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.
This is a phase diagram showing the cluster formations predicted by GA and their validation (squares).
Credit: Columbia Engineering
"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 materials—the Darwinian model of evolution—by 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 nanomaterials—a priority area under the White House's Materials Genome Initiative—using 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."
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.
This research has been funded by a $1.4 million three-year grant from the U.S. Department of Energy.Columbia Engineering
New concept for structural colors
18.05.2018 | Technische Universität Hamburg-Harburg
Saarbrücken mathematicians study the cooling of heavy plate from Dillingen
17.05.2018 | Universität des Saarlandes
So-called quantum many-body scars allow quantum systems to stay out of equilibrium much longer, explaining experiment | Study published in Nature Physics
Recently, researchers from Harvard and MIT succeeded in trapping a record 53 atoms and individually controlling their quantum state, realizing what is called a...
The historic first detection of gravitational waves from colliding black holes far outside our galaxy opened a new window to understanding the universe. A...
A team led by Austrian experimental physicist Rainer Blatt has succeeded in characterizing the quantum entanglement of two spatially separated atoms by observing their light emission. This fundamental demonstration could lead to the development of highly sensitive optical gradiometers for the precise measurement of the gravitational field or the earth's magnetic field.
The age of quantum technology has long been heralded. Decades of research into the quantum world have led to the development of methods that make it possible...
Cardiovascular tissue engineering aims to treat heart disease with prostheses that grow and regenerate. Now, researchers from the University of Zurich, the Technical University Eindhoven and the Charité Berlin have successfully implanted regenerative heart valves, designed with the aid of computer simulations, into sheep for the first time.
Producing living tissue or organs based on human cells is one of the main research fields in regenerative medicine. Tissue engineering, which involves growing...
A team of scientists of the Max Planck Institute for the Structure and Dynamics of Matter (MPSD) at the Center for Free-Electron Laser Science in Hamburg investigated optically-induced superconductivity in the alkali-doped fulleride K3C60under high external pressures. This study allowed, on one hand, to uniquely assess the nature of the transient state as a superconducting phase. In addition, it unveiled the possibility to induce superconductivity in K3C60 at temperatures far above the -170 degrees Celsius hypothesized previously, and rather all the way to room temperature. The paper by Cantaluppi et al has been published in Nature Physics.
Unlike ordinary metals, superconductors have the unique capability of transporting electrical currents without any loss. Nowadays, their technological...
02.05.2018 | Event News
13.04.2018 | Event News
12.04.2018 | Event News
18.05.2018 | Power and Electrical Engineering
18.05.2018 | Information Technology
18.05.2018 | Information Technology