I am a Senior Member of the Technical Staff in the Computational Materials Science and Engineering
Dept. (Org. 1814) at Sandia National
Laboratories. I earned my B.S. degree at the University of
Virginia, and my Ph.D. in Physics at the University of Texas
at Austin. Prior to joining Sandia, I was a postdoctoral
fellow at the Center for Nonlinear Dynamics at Texas.
My computational research interests are in nanoscale soft condensed matter and far-from-equilibrium systems. My approach to both is influenced heavily by my training in nonlinear dynamics. My work is grounded in fundamental physics, but is strongly motivated by applications in computational chemistry, materials science and engineering mechanics.
Using large-scale molecular dynamics (MD) simulation, I study solids and soft materials at atomic resolution. Massively-parallel MD simulation is a powerful methodology to probe complex structure and dynamics in systems which depend on atom-scale processes. MD simulations provide a more complete molecular-level understanding of phenomena than experiment alone. Additionally, when tied to theory and quantum calculations, MD simulations offer a clearer picture of the emergent phenomenon which arise from larger length scales and added complexity.
All of these applications
depend on dispersed nanoparticles which do not aggregate. In
colloidal systems where particles are much larger, aggregation can be
overcome by coating particles with short-chain polymers. This method
is often adopted to stabilize nanoparticle suspensions as well. But
we are learning that "small is different" in the case of nanoparticle
coatings, and much of my research focuses on characterizing these
differences.
By understanding the nanoscale soft material properties of nanoparticle coatings, we can tailor the shape and interactions between nanoparticles separately from the properties of the core particles. By controlling the interactions and morphology of individual nanoparticles, we can, in turn, control the collective properties and structures of nanoparticle assemblies.
The relevant length scales of these systems make molecular dynamics a good tool for investigation. Experimentally, it is difficult to manipulate and measure forces on individual nanoparticles smaller than ~100 nm. Theoretical treatments are challenging because the coatings are relatively short, while the particles themselves are outside the large radius of curvature limit. MD studies of nanoparticles and nanoscale soft matter are well suited to bridge the gap between theory and experiments.
Nanoparticles in solution are usually stabilized with functional
coatings. To prevent macroscopic aggregation, these coatings alter
the nanoscopic interactions of the particles, coatings and fluids.
The coating selection process is empirical in nature and too poorly
understood to allow a priori design of the rheological
properties of a nanoparticle suspension, such as phase separation,
viscosity and shear response. Moreover, recent studies have shown
that coatings on the smallest nanoparticles are asymmetric and show
complex responsive behavior to their environment.
My reseach in this area seeks to characterize how these functional coatings affect the interactions between nanoparticles and with the surrounding solvent. The image to the right illustrates how mesoscale forces between nanoparticles were measured, using a method which leverages our understanding of atom scale forces to quantify the mesoscale hydrodynamic, lubrication, and depletion forces.
In a recent paper, featured on the cover of Physical Review Letters we demonstrated that small spherical nanoparticles -- coated with a simple polymer -- produce highly asymmetric coating arrangements even when extremely uniform grafting arrangements and full coverages are employed. These results and others [A] have forced a rethinking of the limitations of, and opportunities provided by, highly anisotropic coatings on spherical nanoparticles.
[A] P.K. Ghorai & S.C. Glotzer, "Molecular dynamics simulation study of self-assembled monolayers of alkanethiol surfactants on spherical gold nanoparticles," J. Phys. Chem. C, 111, 15857 (2007).
Polymer nanocomposites have many promising applications, from
wear-resistant rubbers for tires, to conducting polymers films.
Compared to traditional filled polymers, it has been shown that the
introduction of a relatively low volume fraction of nanoparticles into
a polymer matrix has dramatic effects on the viscoelastic response of
polymer nanocomposites. To successfully exploit the enhancement in the
properties of this class of materials, it is critical to understand
how variations in nanoparticle size, shape, and interaction with the
matrix affect the properties of the resulting composite. Significant
computational effort has been put toward the investigation of the
properties of nanoparticle suspensions. However, with the exception of
carbon nanotube loaded polymer nanocomposites, most work has focused
on spherical or mildly aspherical nanoparticles.
The goal of our research in this area is to study systems of significance, for their dramatic effect on either rheology or function. An initial study of highly extended nanoparticles, which were jack shaped, showed orders of magnitude higher viscosity than compact spherical nanoparticles of the same mass. Even for low volume fractions, the jacks quickly become entangled, resulting in a very rapid increase in the viscosity and decrease in the diffusion.
The nanoscale behavior of water in contact with polymer-coated
surfaces is important for understanding and predicting responses in
many biological and engineering systems. The emerging fields of
nanofluidics, MEMS/NEMS devices, and nanofiltration demand an
understanding of water interacting in nanoscale pores or gaps, which
are often protected with self-assembled monolayers (SAMs) of
short-chain polymers. Thus, the details of the SAM-water interactions
are of significant interest both fundamentally and technologically.
Microelectromechanical systems (MEMS) hold the promise of low-cost reliable devices that are a fraction of the size of their current counterparts. Combining logic and actuation on the same chip is extremely desirable. However, the issues of in-use stiction and friction in silicon-based MEMS devices is an open problem when parts are in sliding contact. Alkylsilane coatings have been proven to reduce in-process stiction, adhesion and friction of silica surfaces. However, these coatings can be damaged when exposed to mechanical stress and humid environments.
In an article feaured on the cover of Langmuir, we investigated damaged SAMs exposed to water in order to determine the potential impact on these protective coatings. We found that SAM coatings that have been even slightly damaged are susceptible to water penetration and migration to the underlying hydrophilic substrate. However, we found that the presence of water tends to heal damage when the damaged regions are small, while for larger damage regions, it exploits and magnifies damage. In the context of MEMS protection, these findings predict strong implications for the aging and reliability of SAM coatings when water is present.
We investigated the behavior of water confined to subnanometer thicknesses between hydrophilic alkanethiol self-assembled monolayers (SAMs) on gold. Significant conflicts existed in the literature on the structure (ice vs. fluid) and viscosity response of water in confinement. Our principal finding was that water confined between hydrophilic SAMs retains fluidlike dynamics, even under pressure. However, we observe surface-induced ordering and significant suppression of diffusion.
As scientists, we often like to imagine that the world is in equilibrium. But many of the most interesting and critical problems are unstable, driven, or even chaotic. Such systems are best discussed in the language of nonlinear dynamics, in which common linear theory must be replaced with analyses of instability/bifurcation, scaling and spatio-temporal pattern formation. Molecular dynamics simulation, because it is intrinsically nonlinear, is a remarkably effective tool for studying complex far-from-equilibrium systems. As in experiment, the nonlinear physics simply emerges from the dynamics. In my research, I apply MD simulation to study the nonlinear problems of nucleation, fracture, and shock waves.
Our primary application will be to recent flyer-plate experiments on Z that have shown a gradual drop in wave speed near melt in beryllium. This response is not captured by continuum models. Finally, we will address strength and phase transformation behavior under ramp loading. The techniques we develop will allow us to contribute significantly to the understanding of shock and quasi-isentropic physics relevant to weapons and inertial-confinement fusion applications, as well as to substantially expand understanding of several current critical areas of material behavior.
In past work, I used massively-parallel non-equilibrium molecular dynamics simulation as a tool to investigate the fracture properties of vitreous silica. Silica (i.e. silicon dioxide) is a commonly occuring molecular solid found naturally in both crystalline and glassy states (e.g. quartz, pyrex, and window glass are primarily SiO$_2$). The random network silica glass was modelled using the Feuston-Garofalini interatomic potential and prepared with a melt-quench technique from the crystalline base state. The goal of this research was to investigate the fracture and mechanical properties of amphorphous solids. I found that the fracture was qualitatively different from brittle fracture in crystals, being characterized by the aggregation of voids, the branching of the crack tip even at low energy density, the pervasive bridging across the crack opening, strong rate-dependence of the loading, and frustrated dynamics often culminating in crack arrest.
Sandia leads the world in experimentally characterizing materials in extreme pressure and density regions of phase space using the Z machine's pulse electromagnetic ramp wave loading. Molecular dynamics simulation (MD) would be an invaluable tool for studying the atom-scale physics produced by the Z, such as structural transitions, non-equilibrium dynamics, and elastic-plastic deformation. There are, however, significant difficulties in utilizing MD for extreme environments. Atomic potentials -- the cornerstone of classical MD simulations -- are generally optimized for ambient material properties and therefore offer qualitatively accurate, but rarely quantitatively accurate results in multi-megabar and high-temperature regimes. In addition, the time scales required to study ramp loading are too long to be simulated with standard methods, for which computing expenditure scales like the time squared.
Before coming to Sandia, my dissertation work produced a new non-equilibrium molecular dynamics method, called the Continuous Hugoniot Method (CHM), which allows the detailed dynamics at a shock front to be calculated (without approximation) with dramatically increased efficiency. This method has allowed simulation of shock fronts using more computationally expensive material models and also allows a system to evolve along the shock Hugoniot curve in a single run. This direct evolution had long been thought to be impossible.
In 2009, I coauthored, with Aidan Thompson, a successful grant application for Lab Directed Research and Development funding. The grant provided funding for generalizing the ideas of CHM to enable MD modeling of high-pressure and high-temperature ramp compression dynamics. Further, we have developed new interatomic potentials specifically for extreme environments.
Experimental advances in femtosecond time-resolved optical and x-ray diffraction diagnostics are providing a new window into shock research, at length and time scales which are particularly well matched to those of computational molecular dynamics. By combining ultrafast precision experimental measurements with atomic-resolution simulation, there is potential to unveil new physics in the material response at these extreme conditions. Under shock loading, the intense uniaxial stresses, inertial confinement and material relaxation mechanisms together drive unique dynamics, such as shear stress driven solid-solid transitions, nonequilibrium melting and anomalous loss of strength prior to melting.
MD simulation is becoming an invaluable tool for study of the atom-scale physics produced by shock and quasi-isentropic loading in solids. We can now characterize shock-induced structural transitions, and non-equilibrium melting in semiconductors.
Semiconductors, such as germanium and silicon, are known to have slow dislocation dynamics compared to most metals. This slow material relaxation mechanism combined with fast shock loading makes these good target materials. Both germanium and silicon form a cubic diamond (cd) structure at low pressures and temperatures. At higher pressures, they transition to a body-centered tetragonal structure (bct).
We showed that near onset the shock-induced solid-solid phase
transition in germanium unexpectedly propagates in shear bands which
appear to nucleate from stacking faults, as seen in the image
above. This partial transition propagates diagonally, rather than in
the strain direction and appears to be driven by shear stress
relaxation.
Organic polymers are the basis of most plastics, lubricants, surfactants, and fuels; and they are key components in explosives, petrochemicals and many modern engineered materials such as gels and foams. As lipids, they form the cell membranes and other structures within living organisms.
Understanding the propagation of shock waves in organic materials
is important to applications ranging from fusion energy studies to the
directed dispersal of medicine to cells. My initial explorations in
this area have focused on compression of a low-density hydrocarbon
foam called TPX, which is a specialized target material for inertially
confined fusion (ICF) studies at Sandia National Labs. I have shown
that the ReaxFF MD potential is quantitatively accurate in predicting
shock compression at pressures up to 50 GPa and impact velocities up
to 5000 m/s.
We've recently showed that the response to weak shocks in both PE and PMP were well described by two of the classical interaction potentials. For strong shocks, only the DFT based simulations were of high fidelity when compared to existing experimental data up to 80 GPa. Based on the first-principles simulations, we predict a feature in the polyethylene Hugoniot at Up = 10 km / s due to gradual dissociation between 2.2 and 2.5 g / cm3.
[12] Lane, J. M. D. and Marder M. P. "Molecular dynamics of shock fronts and their transitions in Lennard-Jonesium and tin," (submitted, Phys. Rev. E).
[11] Lane, J. Matthew D., Gary S. Grest, "Spontaneous asymmetry of coated spherical nanoparticles in solution and at liquid/vapor interfaces," Phys. Rev. Lett., 104, 235501 (2010).
[Featured on Cover]
[Abstract]
[10] Petersen, Matt K., J. Matthew D. Lane, Gary S. Grest, "Shear rheology of extended nanoparticles," Phys. Rev. E, 82, 010201(R) (2010).
[Abstract]
[9] Lorenz, Christian D., Michael Chandross, J. Matthew D. Lane and Gary S. Grest, "Nanotribology of Water Confined between Hydrophilic Alkylsilane Self-Assembled Monolayers," Mod. Sim. in Mat. Sci. Eng., 18, 034055 (2010).
[Abstract]
[8] Mattsson, Thomas. R., J. Matthew D. Lane, Kyle R. Cochrane, Michael P. Desjarlais, Aidan P. Thompson, Gary S. Grest, "First-principles and classical molecular dynamics simulation of shocked polymers: polyethylene and poly(4-methyl-1-pentene)," Phys. Rev. E, 81, 054103 (2010).
[Abstract]
[7] Lane, J. Matthew D., Aidan Thompson, "Molecular dynamics simulation of shock-induced phase transition in germanium." Shock Compression of Condensed Matter. AIP Conference Procs, 1195, 1157 (2009).
[Abstract]
[6] Thompson, Aidan, J. Matthew D. Lane, Michael I. Baskes, Michael P. Desjarlais, "Molecular dynamics simulation of dynamic response of beryllium." Shock Compression of Condensed Matter. AIP Conference Procs, 1195, 833 (2009).
[Abstract]
[5] Lane, J. Matthew D., Ahmed E. Ismail, Michael Chandross, Christian D. Lorenz, Gary S. Grest, "Forces between functionalized silica nanoparticles in solution," Phys. Rev. E, 79, 050501(R) (2009).
[Abstract]
[4] Lorenz, Christian D., J. Matthew D. Lane, Michael Chandross, Mark J. Stevens, Gary S. Grest, "Molecular dynamics simulations of water confined between matched pairs of hydrophobic and hydrophilic self-assembled monolayers," Langmuir, 25, 4535 (2009).
[Abstract]
[3] Lane, J. Matthew D., Michael Chandross, Mark J. Stevens, Gary S. Grest, Christian D. Lorenz, "Water penetration of damaged self-assembled monolayers," Langmuir, 24, 5734 (2008).
[Featured on Cover]
[Abstract]
[2] Lane, J. Matthew D., Michael Chandross, Mark J. Stevens, Gary S. Grest, "Water in nano-confinement between hydrophilic self-assembled monolayers," Langmuir, 24, 5209 (2008).
[Abstract]
[1] Lane, J. M. D. and Marder, M. P. "Numerical Method for Shock Front Hugoniot States." Shock Compression of Condensed Matter. AIP Conference Procs, 845, 331-334 (2006).
[Abstract]
"Asymmetry of coated spherical nanoparticles in solution and at
liquid/vapor interfaces."
American Chemical Society (ACS) National Meeting, Anaheim, CA. (2011).
"Forces and asymmetry on polymer-coated nanoparticles in solution."
CINT User Conference, Sandia National Labs. (2010).
"Teaching with LAMMPS."
LAMMPS User Workshop, Sandia National Labs. (2010).
"Integrating Computational Materials Research and Education."
The Minerals, Metals & Materials Society (TMS) Annual Meeting. (2010).
"Coated nanoparticles in solvents and at interfaces."
IGERT: Integrating Nano, Cell Bio & Neuroscience, Univ. of New Mexico. (2010).
"Dynamics of water on self-assembled monolayers."
Center for Nonlinear Dynamics, University of Texas. (2007).
"Shock front dynamics in solids using the Continuous Hugoniot Method."
Gupta Group, Institute for Shock Physics, Washington State Univ. (2006).
"Shock front dynamics in solids using the Continuous Hugoniot Method."
Goddard Group, California Institute of Technology. (2006).
"Shock front dynamics in solids using the Continuous Hugoniot Method."
Grest Group, Sandia National Laboratories. (2006).
"Computational Dynamics: From shock waves in crystals to force chains in sand."
Niagara University. (2006).
"What is good teaching?"
Center for Teaching Effectiveness New TA Conference,
Univ. of Texas. (2002).
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