The authors want to thank Tim Allis at UC Merced for his assistance in this project.&#160; The NSF-COINS program at UCM supported (KAM) in an early part of this work.&#160; An NSF-BRIGE award supported co-authors (BND and KAM), providing funds for this work and travel expenses to conferences.
The research group wishes to acknowledge primarily the National Science Foundation for funding this work via a BRIGE award.&#160; This material is based upon work supported by the National Science Foundation under Grant No. 1032653.

1. Preparing NanospringCarver Files and Starting MATLAB on a LINUX PC
The following steps are designed for a general user to make use of the files provided online26.
<ol>
	<li>Unpack the nanosprings.tar.gz file archive into the &#8220;Home&#8221; or another preferred directory.
	<ol>
		<li>Download the nanosprings.tar.gz file archive from the web repository26.</li>
		<li>Locate the downloaded archive and move it to a preferred working directory entitled &#8220;Documents/Nanosprings&#8221;.</li>
		<li>Right-click nanosprings.tar.gz and select &#8220;extract here&#8221; from the right-click context menu.</li>
	</ol>
	</li>
	<li>Verify that all of the required files are present in the current directory. A list of those files and their purpose follows: 
	Makefile &#8211; manually managed compile file for nanosprings.cpp and Point.cpp 
	Nanosprings.fig &#8211;MATLAB GUI internals 
	Nanosprings.m &#8211;MATLAB GUI code 
	Point.cpp &#8211; Point (atom) class definition 
	Point.h &#8211; Point (atom) class header 
	carve &#8211; stand-alone nanosprings executable 
	example.par &#8211; example parameter file 
	glasscube.inp &#8211; glasscube data file 
	nanosprings.cpp &#8211; main nanosprings code 
	nanosprings_diagram.jpg &#8211; example nanospring for display 
	nanospringsmex.cpp &#8211; MATLAB-integrated nanosprings.cpp 
	nanospringsmex.mexglx &#8211; MATLAB-integrated nanosprings executable 
	Note: The user will need to create the &#8220;nanospringsmex.mexglx&#8221; executable file for the particular Linux machine being used (32-bit version in this example). If this has not yet been done, verify access to the MATLAB &#8220;mex&#8221; compiler by typing on the command line &#8220;which mex&#8221; and verifying the existence of the program. Also verify access to the MATLAB program by typing on the command line &#8220;which matlab&#8221;. Using a command line to type &#8220;mex nanospringsmex.cpp Point.cpp&#8221; will create the &#8220;nanospringsmex.mexglx&#8221; executable MATLAB-integrated NanospringCarver file, as shown in the instructions below. Though not required for the GUI interface, if desired a stand-alone version of the NanospringCarver program can be created by typing &#8220;make&#8221; on a command line. This will compile the nanosprings.cpp and Point.cpp program elements together to create the &#8220;carve&#8221; executable file. In this tutorial, the &#8220;glasscube.inp&#8221; file contains position information for 192,000 silicon and oxygen atoms representing a silica glass model, with each line containing an atom ID, atom type, and x, y, z coordinates for the atom. The first line of the file is the total atom count (192,000). The atomic coordinates in this file are relative values, which if multiplied by 0.716 would represent nanometer distances.</li>
	<li>On the desktop, open a terminal window. On many LINUX versions accomplish this by simultaneously pressing the &#8220;Ctrl&#8221;, &#8220;Alt&#8221; and &#8220;T&#8221; keys.</li>
	<li>Change the directory to the folder into which the nanosprings project files were extracted by typing: 
	cd Documents/Nanosprings/</li>
	<li>Next, run the command to compile the binary for the system by typing: 
	mex nanospringsmex.cpp Point.cpp</li>
	<li>Next initiate MATLAB by typing matlab on the command line</li>
</ol>
2. Modifying and Using a Graphical User Interface (GUI) to the NanospringCarver Program
Follow the steps below using the files provided online26.
<ol>
	<li>Open the GUIDE in MATLAB by clicking the GUIDE icon, on the top left toolbar area (Figure 2), to display a new window with the GUIDE quick start (Figure 3).</li>
</ol>
<img alt="Figure 2" fo:content-width="6in" src="/files/ftp_upload/51372/51372fig2highres.jpg" width="600" /> 
Figure 2: MATLAB user interface showing how to open MATLAB GUIDE.
<img alt="Figure 3" fo:content-width="6in" src="/files/ftp_upload/51372/51372fig3highres.jpg" width="600" /> 
Figure 3: MATLAB GUIDE interface initializing.
<ol start="2">
	<li>Use the &#8220;Open Existing GUI&#8221; tab (Figure 4) to modify an existing figure. Click on the &#8220;Browse&#8221; button to search for the existing GUI figure to be modified. After selecting the figure file (Nanosprings.fig, see blue box), click on &#8220;Open&#8221; on both windows to display a new window with the GUI figure. Locate the buttons available to be utilized for GUI creation on the left panel (Figure 5).</li>
</ol>
<img alt="Figure 4" fo:content-width="6in" src="/files/ftp_upload/51372/51372fig4highres.jpg" width="600" /> 
Figure 4: MATLAB GUIDE interface showing how to open an existing GUI figure file.
<img alt="Figure 5" fo:content-width="6in" src="/files/ftp_upload/51372/51372fig5highres.jpg" width="600" /> 
Figure 5: MATLAB GUIDE interface showing tools for modifying an existing GUI figure.
<ol start="3">
	<li>In order to run the GUI, click on &#8220;Run&#8221; under the &#8220;Tools&#8221; menu. Then, click &#8220;Yes&#8221; when a pop-up window prompts whether to save the figure before running. A new window displays the modified GUI.</li>
	<li>If necessary, create another GUI for a different specific material using this GUI as an example.</li>
	<li>To set up the example run, first click on the &#8220;Select input model file&#8221; button at the top of the GUI and navigate to the &#8220;glasscube.inp&#8221; file. Select this file and click &#8220;Open&#8221; to close the browsing window. The selected input file and path to it should now appear in the GUI window to the right of the &#8220;Selected input model file&#8221; button (Figure 6).</li>
</ol>
<img alt="Figure 6" fo:content-width="6in" src="/files/ftp_upload/51372/51372fig6highres.jpg" width="600" /> 
Figure 6: Screenshot of using GUI to create an example silica nanospring model.
<ol start="6">
	<li>Next, use the &#8220;Browse&#8221; button in the &#8220;Output Model&#8221; section to browse for and select the directory to save the output model into. Ensure that the output directory is actively selected in order for the run to be enabled, even though there is an output directory already listed in the accompanying window to the right of this button. 
	Note: The &#8220;Advance Parameters Minimum Distance&#8221; value listed (0.209311 in Figure 6) was computed specifically for the &#8220;glasscube.inp&#8221; input file provided in this example, and should be left as is. This value may be computed as necessary on first use of a different input file by entering a value of &#8220;0&#8221; in this location before running the model. In this example, all parameter values are in relative units to match the input atomic coordinate system. If multiplied by 0.716 the parameter values would represent nanometer distances.</li>
	<li>Run the example using the given spring parameters of r = 1.0, R = 5.0, p = 1.5, and d = .209311 by pressing the GUI &#8220;Run&#8221; button. View feedback from the run in the MATLAB Command window (Figure 7). In the feedback, check that the spring parameters are confirmed, that the input data file is read successfully, and the results stored in the output file named &#8220;model&#8221; are described.</li>
</ol>
<img alt="Figure 7" fo:content-width="5in" src="/files/ftp_upload/51372/51372fig7highres.jpg" width="500" /> 
Figure 7: MATLAB Command window feedback from GUI-based Nanosprings run.
Note: In the above example, the file &#8220;model&#8221; contains 5,176 atoms comprising the desired spring, one per line, with the first line giving the total number of atoms in the file. Each line defining an atom includes the atom ID, atom type, and x, y, z coordinates of that atom.
<ol start="8">
	<li>Once the GUI interface is finalized, perform successive runs by right-clicking on &#8220;Nanosprings.m&#8221; in the MATLAB &#8220;Current Folder&#8221; window, and selecting &#8220;Run&#8221; to bring up the GUI interface directly. 
	Note: Various references are listed27-31 for additional information on MATLAB GUIDE and the basic GUIDE interface.</li>
</ol>
3. Verifying NanospringCarver Results in an Open-source Visualizer19
The following steps are designed for a general user to visualize and verify the output spring models created by NanospringCarver.
<ol>
	<li>Use the NanospringCarver MATLAB GUI as described above to generate files for input into the visualization program19. When running the visualization program, use the &#8220;point coordinate file&#8221; input option, distinguish atom types by color, and select an axis grid border for the field.</li>
	<li>Measure distances in the spring models and make a record of them.</li>
	<li>Compare measured data against desired spring dimensions and verify spring model accuracy.</li>
</ol>
4. Using NanospringCarver Results in MD Tensile Simulations of Nanosprings
The following steps are summarized for a general user to use the spring models created by NanospringCarver as input to a conventional open-source MD code32.
<ol>
	<li>Download the latest version of the open-source MD program LAMMPS. Refer to the associated online documentation for manuals and examples.</li>
	<li>Determine the dimensions of the desired nanospring model in order to prepare the appropriate initial bulk silica glass model, as reported before18.</li>
	<li>Create the desired nanospring model using the NanospringCarver MATLAB GUI (see Section 2 above).</li>
	<li>Perform tensile simulations on the desired nanospring, by stretching the model axially 11,13,23. Produce a representative video of nanospring model being stretched (see Figure 8, below, and Animated Figure 1) for visualization and analysis. Scientific results regarding the stress-strain behavior and stiffness of several nanospring models under tension have been reported elsewhere23.</li>
</ol>
<img alt="Figure 8" fo:content-width="4in" src="/files/ftp_upload/51372/51372fig8highres.jpg" width="400" /> 
Figure 8: Screenshot of a silica nanospring during tensile simulation (see also Animated Figure 1).

<ol>
	<li>Gao, P. X., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Conversion+of+zinc+oxide+nanobelts+into+superlattice-structured+nanohelices.">Conversion of zinc oxide nanobelts into superlattice-structured nanohelices.</a> Science. 309 (5741), 1700-1704 (2005).</li><li>McIlroy, D. N., Zhang, D., Kranov, Y., Norton, M. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Nanosprings.">Nanosprings.</a> Appl. Phys. Lett. 79 (10), 1540-1542 (2001).</li><li>He, Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multilayered+Si/Ni+nanosprings+and+their+magnetic+properties.">Multilayered Si/Ni nanosprings and their magnetic properties.</a> Small. 3 (1), 153-160 (2007).</li><li>Cammarata, R. C., Sieradzki, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Surface+and+interface+stresses.">Surface and interface stresses.</a> Annu. Rev. Mater. Sci. 24 (1), 215-234 (1994).</li><li>Becker, N., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Molecular+nanosprings+in+spider+capture-silk+threads.">Molecular nanosprings in spider capture-silk threads.</a> Nat. Mater. 2 (4), 278-283 (2003).</li><li>Singh, J. P., Liu, D. -. L., Ye, D. -. X., Picu, R. C., Lu, T. -. M., Wang, G. -. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Metal-coated+Si+springs:+nanoelectromechanical+actuators.">Metal-coated Si springs: nanoelectromechanical actuators.</a> Appl. Phys. Lett. 84 (18), 3657-3659 (2004).</li><li>Kim, K. J., Park, K., Lee, J., Zhang, Z. M., King, W. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Nanotopographical+imaging+using+a+heated+atomic+force+microscope+cantilever+probe.">Nanotopographical imaging using a heated atomic force microscope cantilever probe.</a> Sens. Actuators A-Phys. 136 (1), 95-103 (2007).</li><li>Dobrokhotov, V., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=ZnO+coated+nanospring-based+chemiresistors.">ZnO coated nanospring-based chemiresistors.</a> J. Appl. Phys. 111 (4), 044311-044318 (2012).</li><li>Sai, V. V. R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Chapter+1:+Bio+Sensors,+Diagnostics+&amp;+Imaging.">Chapter 1: Bio Sensors, Diagnostics &amp; Imaging.</a> Nanotechnology 2010: Bio Sensors, Instruments, Medical, Environment and Energy. , 19 (2010).</li><li>Sai, V. V. R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Silica+nanosprings+coated+with+noble+metal+nanoparticles:+highly+active+SERS+substrates.">Silica nanosprings coated with noble metal nanoparticles: highly active SERS substrates.</a> J. Phys. Chem. C. 115 (2), 453-459 (2010).</li><li>Fonseca, d. a., Galv&#227;o, A. F., S, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mechanical+properties+of+nanosprings.">Mechanical properties of nanosprings.</a> Phys. Rev.Lett. 92 (17), 175502-175505 (2004).</li><li>Zhang, G., Zhao, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mechanical+characteristics+of+nanoscale+springs.">Mechanical characteristics of nanoscale springs.</a> J. Appl. Phys. 95 (1), 267-271 (2004).</li><li>Fonseca, d. a., Malta, A. F., Galv&#227;o, C. P., S, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mechanical+properties+of+amorphous+nanosprings.">Mechanical properties of amorphous nanosprings.</a> Nanotechnology. 17 (22), 5620-5626 (2006).</li><li>Mohedas, I., Garcia, A. P., Buehler, M. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Nanomechanics+of+biologically+inspired+helical+silica+nanostructures.">Nanomechanics of biologically inspired helical silica nanostructures.</a> Proceedings of the Institution of Mechanical Engineers, Part N: J. Nanoengineering and Nanosystems. 224 (3), 93-100 (2010).</li><li>Chang, I. L., Yeh, M. -. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+atomistic+study+of+nanosprings.">An atomistic study of nanosprings.</a> J. Appl. Phys. 104 (2), 0243051-0243056 (2008).</li><li>Poggi, M. A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Measuring+the+compression+of+a+carbon+nanospring.">Measuring the compression of a carbon nanospring.</a> Nano Lett. 4 (6), 1009-1016 (2004).</li><li>Chen, X., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mechanics+of+a+carbon+nanocoil.">Mechanics of a carbon nanocoil.</a> Nano Lett. 3 (9), 1299-1304 (2003).</li><li>D&#225;vila, L. P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Transformations+in+the+medium-range+order+of+fused+silica+under+high+pressure.">Transformations in the medium-range order of fused silica under high pressure.</a> Phys. Rev. Lett. 91 (20), 2055011-2055014 (2003).</li><li>. Nick Gnedin&#8217;s Ionization FRont Interactive Tool (IFrIT) v. 3.2.8 - A general purpose visualization software [Internet] Available from: <a target="_blank" href="https://sites.google.com/site/ifrithome/">https://sites.google.com/site/ifrithome/</a> (2013)</li><li>Silva, E. C. C. M., Tong, L., Yip, S., Van Vliet, K. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Size+effects+on+the+stiffness+of+silica+nanowires.">Size effects on the stiffness of silica nanowires.</a> Small. 2 (2), 239-243 (2006).</li><li>D&#225;vila, L. P., Leppert, V. J., Bringa, E. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+mechanical+behavior+and+nanostructure+of+silica+nanowires+via+simulations.">The mechanical behavior and nanostructure of silica nanowires via simulations.</a> Scripta Mater. 60 (10), 843-846 (2009).</li><li>Doblack, B. N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> The structure and properties of silica glass nanostructures using novel computational systems [thesis]. , 55-55 (2013).</li><li>Nanospring Models via MATLAB and NanospringCarver. Davila group website [Internet] Available from: <a target="_blank" href="https://eng.ucmerced.edu/people/ldavila/home/nanospring-models-via-matlab-nanospringcarver-dissemination-of-research-results-and-products">https://eng.ucmerced.edu/people/ldavila/home/nanospring-models-via-matlab-nanospringcarver-dissemination-of-research-results-and-products</a> (2013)</li><li>. Blinkdagger - An Engineering and MATLAB blog [Internet] Available from: <a target="_blank" href="https://eng.ucmerced.edu/people/ldavila/home/nanospring-models-via-matlab-nanospringcarver-dissemination-of-research-results-and-products">https://eng.ucmerced.edu/people/ldavila/home/nanospring-models-via-matlab-nanospringcarver-dissemination-of-research-results-and-products</a> (2014)</li></ol>

The authors declare that they have no competing financial interests.

Modification of the original approach to create nanohelical structures led to the development of two distinct codes to allow creation of both nanoribbons and nanosprings from an initial bulk silica glass MD model.&#160; The verification of the silica nanoribbon and nanospring models was pursued using different software packages19-20, which confirmed their dimensional accuracy within the measurement capability of the programs.&#160; Comparison between nanosprings and nanoribbons was also performed by overlaying...

A correction was made to <a href="/video/51372">Scalable Nanohelices for Predictive Studies and Enhanced 3D Visualization</a>. Online article is missing its 29th author reference.
The reference section has added:
29. MathWorks. Use and create MATLAB MEX-files [Internet]. [Massachusetts]: MathWorks; [cited 2013 May 30]. Available from: http://
www.mathworks.com/help/matlab/call-mex-files-1.html (2014).

A correction was made to <a href="/video/51372">Scalable Nanohelices for Predictive Studies and Enhanced 3D Visualization</a>. Online article is missing its 29th author reference.

Erratum: Scalable Nanohelices for Predictive Studies and Enhanced 3D Visualization

Helical nanostructures are typically produced in the laboratory using chemical vapor deposition techniques1-2, while new approaches have been reported in the literature3.&#160; In particular nanosprings and nanoribbons have been studied because of their distinct properties and promising applications in sensors, optics, and electromechanical and fluidic devices4-7.&#160; Synthesis methods have been reported to produce silica (SiO2) nanoribbons, making these structures potential building block units for hierarchical systems.&#160; Novel synthesis of 3D silica nanosprings has expanded their applications to chemiresistors when coated with ZnO8 or nanoparticles for diagnostic applications9-10.
Experimental studies on the mechanical properties of silica nanosprings and nanoribbons are scarce, primarily due to current limitations in manipulation and testing methods and equipment.&#160; Investigations into the nanomechanics of nanostructures and nanosprings have been reported using theory and simulations11-14.&#160; Some simulations13 have focused on nanomechanical behavior of amorphous nanosprings because they can explore regimes not fully accessible through experimentation.&#160; Atomistic studies of metallic nanosprings have been reported in literature to investigate the size dependence of elastic properties15, and more recently the nanomechanics of helical crystalline silica nanostructures14.&#160; Experimental testing of nanospring structures has also been performed in different materials such as helical carbon nanostructures and carbon nanocoils16-17.&#160; Despite the knowledge gathered thus far, a more complete understanding of the mechanical properties of these novel nanostructures is needed for future nanodevice fabrication efforts.
As MD studies of silica glass (non-crystalline silica) nanohelices are still quite limited, the atomistic modeling of such structures requires the creation of customized codes.&#160; No other alternative methods of creating silica glass helical MD models have been identified thus far upon recent literature search.&#160; In this work, a bottom-up approach to the atomistic modeling of helical silica glass nanostructures including nanosprings and nanoribbons is pursued for future large-scale MD nanomechanical simulations.&#160; The general approach involves the creation of an MD &#8220;bulk&#8221; silica glass model as reported previously18, and carving out various helical nanostructures from this &#8220;bulk&#8221; sample via two robust and adaptable computer codes developed for this purpose.&#160; Both computational procedures offer a distinct way to create nanoribbon and nanospring models with great efficiency and atomistic detail; these structures are suitable for large-scale atomistic simulations.&#160; In addition, a customized graphical user interface is used to facilitate creation and visualization of the helical structures.
The structure of the &#8220;bulk&#8221; silica glass model is initially created at room temperature.&#160; Large-scale MD simulations are conducted for this purpose using the Garofalini interatomic potential similar to prior studies18, which is relatively efficient computationally and appropriate for large systems. The initial &#8220;bulk&#8221; silica glass structure consists of a cubical model (14.3 x 14.3 x 14.3 nm3) which contains 192,000 atoms.&#160; The &#8220;bulk&#8221; silica glass model is equilibrated at 300 K for 0.5 nsec to obtain the initial state using periodic boundary conditions.
Two computational procedures are designed and utilized to create atomistic silica nanoribbon and nanospring models.&#160; The first method involves carving out silica nanoribbons from the &#8220;bulk&#8221; structure using the parametric equations that define a helix, and its geometry (pitch, radius of helix, and wire radius).&#160; This procedure includes using the AWK programming language, the LINUX operating system, and open-source visualization software19.&#160; The general iterative procedure to create atomistic models of nanoribbons involves: (1) selecting an atom in the &#8220;bulk&#8221; silica glass model, (2) calculating the distance from the selected atom to a point in space on a pre-defined helical function, (3) comparing this distance to the radius of the desired nanoribbon, and (4) discarding or keeping the atom in an output data model.&#160; A detailed step-by-step description for this method is included in the Scalable Open-Source Codes Supplemental Material.&#160; With this method, several silica nanoribbons were created using different pitch, radius of helix and nanoribbon radius values, which were measured subsequently for accuracy against the desired dimensional values with molecular analysis and visualization software19-20.&#160; Atomistic models of silica nanoribbons were generated with functional geometries (high values of pitch and low values of nanoribbon radius).&#160; Some artifacts, consisting of atoms excluded in error, leading to a less smooth nanoribbon surface, were observed at exceedingly high nanoribbon radius values and extremely low pitch values.&#160; Similar methods have been used in the process of creating silica nanowires21-23.
The second method presented here includes carving out silica nanosprings from the &#8220;bulk&#8221; silica structure by implementing pre-screening methods to increase efficiency in addition to the mathematical equations for a helix.&#160; This procedure required creating a more robust C++ code to allow greater flexibility in modeling these helical nanostructures.&#160; The iterative method to create atomistic models of nanosprings includes: (1) discarding all atoms guaranteed to fall outside the helical path, (2) deterministically selecting a point on the helical path, (3) comparing all atoms within a specific distance to this selected point, and (4) discarding or storing each atom in an output data model.&#160; A step-by-step description for this method is also included in the Scalable Open-Source Codes Supplemental Material.&#160; With this method, several silica nanospring models were obtained with varied dimensions (wire radius, radius of helix, and pitch of nanospring) as shown in Figure 1.&#160; Highly precise silica nanospring models were obtained efficiently with this method, with no evidence of artifacts found at extreme (low and high) pitch values for the nanospring.&#160; The creation and use of the graphical user interface for this method is described in the Protocol section.
<img alt="Figure 1" fo:content-width="4in" src="/files/ftp_upload/51372/51372fig1highres.jpg" width="400" /> 
Figure 1: A general helical structure showing characteristic dimensions, where r, R and p represent the wire radius, radius of helix, and pitch respectively. H denotes the total height of the helical structure23.
This protocol describes how to prepare the NanospringCarver files, running MATLAB24 on a LINUX25 PC, and use a graphical user interface to prepare atomistic nanospring models.&#160; These previously unavailable models serve as the basis for novel molecular dynamics (MD) simulations23 toward materials innovation research.
The general step-by-step procedure to create atomistic nanospring models involves using the following elements: (a) NanospringCarver (v. 0.5 beta) code (open-source in C++ language), (b) bulk silica glass model (input file), (c) MATLAB GUI interface and related files, and (d) MATLAB software (version 7) using a local license on a LINUX PC.&#160; Items (a)-(c) above (NanospringCarver code, silica glass model, MATLAB GUI files) are free to download online26.&#160; MATLAB (Matrix Laboratory) is a high-level language for numerical computation, visualization, and application development from MathWorks24, which is mostly used for data visualization and analysis, image processing, and computational biology.

<table border="0" cellpadding="0" cellspacing="0">
	<tbody>
		<tr>
			<td>MATLAB numerical computing software</td>
			<td>Mathworks</td>
			<td><a href="http://www.mathworks.com/products/matlab/description1.html">http://www.mathworks.com/products/matlab/description1.html</a></td>
			<td>See Protocol Introduction and Reference [24]</td>
		</tr>
		<tr>
			<td>NanospringCarver program code and files</td>
			<td>UC Merced - open source</td>
			<td><a href="http://tinyurl.com/qame8dj">http://tinyurl.com/qame8dj</a></td>
			<td>See Protocol Section 1 (Step 1.2) and Reference [26]</td>
		</tr>
		<tr>
			<td>MATLAB GUI files</td>
			<td>UC Merced - open source</td>
			<td><a href="http://tinyurl.com/qame8dj">http://tinyurl.com/qame8dj</a></td>
			<td>See Protocol Section 1 (Step 1.2) and Reference [26]</td>
		</tr>
		<tr>
			<td>Atomistic bulk glass input file</td>
			<td>UC Merced - open source</td>
			<td><a href="http://tinyurl.com/qame8dj">http://tinyurl.com/qame8dj</a></td>
			<td>See Protocol Section 1 (Step 1.2) and Reference [26]</td>
		</tr>
		<tr>
			<td>IFrIT visualization software</td>
			<td>Open source software</td>
			<td><a href="http://sites.google.com/site/ifrithome/">http://sites.google.com/site/ifrithome/</a></td>
			<td>See Protocol Section 3 and Reference [19]</td>
		</tr>
		<tr>
			<td>LAMMPS molecular dynamics software</td>
			<td>Open source software</td>
			<td><a href="http://www.lammps.sandia.gov/">http://www.lammps.sandia.gov/</a></td>
			<td>See Protocol Section 4 and Reference [32]</td>
		</tr>
	</tbody>
</table>

scalable nanohelices for predictive studies and enhanced 3d visualization

Spring-like materials are ubiquitous in nature and of interest in nanotechnology for energy harvesting, hydrogen storage, and biological sensing applications.&#160; For predictive simulations, it has become increasingly important to be able to model the structure of nanohelices accurately.&#160; To study the effect of local structure on the properties of these complex geometries one must develop realistic models.&#160; To date, software packages are rather limited in creating atomistic helical models.&#160; This work focuses on producing atomistic models of silica glass (SiO2) nanoribbons and nanosprings for molecular dynamics (MD) simulations. Using an MD model of &#8220;bulk&#8221; silica glass, two computational procedures to precisely create the shape of nanoribbons and nanosprings are presented.&#160; The first method employs the AWK programming language and open-source software to effectively carve various shapes of silica nanoribbons from the initial bulk model, using desired dimensions and parametric equations to define a helix.&#160; With this method, accurate atomistic silica nanoribbons can be generated for a range of pitch values and dimensions.&#160; The second method involves a more robust code which allows flexibility in modeling nanohelical structures.&#160; This approach utilizes a C++ code particularly written to implement pre-screening methods as well as the mathematical equations for a helix, resulting in greater precision and efficiency when creating nanospring models.&#160; Using these codes, well-defined and scalable nanoribbons and nanosprings suited for atomistic simulations can be effectively created.&#160; An added value in both open-source codes is that they can be adapted to reproduce different helical structures, independent of material.&#160; In addition, a MATLAB graphical user interface (GUI) is used to enhance learning through visualization and interaction for a general user with the atomistic helical structures.&#160; One application of these methods is the recent study of nanohelices via MD simulations for mechanical energy harvesting purposes.

The atomistic nanoribbon models created with the first computational procedure (nanoribbons code) and their associated dimensions are shown in Figure 9. The resulting nanospring models using the second computational procedure (nanosprings code) and associated dimensions are shown in Figure 10.
<img alt="Figure 9" fo:content-width="5in" src="/files/ftp_upload/51372/51372fig9highres.jpg" width="500" /> 
Figure 9...

Watch this Scientific Journal Video about Scalable Nanohelices for Predictive Studies and Enhanced 3D Visualization at JoVE.com

Scalable Nanohelices for Predictive Studies and Enhanced 3D Visualization

Accurate modeling of nanohelical structures is important for predictive simulation studies leading to novel nanotechnology applications.&#160; Currently, software packages and codes are limited in creating atomistic helical models.&#160; We present two procedures designed to create atomistic nanohelical models for simulations, and a graphical interface to enhance research through visualization.

Spring-like materials are ubiquitous in nature and of interest in nanotechnology for energy harvesting, hydrogen storage, and biological sensing ...

scalable-nanohelices-for-predictive-studies-enhanced-3d

Research

JoVE Journal

Engineering

10.4K Views.  University of California Merced. Accurate modeling of nanohelical structures is important for predictive simulation studies leading to novel nanotechnology applications.  Currently, software packages and codes are limited in creating atomistic helical models.  We present two procedures designed to create atomistic nanohelical models for simulations, and a graphical interface to enhance research through visualization.

Video: Scalable Nanohelices for Predictive Studies and Enhanced 3D Visualization

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

Digital fringe projection (DFP) techniques provide dense 3D measurements of dynamically changing surfaces.&#160;Like the human eyes and brain, DFP uses triangulation between matching points in two views of the same scene at different angles to compute depth.&#160;However, unlike a stereo-based method, DFP uses a digital video projector to replace one of the cameras1. The projector rapidly projects a known sinusoidal pattern onto the subject, and the surface of the subject distorts these patterns in the camera&#8217;s field of view. Three distorted patterns (fringe images) from the camera can be used to compute the depth using triangulation.
Unlike other 3D measurement methods, DFP techniques lead to systems that tend to be faster, lower in equipment cost, more flexible, and easier to develop.&#160;DFP systems can also achieve the same measurement resolution as the camera.&#160;For this reason, DFP and other digital structured light techniques have recently been the focus of intense research (as summarized in1-5). Taking advantage of DFP, the graphics processing unit, and optimized algorithms, we have developed a system capable of 30&#160;Hz 3D video data acquisition, reconstruction, and display for over 300,000 measurement points per frame6,7.&#160;Binary defocusing DFP methods can achieve even greater speeds8.
Diverse applications can benefit from DFP techniques. Our collaborators have used our systems for facial function analysis9, facial animation10, cardiac mechanics studies11, and fluid surface measurements, but many other potential applications exist.&#160;This video will teach the fundamentals of DFP techniques and illustrate the design and operation of a binary defocusing DFP system.

This video describes the fundamentals of digital fringe projection techniques, which provide dense 3D measurements of dynamically changing surfaces.&#160;It also demonstrates the design and operation of a high-speed binary defocusing system based on these techniques.

Digital fringe projection (DFP) techniques provide dense 3D measurements of dynamically changing surfaces.&#160;Like the human eyes and brain, DFP uses ...

Fabrication, Operation and Flow Visualization in Surface-acoustic-wave-driven Acoustic-counterflow Microfluidics

Surface acoustic waves (SAWs) can be used to drive liquids in portable microfluidic chips via the acoustic counterflow phenomenon. In this video we present the fabrication protocol for a multilayered SAW acoustic counterflow device. The device is fabricated starting from a lithium niobate (LN) substrate onto which two interdigital transducers (IDTs) and appropriate markers are patterned. A polydimethylsiloxane (PDMS) channel cast on an SU8 master mold is finally bonded on the patterned substrate. Following the fabrication procedure, we show the techniques that allow the characterization and operation of the acoustic counterflow device in order to pump fluids through the PDMS channel grid. We finally present the procedure to visualize liquid flow in the channels. The protocol is used to show on-chip fluid pumping under different flow regimes such as laminar flow and more complicated dynamics characterized by vortices and particle accumulation domains.

In this video we first describe fabrication and operation procedures of a surface acoustic wave (SAW) acoustic counterflow device. We then demonstrate an experimental setup that allows for both qualitative flow visualization and quantitative analysis of complex flows within the SAW pumping device.

Surface acoustic waves (SAWs) can be used to drive liquids in portable microfluidic chips via the acoustic counterflow phenomenon. In this video we ...

Novel 3D/VR Interactive Environment for MD Simulations, Visualization and Analysis

The increasing development of computing (hardware and software) in the last decades has impacted scientific research in many fields including materials science, biology, chemistry and physics among many others. A new computational system for the accurate and fast simulation and 3D/VR visualization of nanostructures is presented here, using the open-source molecular dynamics (MD) computer program LAMMPS. This alternative computational method uses modern graphics processors, NVIDIA CUDA technology and specialized scientific codes to overcome processing speed barriers common to traditional computing methods. In conjunction with a virtual reality system used to model materials, this enhancement allows the addition of accelerated MD simulation capability. The motivation is to provide a novel research environment which simultaneously allows visualization, simulation, modeling and analysis. The research goal is to investigate the structure and properties of inorganic nanostructures (e.g., silica glass nanosprings) under different conditions using this innovative computational system. The work presented outlines a description of the 3D/VR Visualization System and basic components, an overview of important considerations such as the physical environment, details on the setup and use of the novel system, a general procedure for the accelerated MD enhancement, technical information, and relevant remarks. The impact of this work is the creation of a unique computational system combining nanoscale materials simulation, visualization and interactivity in a virtual environment, which is both a research and teaching instrument at UC Merced.

A new computational system featuring GPU-accelerated molecular dynamics simulation and 3D/VR visualization, analysis and manipulation of nanostructures has been implemented, representing a novel approach to advance materials research and promote innovative investigation and alternative methods to learn about material structures with dimensions invisible to the human eye.

The increasing development of computing (hardware and software) in the last decades has impacted scientific research in many fields including materials ...

Micro-masonry for 3D Additive Micromanufacturing

Transfer printing is a method to transfer solid micro/nanoscale materials (herein called &#8216;inks&#8217;) from a substrate where they are generated to a different substrate by utilizing elastomeric stamps. Transfer printing enables the integration of heterogeneous materials to fabricate unexampled structures or functional systems that are found in recent advanced devices such as flexible and stretchable solar cells and LED arrays. While transfer printing exhibits unique features in material assembly capability, the use of adhesive layers or the surface modification such as deposition of self-assembled monolayer (SAM) on substrates for enhancing printing processes hinders its wide adaptation in microassembly of microelectromechanical system (MEMS) structures and devices. To overcome this shortcoming, we developed an advanced mode of transfer printing which deterministically assembles individual microscale objects solely through controlling surface contact area without any surface alteration. The absence of an adhesive layer or other modification and the subsequent material bonding processes ensure not only mechanical bonding, but also thermal and electrical connection between assembled materials, which further opens various applications in adaptation in building unusual MEMS devices.

This paper introduces a 3D additive micromanufacturing strategy (termed &#8216;micro-masonry&#8217;) for the flexible fabrication of microelectromechanical system (MEMS) structures and devices. This approach involves transfer printing-based assembly of micro/nanoscale materials in conjunction with rapid thermal annealing-enabled material bonding techniques.

Transfer printing is a method to transfer solid micro/nanoscale materials (herein called &#8216;inks&#8217;) from a substrate where they are generated to ...

Surface Enhanced Raman Spectroscopy Detection of Biomolecules Using EBL Fabricated Nanostructured Substrates

Fabrication and characterization of conjugate nano-biological systems interfacing metallic nanostructures on solid supports with immobilized biomolecules is reported. The entire sequence of relevant experimental steps is described, involving the fabrication of nanostructured substrates using electron beam lithography, immobilization of biomolecules on the substrates, and their characterization utilizing surface-enhanced Raman spectroscopy (SERS). Three different designs of nano-biological systems are employed, including protein A, glucose binding protein, and a dopamine binding DNA aptamer. In the latter two cases, the binding of respective ligands, D-glucose and dopamine, is also included. The three kinds of biomolecules are immobilized on nanostructured substrates by different methods, and the results of SERS imaging are reported. The capabilities of SERS to detect vibrational modes from surface-immobilized proteins, as well as to capture the protein-ligand and aptamer-ligand binding are demonstrated. The results also illustrate the influence of the surface nanostructure geometry, biomolecules immobilization strategy, Raman activity of the molecules and presence or absence of the ligand binding on the SERS spectra acquired.

We describe the fabrication and characterization of nano-biological systems interfacing nanostructured substrates with immobilized proteins and aptamers. The relevant experimental steps involving lithographic fabrication of nanostructured substrates, bio-functionalization, and surface-enhanced Raman spectroscopy (SERS) characterization, are reported. SERS detection of surface-immobilized proteins, and probing of protein-ligand and aptamer-ligand binding is demonstrated.

Fabrication and characterization of conjugate nano-biological systems interfacing metallic nanostructures on solid supports with immobilized biomolecules ...

3D Printing of Biomolecular Models for Research and Pedagogy

The construction of physical three-dimensional (3D) models of biomolecules can uniquely contribute to the study of the structure-function relationship. 3D structures are most often perceived using the two-dimensional and exclusively visual medium of the computer screen. Converting digital 3D molecular data into real objects enables information to be perceived through an expanded range of human senses, including direct stereoscopic vision, touch, and interaction. Such tangible models facilitate new insights, enable hypothesis testing, and serve as psychological or sensory anchors for conceptual information about the functions of biomolecules. Recent advances in consumer 3D printing technology enable, for the first time, the cost-effective fabrication of high-quality and scientifically accurate models of biomolecules in a variety of molecular representations. However, the optimization of the virtual model and its printing parameters is difficult and time consuming without detailed guidance. Here, we provide a guide on the digital design and physical fabrication of biomolecule models for research and pedagogy using open source or low-cost software and low-cost 3D printers that use fused filament fabrication technology.

Physical models of biomolecules can facilitate an understanding of their structure-function for the researcher, aid in communication between researchers, and serve as an educational tool in pedagogical endeavors. Here, we provide detailed guidance for the 3D printing of accurate models of biomolecules using fused filament fabrication desktop 3D printers.

The construction of physical three-dimensional (3D) models of biomolecules can uniquely contribute to the study of the structure-function relationship. 3D ...

Scalable Solution-processed Fabrication Strategy for High-performance, Flexible, Transparent Electrodes with Embedded Metal Mesh

Here, the authors report the embedded metal-mesh transparent electrode (EMTE), a new transparent electrode (TE) with a metal mesh completely embedded in a polymer film. This paper also presents a low-cost, vacuum-free fabrication method for this novel TE; the approach combines lithography, electroplating, and imprint transfer (LEIT) processing. The embedded nature of the EMTEs offers many advantages, such as high surface smoothness, which is essential for organic electronic device production; superior mechanical stability during bending; favorable resistance to chemicals and moisture; and strong adhesion with plastic film. LEIT fabrication features an electroplating process for vacuum-free metal deposition and is favorable for industrial mass production. Furthermore, LEIT allows for the fabrication of metal mesh with a high aspect ratio (i.e., thickness to linewidth), significantly enhancing its electrical conductance without adversely losing optical transmittance. We demonstrate several prototypes of flexible EMTEs, with sheet resistances lower than 1 &#937;/sq and transmittances greater than 90%, resulting in very high figures of merit (FoM) &#8211; up to 1.5 x 104 &#8211; which are amongst the best values in the published literature.

This protocol describes a solution-based fabrication strategy for high-performance, flexible, transparent electrodes with fully-embedded, thick metal mesh. Flexible transparent electrodes fabricated by this process demonstrate among the highest reported performances, including ultra-low sheet resistance, high optical transmittance, mechanical stability under bending, strong substrate adhesion, surface smoothness, and environmental stability.

Here, the authors report the embedded metal-mesh transparent electrode (EMTE), a new transparent electrode (TE) with a metal mesh completely embedded in a ...

Scalable Quantum Integrated Circuits on Superconducting Two-Dimensional Electron Gas Platform

To form a coherent quantum transport in hybrid superconductor-semiconductor (S-Sm) junctions, the formation of a homogeneous and barrier-free interface between two different materials is necessary. The S-Sm junction with high interface transparency will then facilitate the observation of the induced hard superconducting gap, which is the key requirement to access the topological phases (TPs) and observation of exotic quasiparticles such as Majorana zero modes (MZM) in hybrid systems. A material platform that can support observation of TPs and allows the realization of complex and branched geometries is therefore highly demanding in quantum processing and computing science and technology. Here, we introduce a two-dimensional material system and study the proximity induced superconductivity in semiconducting two-dimensional electron gas (2DEG) that is the basis of a hybrid quantum integrated circuit (QIC). The 2DEG is a 30 nm thick In0.75Ga0.25As quantum well that is buried between two In0.75Al0.25As barriers in a heterostructure. Niobium (Nb) films are used as the superconducting electrodes to form Nb- In0.75Ga0.25As -Nb Josephson junctions (JJs) that are symmetric, planar and ballistic. Two different approaches were used to form the JJs and QICs. The long junctions were fabricated photolithographically, but e-beam lithography was used for short junctions&#8217; fabrication. The coherent quantum transport measurements as a function of temperature in the presence/absence of magnetic field B are discussed. In both device fabrication approaches, the proximity induced superconducting properties were observed in the In0.75Ga0.25As 2DEG. It was found that e-beam lithographically patterned JJs of shorter lengths result in observation of induced superconducting gap at much higher temperature ranges. The results that are reproducible and clean suggesting that the hybrid 2D JJs and QICs based on In0.75Ga0.25As quantum wells could be a promising material platform to realize the real complex and scalable electronic and photonic quantum circuitry and devices.

Quantum integrated circuits (QICs) consisting of array of planar and ballistic Josephson junctions (JJs) based on In0.75Ga0.25As two-dimensional electron gas (2DEG) is demonstrated. Two different methods for fabrication of the two-dimensional (2D) JJs and QICs are discussed followed by the demonstration of quantum transport measurements in sub-Kelvin temperatures.

To form a coherent quantum transport in hybrid superconductor-semiconductor (S-Sm) junctions, the formation of a homogeneous and barrier-free interface ...

Scalable Stamp Printing and Fabrication of Hemiwicking Surfaces

Hemiwicking is a process where a fluid wets a patterned surface beyond its normal wetting length due to a combination of capillary action and imbibition. This wetting phenomenon is important in many technical fields ranging from physiology to aerospace engineering. Currently, several different techniques exist for fabricating hemiwicking structures. These conventional methods, however, are often time consuming and are difficult to scale-up for large areas or are difficult to customize for specific, nonhomogeneous patterning geometries. The presented protocol provides researchers with a simple, scalable, and cost-effective method for fabricating micro-patterned hemiwicking surfaces. The method fabricates wicking structures through the use of stamp printing, polydimethylsiloxane (PDMS) molding, and thin-film surface coatings. The protocol is demonstrated for hemiwicking with ethanol on PDMS micropillar arrays coated with a 70 nm thick aluminum thin-film.

A simple protocol is provided for the fabrication of hemiwicking structures of varying sizes, shapes, and materials. The protocol uses a combination of physical stamping, PDMS molding, and thin-film surface modifications via common materials deposition techniques.

Hemiwicking is a process where a fluid wets a patterned surface beyond its normal wetting length due to a combination of capillary action and imbibition. ...

3D Printing - Evaluating Particle Emissions of a 3D Printing Pen

Three-dimensional (3D) printing as a type of additive manufacturing shows continuing increase in application and consumer popularity. The fused filament fabrication (FFF) is an inexpensive method used most frequently by consumers. Studies with 3D printers have shown that during the printing process particulate and volatile substances are released. Handheld 3D printing pens also use the FFF method but the consumer&#8217;s proximity to the 3D pens gives reason to higher exposure compared to a 3D printer. At the same time, 3D printing pens are often marketed for children who could be more sensitive to the printing emission. The aim of this study was to implement a low cost method to analyze the emissions of 3D printing pens. Polylactide (PLA) and acrylonitrile butadiene styrene (ABS) filaments of different colors were tested. In addition, filaments containing metal and carbon nanotubes (CNTs) were analyzed. An 18.5 L chamber and sampling close to the emission source was used to characterize emissions and concentrations near the breathing zone of the user.
Particle emissions and particle size distributions were measured and the potential release of metal particles and CNTs investigated. Particle number concentrations were found in a range of 105 - 106 particles/cm3, which is comparable to previous reports from 3D printers. Transmission electron microscopy (TEM) analysis showed nanoparticles of the different thermoplastic materials as well as of metal particles and CNTs. High contents of metal were observed by inductively coupled plasma mass spectrometry (ICP-MS).
These results call for a cautious use of 3D pens due to potential risk to the consumers.

This protocol presents a method to analyze the emission of 3D printing pens. Particle concentration and particle size distribution of the released particle is measured. Released particles are further analyzed with transmission electron microscopy (TEM). Metal content in filaments is quantified by inductively coupled plasma mass spectrometry (ICP-MS).

Three-dimensional (3D) printing as a type of additive manufacturing shows continuing increase in application and consumer popularity. The fused filament ...