The multi-entropy strategy can significantly improve these properties by introducing a variety of elements. Illustration: Phase field simulation of the impact of configuration entropy (Sconfig) on ​​energy storage performance. (Source: paper) High-entropy ceramics improve energy storage performance by forming diverse polarization structures with different valence states, ionic radii, and electronegativities, improving polarization response and breakdown strength. Currently, traditional experimental methods are inefficient and costly in discovering new high-entropy systems. To address these challenges, research teams from Tsinghua University, Wuhan University of Technology, and Pennsylvania State University built a generative learning-based framework based on small experimental data to accelerate the discovery of high energy density HED

. 比原始材料強8倍,清華、武漢理工團隊用AI篩選高熵電介質材料

Illustration: Overview of the generative learning framework for high-entropy design. (Source: paper) In order to clarify the influence of configurational entropy on polarization response, the researchers performed phase field simulations to calculate the polarization-electric field (P-E) loop and corresponding energy density of HEDs with different entropy values. The results show that as the entropy value increases, the polarization region becomes more neutral and the energy density increases significantly. As an experimental example, the team selected Bi(Mg0.5Ti0.5)O3 (BMT) as the original matrix and designed the HED by simultaneously doping its A-site and B-site with multiple elements. Using 77 sets of experimental results as initial data, the researchers established a generative learning model based on encoding-decoding architecture, and combined data reconstruction and artificial neural network (ANN) to find potential optimal high-entropy combinations. Illustration: phase

structure比原始材料強8倍,清華、武漢理工團隊用AI篩選高熵電介質材料 and electrical property analysis. (Source: paper) Then perform probability sampling on the existing small sample data, retain two decimal places for the element content of positions A and B, and set the sum of each position to 1 to construct a possibility of close to 10^11 combinations.

space, looking for the optimalcombination that satisfies the high entropy criterion. Then, the top five combinations with predicted results were screened from more than 2,000 candidate materials, and five sets of targeted experiments were conducted to verify their potential in energy storage performance.

比原始材料強8倍,清華、武漢理工團隊用AI篩選高熵電介質材料圖示:儲能效能和循環穩定性。 (資料來源:論文)實驗結果顯示,所製備的高熵陶瓷電介質薄膜在能量密度和擊穿強度方面均顯著優於傳統材料,特別是C-3薄膜在5104 kV/cm的電場下能量密度達到156 J/cm^3,是原始BMT(~18 J/cm^3)薄膜的八倍。此外,研究也探討了不同退火溫度對高熵薄膜性能的影響,發現適當的退火溫度能進一步提升材料的儲能特性。總而言之,高熵薄膜不僅具有優異的疲勞性能以及溫度和頻率穩定性,而且在儲能電容器中也顯示出廣泛應用的巨大潛力。基於機器學習驅動的模式,團隊利用非常稀疏的實驗數據有效地找到具有高儲能性能的所需高熵複合材料。該方法還使研究人員顯著縮短了整體實驗週期,並為設計具有複雜組件的材料系統開闢了新的途徑論文連結:https://www.nature.com/articles/s41467-024-49170-8

以上是比原始材料強8倍,清華、武漢理工團隊用AI篩選高熵電介質材料的詳細內容。更多資訊請關注PHP中文網其他相關文章!

陳述
本文內容由網友自願投稿,版權歸原作者所有。本站不承擔相應的法律責任。如發現涉嫌抄襲或侵權的內容,請聯絡admin@php.cn
微軟工作趨勢指數2025顯示工作場所容量應變微軟工作趨勢指數2025顯示工作場所容量應變Apr 24, 2025 am 11:19 AM

由於AI的快速整合而加劇了工作場所的迅速危機危機,要求戰略轉變以外的增量調整。 WTI的調查結果強調了這一點:68%的員工在工作量上掙扎,導致BUR

AI可以理解嗎?中國房間的論點說不,但是對嗎?AI可以理解嗎?中國房間的論點說不,但是對嗎?Apr 24, 2025 am 11:18 AM

約翰·塞爾(John Searle)的中國房間論點:對AI理解的挑戰 Searle的思想實驗直接質疑人工智能是否可以真正理解語言或具有真正意識。 想像一個人,對下巴一無所知

中國的'智能” AI助手回應微軟召回的隱私缺陷中國的'智能” AI助手回應微軟召回的隱私缺陷Apr 24, 2025 am 11:17 AM

與西方同行相比,中國的科技巨頭在AI開發方面的課程不同。 他們不專注於技術基準和API集成,而是優先考慮“屏幕感知” AI助手 - AI T

Docker將熟悉的容器工作流程帶到AI型號和MCP工具Docker將熟悉的容器工作流程帶到AI型號和MCP工具Apr 24, 2025 am 11:16 AM

MCP:賦能AI系統訪問外部工具 模型上下文協議(MCP)讓AI應用能夠通過標準化接口與外部工具和數據源交互。由Anthropic開發並得到主要AI提供商的支持,MCP允許語言模型和智能體發現可用工具並使用合適的參數調用它們。然而,實施MCP服務器存在一些挑戰,包括環境衝突、安全漏洞以及跨平台行為不一致。 Forbes文章《Anthropic的模型上下文協議是AI智能體發展的一大步》作者:Janakiram MSVDocker通過容器化解決了這些問題。基於Docker Hub基礎設施構建的Doc

使用6種AI街頭智能策略來建立一家十億美元的創業使用6種AI街頭智能策略來建立一家十億美元的創業Apr 24, 2025 am 11:15 AM

有遠見的企業家採用的六種策略,他們利用尖端技術和精明的商業敏銳度來創造高利潤的可擴展公司,同時保持控制。本指南是針對有抱負的企業家的,旨在建立一個

Google照片更新解鎖了您所有圖片的驚人Ultra HDRGoogle照片更新解鎖了您所有圖片的驚人Ultra HDRApr 24, 2025 am 11:14 AM

Google Photos的新型Ultra HDR工具:改變圖像增強的遊戲規則 Google Photos推出了一個功能強大的Ultra HDR轉換工具,將標準照片轉換為充滿活力的高動態範圍圖像。這種增強功能受益於攝影師

Descope建立AI代理集成的身份驗證框架Descope建立AI代理集成的身份驗證框架Apr 24, 2025 am 11:13 AM

技術架構解決了新興的身份驗證挑戰 代理身份集線器解決了許多組織僅在開始AI代理實施後發現的問題,即傳統身份驗證方法不是為機器設計的

Google Cloud Next 2025以及現代工作的未來Google Cloud Next 2025以及現代工作的未來Apr 24, 2025 am 11:12 AM

(注意:Google是我公司的諮詢客戶,Moor Insights&Strateging。) AI:從實驗到企業基金會 Google Cloud Next 2025展示了AI從實驗功能到企業技術的核心組成部分的演變,

See all articles

熱AI工具

Undresser.AI Undress

Undresser.AI Undress

人工智慧驅動的應用程序,用於創建逼真的裸體照片

AI Clothes Remover

AI Clothes Remover

用於從照片中去除衣服的線上人工智慧工具。

Undress AI Tool

Undress AI Tool

免費脫衣圖片

Clothoff.io

Clothoff.io

AI脫衣器

Video Face Swap

Video Face Swap

使用我們完全免費的人工智慧換臉工具,輕鬆在任何影片中換臉!

熱工具

ZendStudio 13.5.1 Mac

ZendStudio 13.5.1 Mac

強大的PHP整合開發環境

SublimeText3 英文版

SublimeText3 英文版

推薦:為Win版本,支援程式碼提示!

記事本++7.3.1

記事本++7.3.1

好用且免費的程式碼編輯器

SAP NetWeaver Server Adapter for Eclipse

SAP NetWeaver Server Adapter for Eclipse

將Eclipse與SAP NetWeaver應用伺服器整合。

WebStorm Mac版

WebStorm Mac版

好用的JavaScript開發工具