Award Abstract # 1661412
Tip-based Nanochemistry for Printing Soft Materials

NSF Org: CMMI
Division of Civil, Mechanical, and Manufacturing Innovation
Recipient: TRUSTEES OF BOSTON UNIVERSITY
Initial Amendment Date: May 26, 2017
Latest Amendment Date: July 17, 2020
Award Number: 1661412
Award Instrument: Standard Grant
Program Manager: Khershed Cooper
khcooper@nsf.gov
 (703)292-7017
CMMI
 Division of Civil, Mechanical, and Manufacturing Innovation
ENG
 Directorate for Engineering
Start Date: September 1, 2017
End Date: August 31, 2022 (Estimated)
Total Intended Award Amount: $400,886.00
Total Awarded Amount to Date: $478,859.00
Funds Obligated to Date: FY 2017 = $400,886.00
FY 2018 = $8,000.00

FY 2020 = $69,973.00
History of Investigator:
  • Keith Brown (Principal Investigator)
    brownka@bu.edu
  • Sean Andersson (Co-Principal Investigator)
Recipient Sponsored Research Office: Trustees of Boston University
1 SILBER WAY
BOSTON
MA  US  02215-1703
(617)353-4365
Sponsor Congressional District: 07
Primary Place of Performance: Trustees of Boston University
8 St. Mary's Street
Boston
MA  US  02215-2421
Primary Place of Performance
Congressional District:
07
Unique Entity Identifier (UEI): THL6A6JLE1S7
Parent UEI:
NSF Program(s): AM-Advanced Manufacturing,
Special Initiatives,
NANOMANUFACTURING
Primary Program Source: 01001819DB NSF RESEARCH & RELATED ACTIVIT
01001718DB NSF RESEARCH & RELATED ACTIVIT

01002021DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 9178, 9231, 116E, 083E, 9251, 084E, 081E, 091Z
Program Element Code(s): 088y00, 164200, 178800
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.041

ABSTRACT

The ubiquitous utilization of integrated circuits shows that industry is exceptionally capable of manufacturing ultra-high resolution arrangements of semiconductors, metals and insulators. However, there is a vast disconnect between the methods for patterning these sorts of hard materials and those that exist for patterning soft materials such as chemicals, polymers or biological materials. If it were possible to pattern soft materials with the same reliability and resolution as hard materials, it would enable the manufacture of myriad structures and devices including electronics with multiplexed biosensor arrays or nanoscale organic electronic devices for applications in stretchable electronics. While additive manufacturing strategies are very useful at the macroscopic scale, these approaches have not achieved manufacturing-level reproducibility when patterning soft materials at the nanoscale. This award will enable nanoscale manufacturing of soft materials by providing the tools and understanding needed to realize patterning with industry-required reliably and nanoscale resolution. This interdisciplinary work spans fluid mechanics, control theory, and nanoscience and contributes to the undergraduate and graduate level education of engineering students. Furthermore, this work provides opportunities for students from broad backgrounds to design and interact with materials at previously inaccessible scales.

The main goal of this research work is to develop the fundamental and technological foundation to transition tip-based nanopatterning of soft materials into a manufacturing tool. This approach is based on the transfer of material from an ink-coated scanning probe to a surface. Despite over a decade of research, reproducibility and controllability have remained key barriers for the adoption of this technique in a manufacturing setting. This research work addresses a number of processing issues that have not previously received attention. It investigates and develops novel approaches, e.g., a method for precisely monitoring the quantity of ink that is on a probe, an ink formulation that allows one to pattern and image with the same probe, and a procedure for monitoring and controlling the concentration of reagents in the ink during patterning. Equally important, these studies are designed to provide deeper insight into the patterning process and answer open questions about nanoscale capillarity and statistical mechanics in systems that violate the continuum hypothesis. Additionally, these new approaches are combined with advanced models of patterning to form an automated closed-loop feedback system that iteratively improves the quality of patterning in situ.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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(Showing: 1 - 10 of 15)
Xu, Bowen and Saygin, Verda and Brown, Keith A. and Andersson, Sean B. "High-resolution measurement of atomic force microscope cantilever resonance frequency" Review of Scientific Instruments , v.91 , 2020 https://doi.org/10.1063/5.0026069 Citation Details
Wang, Sen and Li, Le and Su, Deanyone and Robin, Kevin and Brown, Keith A. "Patterning Porosity in Hydrogels by Arresting Phase Separation" ACS Applied Materials & Interfaces , v.10 , 2018 10.1021/acsami.8b11530 Citation Details
Alsharif, Nourin and Burkatovsky, Anna and Lissandrello, Charles and Jones, Keith M. and White, Alice E. and Brown, Keith A. "Design and Realization of 3D Printed AFM Probes" Small , v.14 , 2018 10.1002/smll.201800162 Citation Details
Brown, Keith A. "Scanning probes as a materials automation platform with extremely miniaturized samples" Matter , v.5 , 2022 https://doi.org/10.1016/j.matt.2022.08.004 Citation Details
Brown, Keith A. and Brittman, Sarah and Maccaferri, Nicolò and Jariwala, Deep and Celano, Umberto "Machine Learning in Nanoscience: Big Data at Small Scales" Nano Letters , v.20 , 2019 10.1021/acs.nanolett.9b04090 Citation Details
Brown, Keith A. and Hedrick, James L. and Eichelsdoerfer, Daniel J. and Mirkin, Chad A. "Nanocombinatorics with Cantilever-Free Scanning Probe Arrays" ACS Nano , v.13 , 2019 https://doi.org/10.1021/acsnano.8b08185 Citation Details
Gongora, Aldair E. and Snapp, Kelsey L. and Pang, Richard and Tiano, Thomas M. and Reyes, Kristofer G. and Whiting, Emily and Lawton, Timothy J. and Morgan, Elise F. and Brown, Keith A. "Designing lattices for impact protection using transfer learning" Matter , v.5 , 2022 https://doi.org/10.1016/j.matt.2022.06.051 Citation Details
Gongora, Aldair E. and Snapp, Kelsey L. and Whiting, Emily and Riley, Patrick and Reyes, Kristofer G. and Morgan, Elise F. and Brown, Keith A. "Using simulation to accelerate autonomous experimentation: A case study using mechanics" iScience , v.24 , 2021 https://doi.org/10.1016/j.isci.2021.102262 Citation Details
Gongora, Aldair E. and Xu, Bowen and Perry, Wyatt and Okoye, Chika and Riley, Patrick and Reyes, Kristofer G. and Morgan, Elise F. and Brown, Keith A. "A Bayesian experimental autonomous researcher for mechanical design" Science Advances , v.6 , 2020 10.1126/sciadv.aaz1708 Citation Details
Kang, Zhixin and Saygin, Verda and Brown, Keith A. and Andersson, Sean "A stepped-sine curve-fit algorithm for finding cantilever resonance shifts in AFM" 2019 American Control Conference (ACC) , 2019 10.23919/ACC.2019.8814403 Citation Details
Saygin, Verda and Xu, Bowen and Andersson, Sean B. and Brown, Keith A. "Closed-Loop Nanopatterning of Liquids with Dip-Pen Nanolithography" ACS Applied Materials & Interfaces , v.13 , 2021 https://doi.org/10.1021/acsami.1c00095 Citation Details
(Showing: 1 - 10 of 15)

PROJECT OUTCOMES REPORT

Disclaimer

This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.

The goal of this program was to reliably prepare extremely miniaturized samples of polymers. The technique for fabricating these samples was based on an atomic force microscope, which consists of a sharp tip at the end of a compliant cantilever. Specifically, we utilize dip-pen nanolithography, a process for using an atomic force microscope probe as a pen that transfers materials from the tip to a substrate at precise locations by programmably bringing the two into contact. While this approach was already capable of patterning very small samples, it was only able to do so without control over the amount of material to be deposited, limiting its use as a manufacturing tool. This program was developed to overcome this limitation and transform dip-pen nanolithography into a closed-loop patterning system in which the size of patterned features could be predicted, specified, and measured. As a foundational discovery, we invented a process for measuring the quantity of fluid on an atomic force microscope probe by examining changes in the vibrational resonance frequency of the cantilever. This process required innovating in the type of atomic force microscope probe, how it is treated, and the type of fluid used for patterning. By measuring the fluid mass before and after patterning actions, it is possible to measure the amount of fluid written. Using this foundation, we were able to study the fluid transport physics and discover that the amount of fluid transferred can be controlled by adjusting the speed at which the probe is withdrawn from the surface. Collectively, these innovations allowed us to realize patterning of extremely small quantities of fluid with control over the amount and location of this fluid.

Having invented a process for patterning extremely small quantities of fluid, we sought both to further expand the manufacturing capabilities of this process and to use it to produce material innovations. For example, we found that the fluid transfer process allowed us to load controlled amounts of epoxy onto an atomic force microscope probe. As a second step, this epoxy-tipped probe can then be brought into contact with samples of interest to adhere microscopic materials to the end of this probe. We found that this process works for both attaching microscopic spherical beads as well as metal-organic framework microcrystals.

While controlling the amount of material patterned is an important facet of nanomanufacturing, it is also important to control the composition of the material that is patterned. Thus, we sought to overcome the long-standing limitation of dip-pen nanolithography that the composition of the material to be patterned has to be dictated in advance of the experiment by the operator. We hypothesized that control over fluid transfer would allow us to realize mixtures of fluids. In particular, we found that when a probe loaded with a fluid sample is brought into contact with a fluid sample on a surface, these fluids mix and the resulting mixture can be controllably patterned. This is a critical innovation as it means that preparing a set of reservoir samples can allow a user to build a compositional gradient of materials. 

Despite this program predominantly focusing on advancing the manufacturing aspects of dip-pen nanolithography, it also resulted in a major advance that moves this approach closer to being a platform for materials discovery. Atomic force microscopy is noteworthy as a tool for nanoscience due to its versatility. In addition to allowing one to pattern features using dip-pen nanolithography, it also allows one to functionally characterize and topographically image samples with exceptionally high spatial resolution. While this capability has already been extensively leveraged for nanoscience, advancing the manufacturing capabilities of atomic force microscopy has the important implication that interesting and useful structures can now be made and interrogated using the same instrument. Crucially, this would allow one to select a desired material composition, realize a structure with this composition, and then interrogate it using a single system. As an initial proof of this concept, we used the atomic force microscope to both pattern photocurable resin and determine the mechanical properties of the cured resin. In addition to allowing us to compare bulk and nanoscale mechanical properties, this experiment provided an important proof-of-concept showing that it is possible to perform closed-loop materials discovery.


Last Modified: 12/22/2022
Modified by: Keith A Brown

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