Navigation Links
Using genetic algorithms to discover new nanostructured materials
Date:10/28/2013

New York, NYOctober 28, 2013: Researchers at Columbia Engineering, led by Chemical Engineering Professors Venkat Venkatasubramanian and Sanat Kumar, have developed a new approach to designing novel nanostructured materials through an inverse design framework using genetic algorithms. The study, published in the October 28 Early Online edition of Proceedings of the National Academy of Sciences (PNAS), is the first to demonstrate the application of this methodology to the design of self-assembled nanostructures, and shows the potential of machine learning and "big data" approaches embodied in the new Institute for Data Sciences and Engineering at Columbia.

"Our framework can help speed up the materials discovery process," says Venkatasubramanian, Samuel Ruben-Peter G. Viele Professor of Engineering, and co-author of the paper. "In a sense, we are leveraging how nature discovers new materialsthe Darwinian model of evolutionby suitably marrying it with computational methods. It's Darwin on steroids!"

Using a genetic algorithm they developed, the researchers designed DNA-grafted particles that self-assembled into the crystalline structures they wanted. Theirs was an "inverse" way of doing research. In conventional research, colloidal particles grafted with single-stranded DNA are allowed to self-assemble, and then the resulting crystal structures are examined. "Although this Edisonian approach is useful for a posteriori understanding of the factors that govern assembly," notes Kumar, Chemical Engineering Department Chair and the study's co-author, "it doesn't allow us to a priori design these materials into desired structures. Our study addresses this design issue and presents an evolutionary optimization approach that was not only able to reproduce the original phase diagram detailing regions of known crystals, but also to elucidate previously unobserved structures."

The researchers are using "big data" concepts and techniques to discover and design new nanomaterialsa priority area under the White House's Materials Genome Initiativeusing a methodology that will revolutionize materials design, impacting a broad range of products that affect our daily lives, from drugs and agricultural chemicals such as pesticides or herbicides to fuel additives, paints and varnishes, and even personal care products such as shampoo.

"This inverse design approach demonstrates the potential of machine learning and algorithm engineering approaches to challenging problems in materials science," says Kathleen McKeown, director of the Institute for Data Sciences and Engineering and Henry and Gertrude Rothschild Professor of Computer Science. "At the Institute, we are focused on pioneering such advances in a number problems of great practical importance in engineering."

Venkatasubramanian adds, "Discovering and designing new advanced materials and formulations with desired properties is an important and challenging problem, encompassing a wide variety of products in industries addressing clean energy, national security, and human welfare." He points out that the traditional Edisonian trial-and-error discovery approach is time-consuming and costlyit can cause major delays in time-to-market as well as miss potential solutions. And the ever-increasing amount of high-throughput experimentation data, while a major modeling and informatics challenge, has also created opportunities for material design and discovery.

The researchers built upon their earlier work to develop what they call an evolutionary framework for the automated discovery of new materials. Venkatasubramanian proposed the design framework and analyzed the results, and Kumar developed the framework in the context of self-assembled nanomaterials. Babji Srinivasan, a postdoc with Venkatasubramanian and Kumar and now an assistant professor at IIT Gandhinagar, and Thi Vo, a PhD candidate at Columbia Engineering, carried out the computational research. The team collaborated with Oleg Gang and Yugang Zhang of Brookhaven National Laboratory, who carried out the supporting experiments.

The team plans to continue exploring the design space of potential ssDNA-grafted colloidal nanostructures, improving its forward models, and bring in more advanced machine learning techniques. "We need a new paradigm that increases the idea flow, broadens the search horizon, and archives the knowledge from today's successes to accelerate those of tomorrow," says Venkatasubramanian.


'/>"/>

Contact: Holly Evarts
holly.evarts@columbia.edu
347-453-7408
Columbia University
Source:Eurekalert  

Related biology technology :

1. Researchers shrink tumors and minimize side effects using tumor-homing peptide to deliver treatment
2. Eye Surgery Center of Michigan First in Southeast Michigan to Perform Bladeless Cataract Surgery Using New LenSx® Laser Technology
3. Slovenias 1st Total Artificial Heart Patient Discharged from UMC Ljubljana Using the Freedom® Portable Driver
4. PubMed Users Now Save Time Accessing and Organizing Scientific Papers by Using Bibliogo From Reprints Desk
5. Genomic Health and OncoMed Announce Strategic Alliance for Biomarker Research and Discovery Using Next Generation Sequencing
6. Using nanoclays to build better asphalt pavement
7. People with paralysis control robotic arms to reach and grasp using brain computer interface
8. From lemons to lemonade: Using carbon dioxide to make carbon nitride
9. Making microscopic machines using metallic glass
10. A new imaging system produces 3-D models of monuments using unmanned aircraft
11. DNA Blood Test Detects Cancer Resistance Using Inostics BEAMing Technology
Post Your Comments:
*Name:
*Comment:
*Email:
Related Image:
Using genetic algorithms to discover new nanostructured materials
(Date:2/11/2016)... ... February 11, 2016 , ... Reichert Technologies, which has ... to pursue the highest level of accuracy and quality with the addition of ... the AR5 Refractometer. Accurate, reliable and tough enough for the most demanding ...
(Date:2/11/2016)... ... 11, 2016 , ... Global Stem Cells Group, ... Ecuador. The new facility will provide advanced protocols and state-of-the-art techniques in cellular ... , The new GSCG clinic is headed by four prominent Ecuadorian physicians, ...
(Date:2/10/2016)... Early-career researchers from Indonesia , ... Uganda and Yemen honored ... Indonesia , Nepal , ... are being honored for their accomplishments in nutrition, psychiatry, biotechnology, ... young women scientists who are pursuing careers in agriculture, biology and medicine ...
(Date:2/10/2016)... NX Prenatal Inc., a US based ... for early warning of adverse pregnancy outcomes, announced ... by Dr. Thomas McElrath of Brigham ... Medicine,s (SMFM) annual meeting held in ... The presentation reported initial positive top-line results regarding ...
Breaking Biology Technology:
(Date:2/3/2016)... , Feb. 3, 2016 ... the addition of the "Emotion Detection ... Machine Learning, and Others), Software Tools (Facial ... Areas, End Users,and Regions - Global forecast ... --> http://www.researchandmarkets.com/research/d8zjcd/emotion_detection ) has ...
(Date:2/2/2016)... , Feb. 2, 2016 Checkpoint ... that Rising Market Are you interested in ... forecasts revenues for checkpoint inhibitors. Visiongain,s report gives ... submarket, product and national level. Avoid falling ... what progress, opportunities and revenues those emerging cancer ...
(Date:2/2/2016)... MOUNTAIN VIEW, Calif. , Feb. 2, 2016 ... diabetic retinopathy market, Frost & Sullivan recognizes US-based ... North America Frost & Sullivan Award for New ... technology provider in North America ... standard in the rapidly growing diabetic retinopathy market. ...
Breaking Biology News(10 mins):