https://tenor-john.github.io/Academicpage/project/ProjectsHugo Blox Builder (https://hugoblox.com)en-usFri, 15 Mar 2024 00:00:00 +0000https://tenor-john.github.io/Academicpage/media/icon_hu7729264130191091259.pnghttps://tenor-john.github.io/Academicpage/project/https://tenor-john.github.io/Academicpage/project/pytorch/Fri, 15 Mar 2024 00:00:00 +0000https://tenor-john.github.io/Academicpage/project/pytorch/<p>利用密度泛函理论（DFT）计算研究电催化CO2还原反应的机理，旨在设计高效的催化剂。</p> <p>Using density functional theory (DFT) calculations to study the mechanism of electrocatalytic CO2 reduction reactions, aiming to design efficient catalysts.</p> <h2 id="项目概述--project-overview">项目概述 | Project Overview</h2> <p>本项目主要研究电催化CO2还原反应的机理，通过理论计算预测催化剂的活性和选择性。</p> <p>This project focuses on studying the mechanism of electrocatalytic CO2 reduction reactions and predicting catalyst activity and selectivity through theoretical calculations.</p> <h2 id="主要工作--main-work">主要工作 | Main Work</h2> <ul> <li>构建了多种催化剂表面模型</li> <li>计算了CO2还原的各种反应路径</li> <li>分析了催化剂结构与性能的关系</li> <li>预测了新型高效催化剂</li> </ul> <h2 id="技术方法--methods">技术方法 | Methods</h2> <ul> <li>密度泛函理论（DFT）计算</li> <li>VASP软件包</li> <li>反应路径分析</li> <li>电子结构分析</li> </ul> <h2 id="研究视频展示--research-video">研究视频展示 | Research Video</h2> <h3 id="计算过程演示">计算过程演示</h3> <div class="video-container" style="margin: 1rem 0;"> <video width="90%" height="auto" controls style="max-width: 100%; height: auto;" > <source src="https://tenor-john.github.io/Academicpage/videos/dft-calculation-demo.mp4" type="video/mp4"> <p>您的浏览器不支持视频播放。请 <a href="https://tenor-john.github.io/Academicpage/videos/dft-calculation-demo.mp4">下载视频</a> 观看。</p> </video> <p class="video-caption" style="text-align: center; font-style: italic; margin-top: 0.5rem;"> DFT计算过程演示 - CO2在催化剂表面的吸附和反应 </p> </div> <h3 id="结果可视化">结果可视化</h3> <div class="video-container" style="margin: 1rem 0;"> <video width="90%" height="auto" controls style="max-width: 100%; height: auto;" > <source src="https://tenor-john.github.io/Academicpage/videos/reaction-pathway.mp4" type="video/mp4"> <p>您的浏览器不支持视频播放。请 <a href="https://tenor-john.github.io/Academicpage/videos/reaction-pathway.mp4">下载视频</a> 观看。</p> </video> <p class="video-caption" style="text-align: center; font-style: italic; margin-top: 0.5rem;"> 反应路径动画展示 - CO2还原的各个步骤 </p> </div> <h2 id="实验验证--experimental-validation">实验验证 | Experimental Validation</h2> <div class="video-container" style="margin: 1rem 0;"> <video width="80%" height="auto" controls style="max-width: 100%; height: auto;" > <source src="https://tenor-john.github.io/Academicpage/videos/electrochemical-test.mp4" type="video/mp4"> <p>您的浏览器不支持视频播放。请 <a href="https://tenor-john.github.io/Academicpage/videos/electrochemical-test.mp4">下载视频</a> 观看。</p> </video> <p class="video-caption" style="text-align: center; font-style: italic; margin-top: 0.5rem;"> 电化学测试实验 - 线性扫描伏安法(LSV)测试 </p> </div>https://tenor-john.github.io/Academicpage/project/pandas/Sat, 20 Jan 2024 00:00:00 +0000https://tenor-john.github.io/Academicpage/project/pandas/<p>基于机器学习和高通量计算设计新型光催化水分解催化剂。</p> <p>Design of novel photocatalytic water splitting catalysts based on machine learning and high-throughput calculations.</p> <h2 id="项目目标--project-goals">项目目标 | Project Goals</h2> <p>开发高效稳定的光催化剂用于太阳能制氢，为清洁能源技术提供理论支撑。</p> <p>Develop efficient and stable photocatalysts for solar hydrogen production, providing theoretical support for clean energy technologies.</p> <h2 id="研究内容--research-content">研究内容 | Research Content</h2> <ul> <li>光催化剂带隙和能带位置优化</li> <li>载流子分离效率提升策略</li> <li>催化剂稳定性机理研究</li> <li>机器学习辅助材料筛选</li> </ul> <h2 id="研究方法--methods">研究方法 | Methods</h2> <ul> <li>第一性原理计算</li> <li>机器学习算法</li> <li>高通量材料筛选</li> <li>实验验证</li> </ul>https://tenor-john.github.io/Academicpage/project/scikit/Fri, 10 Nov 2023 00:00:00 +0000https://tenor-john.github.io/Academicpage/project/scikit/<p>开发基于纳米材料的高灵敏度电化学传感器用于环境监测。</p> <p>Development of highly sensitive electrochemical sensors based on nanomaterials for environmental monitoring.</p> <h2 id="项目背景--background">项目背景 | Background</h2> <p>随着环境污染问题日益严重，开发快速、准确的检测方法变得至关重要。</p> <p>With increasing environmental pollution, developing rapid and accurate detection methods has become crucial.</p> <h2 id="主要成果--main-achievements">主要成果 | Main Achievements</h2> <ul> <li>合成了多种新型纳米复合材料</li> <li>构建了高灵敏度电化学传感平台</li> <li>实现了多种污染物的同时检测</li> <li>开发了便携式检测设备原型</li> </ul> <h2 id="应用前景--applications">应用前景 | Applications</h2> <ul> <li>水质监测</li> <li>空气质量检测</li> <li>食品安全检测</li> <li>生物医学诊断</li> </ul>