Acquisition of a Nanomechanical Testing Platform to Establish a User Center for Nanomecanical Characterization Materials
收购纳米力学测试平台,建立纳米力学表征材料用户中心
基本信息
- 批准号:0420859
- 负责人:
- 金额:$ 29.39万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2004
- 资助国家:美国
- 起止时间:2004-07-15 至 2007-06-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The Nanomechanical Testing Platform addresses the fundamental understanding of the properties of materials at the nanometer length scale. The system includes the Hysitron TriboIndenter as a stand-alone, nanomechanical test instrument that utilizes a fully integrated indenter head and atomic force microscope (AFM) combination. Other accessories integrated with the Triboindenter to support many different nanomechanical characterization techniques for a variety of applications include nanoDMA and modulus mapping module for investigating time dependent properties of materials using a dynamic testing technique; TriboAE module to monitor fracture, delamination and phase transformations that occur under nanoscale contacts using the acoustic waves emitted during the phenomena; Feedback Control Module will allow to operate in closed loop load or displacement control for testing during creep or stress relaxation; Thermal Control Heating/Cooling Stage and a Vacuum Chuck. Nano-mechanical testing in conjunction with nano-scale surface imaging is a powerful way to analyze extremely small volumes of materials or surfaces with a very high resolution. The University of Missouri Columbia has identified Nano-science and Nano-devices as a major research thrust area. Intellectual merit: With these instruments researchers will be able to perform quasi-static testing to study elastic, plastic, and fracture response of both hard and very soft materials during indentation at the nanometer length scale. They will be able to image and quantitatively study surface phenomena such as surface wear by rubbing and scratching. In addition researchers can study time dependent properties of materials over a range of temperatures. It is envisaged that the instrumentation will be used for a wide range of current and future research in areas such as property gradients across composite material interphases and interfaces in welded and joined materials, surface topography in MEMS devices, adhesion and frictional characteristics of electronic devices of micrometer length scale, surface characterization of biological sensors, interfacial properties across layered synthetic and biological materials, mechanical property variations within and across phases in ceramic-polymer composites and investigation of mechanical properties of self-assembled nanostructured materials. Broader Impact: A significant number of graduate and undergraduate students will be exposed to the usage and application of state-of-the-art instrumentation through classroom instruction and research. This experience should sharpen their understanding of materials behavior. This instrumentation will foster interdisciplinary research. The whole range of proposed instruments will form the proposed Nanomechanical Characterization User Center. It should be emphasized that the user facility will be open to faculty and students of all colleges and the medical school on MU campus. The MU campus has made vigorous efforts to recruit students from regional college programs, including those with predominantly Black and Hispanic enrollment. Our group has established collaborative program with Lincoln University (HBCU). The MU is also committed to the recruitment and retention of minority and female students in Science and Engineering.
纳米力学测试平台解决了在纳米长度尺度上对材料性能的基本理解。该系统包括Hysitron TriboIndenter作为一个独立的,纳米机械测试仪器,利用完全集成的压头和原子力显微镜(AFM)的组合。与Triboindenter集成的其他附件支持各种应用的许多不同的纳米机械表征技术,包括nanoDMA和模量映射模块,用于使用动态测试技术研究材料的时间依赖特性; TriboAE模块,用于使用现象期间发出的声波监测纳米级接触下发生的断裂,分层和相变;反馈控制模块将允许在蠕变或应力松弛期间在闭环负载或位移控制下运行,以进行测试;热控制加热/冷却阶段和真空卡盘。结合纳米尺度表面成像的纳米力学测试是以极高分辨率分析极小体积材料或表面的强大方法。 密苏里州哥伦比亚大学已确定纳米科学和纳米器件作为一个主要的研究推力领域。智力优点:有了这些仪器,研究人员将能够进行准静态测试,研究弹性,塑性和断裂响应的硬材料和非常软的材料在压痕在纳米长度尺度。他们将能够成像和定量研究表面现象,如摩擦和划痕引起的表面磨损。此外,研究人员可以研究材料在一定温度范围内的时间依赖性。据设想,该仪器将用于广泛的当前和未来的研究领域,如跨复合材料界面和焊接和连接材料界面的性能梯度,MEMS器件的表面形貌,微米长度尺度的电子器件的粘附和摩擦特性,生物传感器的表面表征,分层合成和生物材料的界面性能,陶瓷-聚合物复合材料中相内和相间的力学性能变化以及自组装纳米结构材料的力学性能研究。更广泛的影响:大量的研究生和本科生将通过课堂教学和研究接触到最先进的仪器的使用和应用。这一经验应该提高他们对材料行为的理解。这种仪器将促进跨学科研究。整个拟议的仪器范围将形成拟议的纳米机械表征用户中心。应该强调的是,用户设施将向所有学院和医学院的师生开放。MU校园积极努力从区域大学项目中招收学生,包括那些以黑人和西班牙裔为主的学生。本集团与林肯大学(HBCU)建立了合作项目。MU还致力于招聘和保留少数民族和女性学生在科学和工程。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
Sanjeev Khanna其他文献
Maximum Bipartite Matching in ?2+?(1) Time via a Combinatorial Algorithm
通过组合算法在 ?2+?(1) 时间内实现最大二分匹配
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Julia Chuzhoy;Sanjeev Khanna - 通讯作者:
Sanjeev Khanna
Palette Sparsification Beyond (∆ + 1) Vertex 1 Coloring 2
调色板稀疏化超出 (Δ + 1) 顶点 1 着色 2
- DOI:
- 发表时间:
2020 - 期刊:
- 影响因子:0
- 作者:
Noga Alon;Sepehr Assadi;Suman Bera;Amit Chakrabarti;Prantar Ghosh;Guru Guruganesh;David Harris;Sanjeev Khanna;Hsin - 通讯作者:
Hsin
Theory of Computing
计算理论
- DOI:
10.4086/toc - 发表时间:
2013 - 期刊:
- 影响因子:0
- 作者:
Alexandr Andoni;Nikhil Bansal;P. Beame;Giuseppe Italiano;Sanjeev Khanna;Ryan O’Donnell;T. Pitassi;T. Rabin;Tim Roughgarden;Clifford Stein;Rocco Servedio;Amir Abboud;Nima Anari;Ibm Srinivasan Arunachalam;T. J. Watson;Research Center;Petra Berenbrink;Aaron Bernstein;Aditya Bhaskara;Sayan Bhattacharya;Eric Blais;H. Bodlaender;Adam Bouland;Anne Broadbent;Mark Bun;Timothy Chan;Arkadev Chattopadhyay;Xue Chen;Gil Cohen;Dana Dachman;Anindya De;Shahar Dobzhinski;Zhiyi Huang;Ken;Robin Kothari;Marvin Künnemann;Tu Kaiserslautern;Rasmus Kyng;E. Zurich;Sophie Laplante;D. Lokshtanov;S. Mahabadi;Nicole Megow;Ankur Moitra;Technion Shay Moran;Google Research;Christopher Musco;Prasad Raghavendra;Alex Russell;Laura Sanità;Alex Slivkins;David Steurer;Epfl Ola Svensson;Chaitanya Swamy;Madhur Tulsiani;Christos Tzamos;Andreas Wiese;Mary Wootters;Huacheng Yu;Aaron Potechin;Aaron Sidford;Aarushi Goel;Aayush Jain;Abhiram Natarajan;Abhishek Shetty;Adam Karczmarz;Adam O’Neill;Aditi Dudeja;Aditi Laddha;Aditya Krishnan;Adrian Vladu Afrouz;J. Ameli;Ainesh Bakshi;Akihito Soeda;Akshay Krishnamurthy;Albert Cheu;A. Grilo;Alex Wein;Alexander Belov;Alexander Block;Alexander Golovnev;Alexander Poremba;Alexander Shen;Alexander Skopalik;Alexandra Henzinger;Alexandros Hollender;Ali Parviz;Alkis Kalavasis;Allen Liu;Aloni Cohen;Amartya Shankha;Biswas Amey;Bhangale Amin;Coja;Yehudayoff Amir;Zandieh Amit;Daniely Amit;Kumar Amnon;Ta;Beimel Anand;Louis Anand Natarajan;Anders Claesson;André Chailloux;André Nusser;Andrea Coladangelo;Andrea Lincoln;Andreas Björklund;Andreas Maggiori;A. Krokhin;A. Romashchenko;Andrej Risteski;Anirban Chowdhury;Anirudh Krishna;A. Mukherjee;Ankit Garg;Anna Karlin;Anthony Leverrier;Antonio Blanca;A. Antoniadis;Anupam Gupta;Anupam Prakash;A. Singh;Aravindan Vijayaraghavan;Argyrios Deligkas;Ariel Kulik;Ariel Schvartzman;Ariel Shaulker;A. Cornelissen;Arka Rai;Choudhuri Arkady;Yerukhimovich Arnab;Bhattacharyya Arthur Mehta;Artur Czumaj;A. Backurs;A. Jambulapati;Ashley Montanaro;A. Sah;A. Mantri;Aviad Rubinstein;Avishay Tal;Badih Ghazi;Bartek Blaszczyszyn;Benjamin Moseley;Benny Pinkas;Bento Natura;Bernhard Haeupler;Bill Fefferman;B. Mance;Binghui Peng;Bingkai Lin;B. Sinaimeri;Bo Waggoner;Bodo Manthey;Bohdan Kivva;Brendan Lucier Bundit;Laekhanukit Burak;Sahinoglu Cameron;Seth Chaodong Zheng;Charles Carlson;Chen;Chenghao Guo;Chenglin Fan;Chenwei Wu;Chethan Kamath;Chi Jin;J. Thaler;Jyun;Kaave Hosseini;Kaito Fujii;Kamesh Munagala;Kangning Wang;Kanstantsin Pashkovich;Karl Bringmann Karol;Wegrzycki Karteek;Sreenivasaiah Karthik;Chandrasekaran Karthik;Sankararaman Karthik;C. S. K. Green;Larsen Kasturi;Varadarajan Keita;Xagawa Kent Quanrud;Kevin Schewior;Kevin Tian;Kilian Risse;Kirankumar Shiragur;K. Pruhs;K. Efremenko;Konstantin Makarychev;Konstantin Zabarnyi;Krišj¯anis Pr¯usis;Kuan Cheng;Kuikui Liu;Kunal Marwaha;Lars Rohwedder László;Kozma László;A. Végh;L'eo Colisson;Leo de Castro;Leonid Barenboim Letong;Li;Li;L. Roditty;Lieven De;Lathauwer Lijie;Chen Lior;Eldar Lior;Rotem Luca Zanetti;Luisa Sinisclachi;Luke Postle;Luowen Qian;Lydia Zakynthinou;Mahbod Majid;Makrand Sinha;Malin Rau Manas;Jyoti Kashyop;Manolis Zampetakis;Maoyuan Song;Marc Roth;Marc Vinyals;Marcin Bieńkowski;Marcin Pilipczuk;Marco Molinaro;Marcus Michelen;Mark de Berg;M. Jerrum;Mark Sellke;Mark Zhandry;Markus Bläser;Markus Lohrey;Marshall Ball;Marthe Bonamy;Martin Fürer;Martin Hoefer;M. Kokainis;Masahiro Hachimori;Matteo Castiglioni;Matthias Englert;Matti Karppa;Max Hahn;Max Hopkins;Maximilian Probst;Gutenberg Mayank Goswami;Mehtaab Sawhney;Meike Hatzel;Meng He;Mengxiao Zhang;Meni Sadigurski;M. Parter;M. Dinitz;Michael Elkin;Michael Kapralov;Michael Kearns;James R. Lee;Sudatta Bhattacharya;Michal Koucký;Hadley Black;Deeparnab Chakrabarty;C. Seshadhri;Mahsa Derakhshan;Naveen Durvasula;Nika Haghtalab;Peter Kiss;Thatchaphol Saranurak;Soheil Behnezhad;M. Roghani;Hung Le;Shay Solomon;Václav Rozhon;Anders Martinsson;Christoph Grunau;G. Z. —. Eth;Zurich;Switzerland;Morris Yau — Massachusetts;Noah Golowich;Dhruv Rohatgi — Massachusetts;Qinghua Liu;Praneeth Netrapalli;Csaba Szepesvári;Debarati Das;Jacob Gilbert;Mohammadtaghi Hajiaghayi;Tomasz Kociumaka;B. Saha;K. Bringmann;Nick Fischer — Weizmann;Ce Jin;Yinzhan Xu — Massachusetts;Virginia Vassilevska Williams;Yinzhan Xu;Josh Alman;Kevin Rao;Hamed Hatami;—. XiangMeng;McGill University;Edith Cohen;Xin Lyu;Tamás Jelani Nelson;Uri Stemmer — Google;Research;Daniel Alabi;Pravesh K. Kothari;Pranay Tankala;Prayaag Venkat;Fred Zhang;Samuel B. Hopkins;Gautam Kamath;Shyam Narayanan — Massachusetts;Marco Gaboardi;R. Impagliazzo;Rex Lei;Satchit Sivakumar;Jessica Sorrell;T. Korhonen;Marco Bressan;Matthias Lanzinger;Huck Bennett;Mahdi Cheraghchi;V. Guruswami;João Ribeiro;Jan Dreier;Nikolas Mählmann;Sebastian Siebertz — TU Wien;The Randomized k ;Conjecture Is;False;Sébastien Bubeck;Christian Coester;Yuval Rabani — Microsoft;Wei;Ethan Mook;Daniel Wichs;Joshua Brakensiek;Sai Sandeep — Stanford;University;Lorenzo Ciardo;Stanislav Živný;Amey Bhangale;Subhash Khot;Dor Minzer;David Ellis;Guy Kindler;Noam Lifshitz;Ronen Eldan;Dan Mikulincer;George Christodoulou;E. Koutsoupias;Annamária Kovács;José Correa;Andrés Cristi;Xi Chen;Matheus Venturyne;Xavier Ferreira;David C. Parkes;Yang Cai;Jinzhao Wu;Zhengyang Liu;Zeyu Ren;Zihe Wang;Ravishankar Krishnaswamy;Shi Li;Varun Suriyanarayana - 通讯作者:
Varun Suriyanarayana
Approximation algorithms for data placement on parallel disks
并行磁盘上数据放置的近似算法
- DOI:
10.1145/1597036.1597037 - 发表时间:
2009 - 期刊:
- 影响因子:0
- 作者:
L. Golubchik;Sanjeev Khanna;Samir Khuller;R. Thurimella;An Zhu - 通讯作者:
An Zhu
A greedy approximation algorithm for minimum-gap scheduling
- DOI:
10.1007/s10951-016-0492-y - 发表时间:
2016-07-27 - 期刊:
- 影响因子:1.800
- 作者:
Marek Chrobak;Uriel Feige;Mohammad Taghi Hajiaghayi;Sanjeev Khanna;Fei Li;Seffi Naor - 通讯作者:
Seffi Naor
Sanjeev Khanna的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('Sanjeev Khanna', 18)}}的其他基金
Collaborative Research: AF: Medium: Fast Combinatorial Algorithms for (Dynamic) Matchings and Shortest Paths
合作研究:AF:中:(动态)匹配和最短路径的快速组合算法
- 批准号:
2402284 - 财政年份:2024
- 资助金额:
$ 29.39万 - 项目类别:
Continuing Grant
AF: Small: Sublinear Algorithms for Flows, Matchings, and Routing Problems
AF:小:流、匹配和路由问题的次线性算法
- 批准号:
2008305 - 财政年份:2020
- 资助金额:
$ 29.39万 - 项目类别:
Standard Grant
AF: Small: Sublinear Algorithms for Graph Optimization Problems
AF:小:图优化问题的次线性算法
- 批准号:
1617851 - 财政年份:2016
- 资助金额:
$ 29.39万 - 项目类别:
Standard Grant
AF: EAGER: Small Space Algorithms and Representations for Graph Optimization Problems
AF:EAGER:图优化问题的小空间算法和表示
- 批准号:
1552909 - 财政年份:2015
- 资助金额:
$ 29.39万 - 项目类别:
Standard Grant
AF: Small: Cut, Flow, and Matching Problems in Graphs
AF:小:图中的切割、流动和匹配问题
- 批准号:
1116961 - 财政年份:2011
- 资助金额:
$ 29.39万 - 项目类别:
Standard Grant
III: Medium: Collaborative Research: Optimization with Sparse Priors--Algorithms, Indices, and Economic Incentives
III:媒介:协作研究:稀疏先验优化——算法、指数和经济激励
- 批准号:
0904314 - 财政年份:2009
- 资助金额:
$ 29.39万 - 项目类别:
Continuing Grant
Effectiveness of problem based learning in a materials science course in the engineering curriculum
基于问题的学习在工程课程材料科学课程中的有效性
- 批准号:
0836914 - 财政年份:2009
- 资助金额:
$ 29.39万 - 项目类别:
Standard Grant
Collaborative Research: CT-T: DoS Prevention in Shared Channels
合作研究:CT-T:共享通道中的 DoS 预防
- 批准号:
0524269 - 财政年份:2005
- 资助金额:
$ 29.39万 - 项目类别:
Standard Grant
Development and Manufacturing of Highly Damage Resistant Fiber Glass Reinforced Window Panels for Buildings in Hurricane Prone Areas
为飓风多发地区的建筑物开发和制造高抗损伤玻璃纤维增强窗板
- 批准号:
0196428 - 财政年份:2001
- 资助金额:
$ 29.39万 - 项目类别:
Continuing Grant
相似海外基金
In-situ nanomechanical testing for materials under extreme environments
极端环境下材料的原位纳米力学测试
- 批准号:
LE240100049 - 财政年份:2024
- 资助金额:
$ 29.39万 - 项目类别:
Linkage Infrastructure, Equipment and Facilities
Nanomechanical testing system
纳米力学测试系统
- 批准号:
522119324 - 财政年份:2023
- 资助金额:
$ 29.39万 - 项目类别:
Major Research Instrumentation
Nanomechanical Testing in Controlled Environments and in the TEM (Nano-TCT)
受控环境和 TEM 中的纳米力学测试 (Nano-TCT)
- 批准号:
EP/S009493/1 - 财政年份:2019
- 资助金额:
$ 29.39万 - 项目类别:
Research Grant
In situ SEM/FIB Nanomechanical Testing System
原位SEM/FIB纳米力学测试系统
- 批准号:
RTI-2018-00271 - 财政年份:2017
- 资助金额:
$ 29.39万 - 项目类别:
Research Tools and Instruments
MRI: Development of and Broad-Based Materials Research with the Next Generation Nanomechanical Testing Laboratory
MRI:下一代纳米力学测试实验室的发展和广泛的材料研究
- 批准号:
1743343 - 财政年份:2017
- 资助金额:
$ 29.39万 - 项目类别:
Standard Grant
Nanomechanical testing platform
纳米力学测试平台
- 批准号:
RTI-2018-00923 - 财政年份:2017
- 资助金额:
$ 29.39万 - 项目类别:
Research Tools and Instruments
MRI: Development of and Broad-Based Materials Research with the Next Generation Nanomechanical Testing Laboratory
MRI:下一代纳米力学测试实验室的发展和广泛的材料研究
- 批准号:
1427812 - 财政年份:2014
- 资助金额:
$ 29.39万 - 项目类别:
Standard Grant
Micro- and nanomechanical testing of superalloys at high temperatures (A06)
高温合金的微观和纳米力学测试(A06)
- 批准号:
211495666 - 财政年份:2012
- 资助金额:
$ 29.39万 - 项目类别:
CRC/Transregios
GOALI: Understanding 3D Dislocation Behavior in Al-Mg through Combined Electron Tomography and in situ TEM Nanomechanical Testing.
目标:通过组合电子断层扫描和原位 TEM 纳米力学测试了解 Al-Mg 中的 3D 位错行为。
- 批准号:
1235610 - 财政年份:2012
- 资助金额:
$ 29.39万 - 项目类别:
Continuing Grant
Nanomechanical testing of biomaterials and nanomaterials
生物材料和纳米材料的纳米力学测试
- 批准号:
315231-2005 - 财政年份:2004
- 资助金额:
$ 29.39万 - 项目类别:
Research Tools and Instruments - Category 1 (<$150,000)