Plane Thermoelastic Waves in Infinite Half-Space Caused

FACTA UNIVERSITATIS

Series: Mechanical Engineering Vol. 14, N
o
3, 2016, pp. 269 - 280

DOI: 10.22190/FUME1603269T

Original scientific paper

ADHESION EFFECTS WITHIN THE HARD MATTER –

SOFT MATTER INTERFACE: MOLECULAR DYNAMICS

UDC 539.8

Alexey Tsukanov
1,2

, Sergey Psakhie
1,2

1
Institute of Strength Physics and Materials Science,

Siberian Branch of Russian Academy of Sciences, Tomsk, Russian Federation
2
Tomsk Polytechnic University, Tomsk, Russian Federation

Abstract. In the present study three soft matter – hard matter systems consisting of

different nanomaterials and organic molecules were studied using the steered molecular

dynamics approach in order to reveal regularities in the formation of organic-inorganic

hybrids and the stability of multimolecular complexes, as well as to analyze the energy

aspects of adhesion between bio-molecules and layered ceramics. The combined process free

energy estimation (COPFEE) procedure was used for quantitative and qualitative

assessment of the considered heterogeneous systems. Interaction of anionic and cationic

amino acids with the surface of a [Mg4Al2(OH)12
2+

2Cl
–
] layered double hydroxide (LDH)

nanosheet was considered. In both cases, strong adhesion was observed despite the

opposite signs of electric charge. The free energy of the aspartic amino acid anion,

which has two deprotonated carboxylic groups, was determined to be –45 kJ/mol for

adsorption on the LDH surface. For the cationic arginine, with only one carboxylic

group and a positive net charge, the energy of adsorption was –26 kJ/mol, which is

twice higher than that of chloride anion adsorption on the same cationic nanosheet.

This fact clearly demonstrates the capability of “soft matter” species to adjust

themselves and fit into the surface, minimizing energy of the system. The adsorption of

protonated histamine, having no carboxylic groups, on a boehmite nanosheet is also

energetically favorable, but the depth of free energy well is quite small at 3.6 kJ/mol. In

the adsorbed state the protonated amino-group of histamine plays the role of proton

donor, while the hydroxyl oxygens of the layered hydroxide have the role of proton

acceptor, which is unusual. The obtained results represent a small step towards further

understanding of the adhesion effects within the hard matter – soft matter contact zone.

Key Words: Adhesion, Interface, Soft Matter, Layered Hydroxide, Steered Molecular

Dynamics

Received September 15, 2016 / Accepted November 07, 2016

Corresponding author: Alexey A.Tsukanov

Institute of Strength Physics and Materials Science SB RAS, Tomsk, 634055, Russia

E-mail: a.a.tsukanov@yandex.ru

270 A. TSUKANOV, S. PSAKHIE

1. INTRODUCTION

In the last decades soft matter engineering has a very rapid development. The

importance of the soft matter extends to a wide range of applications in such fields as

materials science [1], energetics [2, 3], catalysis [4, 5], and pharmaceutics. It especially

stands for biomedicine since biological nano-objects (BNO) such as polypeptides,

proteins, bio-membranes as well as almost all biologically-active compounds (drugs,

genes, viruses, etc.) are soft-matter systems with flexible, non-uniform and multi-

functional surfaces [6, 7]. One of the main characteristics of the soft matter is its ability to

form high-level complicated functional nano-objects from comparatively simple building

blocks [8].

On the other hand, certain condensed materials such as naturally occurring layered

ceramics (LC), in particular cationic clays, layered double hydroxides (LDH) and metal

oxyhydroxides possess special properties such as large surface charge (which allows them

to act as host nanoparticles for ionic molecules), large specific surface area, low toxicity,

chemical inertness and biocompatibility, which makes them extremely promising in such

biomedical/nanomedical applications as drug and gene delivery [9-13]. In addition, low-

dimensional aluminum oxyhydroxide nanoparticles are amphoteric compounds with high

proton and hydroxyl buffer capacity [14], which can affect the ionic balance in the

cellular environment.

The use of LC in the role of hosting “nanocontainers” is explained by the fact that

almost all biologically-active molecules (including modified ones) may be intercalated in

between hydroxide nanolayers. There are two particularly important aspects in this

context: first, interaction effects within the hard matter – soft matter interface (HSI) between the

biologically-active compound (“guest”) and the layered hydroxide nanosheets (“host”)

determine the formation of (conditionally) stable organic-inorganic nanohybrids (NH); second,

the interaction between the inorganic outer surface of the nanohybrid and the cell

membrane determine the mechanism and efficiency of the cellular uptake of the NH.

Predicting behavior and interaction of hard matter and soft matter subsystems is a

challenge. To shed light on several effects which can rise within the hard matter – soft

matter interfacial region a series of steered molecular dynamics (SMD) simulations

utilizing all-atom models was conducted with different pairs of organic and inorganic

nanomaterials.

2. COMPUTATIONAL TECHNIQUE

2.1. Potential energy functional

To accurately compute any energies and forces of the studied thermodynamic system,

suitable potentials need to be selected. In the case of soft matter systems and systems

having covalent bonds, the most typical terms in the potential energy functional of the

bonded atoms are the bond stretching term, angle bending, Urey-Bradly 1-3 stretching

term, dihedral or torsional angle bending and improper rotation or inversions term (Fig.

1). Eq. (1) describes a typical form of potential energy functional with harmonic type of

the terms as it implemented in CHARMM [15]:

Adhesion Effects within Hard Matter – Soft Matter Interface: Molecular Dynamics 271

2 2 2

0 0 0

2 2

( ) ( ) ( )

(1 cos( )) ( )

b UB

bonds angles

unbonded

dihedrals impropers

U k b b k k s s

k n k U



 

 

   

        

     

 

 
(1)

where the unbounded terms such as Lennard-Jones potential and electrostatic interactions

are also included:

6 12

2
ij ij i j

unbonded ij

i j i jij ij ij

q q
U C

r r r 

      
       
         

  . (2)

The most famous all-atom force fields for soft matter systems are GROMACS [16],

AMBER [17], DREIDING [18], CHARMM, etc. The potentials for hard matter systems

are, e.g., EAM for solid metals [19, 20] and liquid metals [21, 22], CLAYFF for ceramics

[23], AIREBO and Tersoff for carbon nanostructures and other compounds [24-26] and

others. There is also a hybrid force field INTERFACE, which is suitable for heterogeneous

system modeling [27].

Fig. 1 Typical terms included in the potential energy functional

of Force Fields for bonded atoms

For bound atoms, special coefficients are often used reducing the Lennard-Jones and

Coulombic terms (so-called 1–2, 1–3, 1–4 special bonds). In addition, to facilitate

computations, a cutoff for pairwise interactions with a smoothly decreasing envelope-

function is used. So-called “full electrostatics” (long-range) is usually calculated with the

particle-particle particle-mesh (PPPM) [28, 29] or particle-mesh Ewald (PME) methods

[30, 31]. In the present study, the cutoff distance of 12 Å for pairwise interaction, with a

smooth decrease starting at 10 Å was utilized, as well as the PPPM method for “long-

range” Coulombic interactions with a relative accuracy of 0.001.

Molecular dynamics (MD) modeling of the layered ceramics nanostructures requires

not only unbounded terms but also an explicit treatment of the covalent bonds in hydroxyl

groups between oxygen and hydrogen atoms [23].

272 A. TSUKANOV, S. PSAKHIE

To parameterize all molecular systems considered in the present study, the following

force fields are used: CHARMM [15] for organic molecules, TIP3P [32] for water

molecules, as well as CLAYFF [23] for layered ceramics, with a simple modification

according to [33].

2.2. Free energy of adsorption

To quantify interactions between different parts of the system or the energy change

between two states of the system, free energy analysis is often very useful. In the present

study of interaction effects within the HSI region, the combined process free energy

estimation (COPFEE) procedure [34] was utilized, which is based on the potential of

mean force (PMF) analysis [35] for constant velocity steered MD. The central idea of the

COPFEE approach is a combination of two oppositely directed processes, which allows

us to reduce the dependence on the velocity of the pulling procedure and to estimate the

level of irreversible energy dissipation in comparison with the free energy change. Briefly, to

estimate the free energy of adsorption (of some molecule) consider the following

combination of two processes: a forward process – forced adsorption, in which an external

force is performing the work of translocating an adsorbate from “infinity” (actually some

point in the solvent, where the adsorbate is fully hydrated) onto the surface of the adsorbent

(Fig. 2); and then a reverse process – forced desorption, when the external force acts to

remove the adsorbed molecule/nanoparticle away from the adsorbent surface to any point in

the solvent that is equidistant with the initial point (Fig. 2). During both the processes the

work done by the external force is integrated, and two free energy profiles (PMF profiles

along reaction coordinate) are obtained as functions of z, in the direction perpendicular to

the adsorbent surface.

Fig. 2 Two stages of combined process free energy estimation procedure (COPFEE) for

an organic anion interacting with an LDH nanosheet: left – forced adsorption of

adsorbate on the adsorbent surface under the action of an external force, right –

forced desorption, the reverse process. During the steered MD simulation, the free

end of the abstract spring is moving with constant velocity in the respective

direction. Adsorbate colors: yellow – C, white – H, blue – N, red – carboxylic O.

Adsorbent colors: purple – Al, black – Mg, gray – hydroxylic O, white – H

Adhesion Effects within Hard Matter – Soft Matter Interface: Molecular Dynamics 273

As is known from thermodynamics, work Aext of the external force is spent on change

of Gibbs free energy G of the system (in case of an isothermal-isobaric ensemble) and on

entropy generation (if the process is not reversible):

ext

A G T S   . (3a)

Writing this for both the forward and reverse processes gives:

fwd fwd

ext ads

rvs rvs

ext ads

A G T S



  

  
(3b)

where T is known (and constant), both A
fwd

and A
rvs

are can be estimated from the SMD

simulations, and ∆G, δS
fwd

and δS
rvs

are unknown variables. Thus, there are three

unknown variables in the system (3b) and only 2 equations. To overcome this problem,

the following assumption can be made [34]: if the pulling velocities in both forward and

reverse processes are equal and sufficiently small, the entropy generation in both

processes should also be approximately equal:

fwd rvs

S S  . (3c)

The system (3b) becomes solvable with this assumption:

1 1

( ) ( ) ( )
2 2 2

fwd rvs fwd rvs fwd rvs

ads ext ext ext ext

T
G A A S S A A        (4a)

If the adsorption is energetically favorable, the external work in forward process A
fwd

negative (with a sufficiently small pulling velocity), while A
rvs

is positive and
fwd

ext

rvs

ext
AA  .

Thus, the free energy of adsorption can be simply estimated as minus the arithmetic mean

of the absolute values of the external work for the forward and reverse processes [34]:

fwd rvs

ext extads

COPFEE

A A
G


   . (4b)

3. RESULTS AND DISCUSSION

3.1. Organic anion adsorption on Mg4/Al2-LDH nanosheet

First we consider a combined adsorption-desorption constant velocity SMD process

for the aspartic amino acid anion (in zwitterionic state) on a [Mg4Al2(OH)12
2+

2Cl
–
]

layered double hydroxide nanosheet, which has a strong positive surface charge (about

0.7 C/m
2
) and exposes polar hydroxyl groups on its surface. The aspartic acid anion

(ASP) has two carboxylic groups with local negative charges on oxygen atoms. The total

charge of the ASP molecule is -1 e. It is convenient for further discourse to put the origin

of the coordinate system in the center of mass of the Mg4/Al2-LDH fragment and to orient

the z-axis perpendicular to the nanosheet plane.

The PMF profile (the cumulative work as a function of the distance between Mg4/Al2-

LDH nanosheet central plane and ASP center of mass) for the forward process obtained

with SMD with a constant pulling velocity v = 0.1 Å/ns is represented by the blue curve in

274 A. TSUKANOV, S. PSAKHIE

Fig. 3. Comparing the reverse process (Fig. 3, green line) it is immediately obvious that

the obtained curves are not equal, because of entropy generation during the irreversible

part of the process (Fig. 3, 5.6 < z < 6.4 Å). It is necessary to note that PMF profiles are

relative functions, which is why a zero level must be chosen for both the dependences.

Since we are interested in the free energy of adsorption, which is the difference of G

between some distant point in the bulk water solution and the point corresponding to the

nearest local minimum of PMF, it seems most convenient to choose the zero level at the

initial point (in the water) for both the curves.

The too fast perturbation (in comparison with thermal motions) of a single-molecule-

thick water layer on the adsorbent surface is the most probable reason for the observed

entropy generation .This could probably be mitigated with a lower velocity of the pulling

process during SMD simulation, while greatly increasing the computational cost of the

numerical experiment.

Fig. 3 Free energy of ASP amino acid anion adsorption on LDH using COPFEE method.

The profile has three local minima: M3 (6.5-7.0 Å) – adsorbate is separated from

LDH surface by a single-molecule-thick water layer, M2 (5.0-5.4 Å) – first

carboxylic group of ASP forms H-bonds with surface OH-groups, M1 (4.2-4.5 Å)

– both carboxylic groups of ASP contact with hydroxylic LDH surface –

completely adsorbed state. Color code is similar to the colors of Fig.2, except that

carbon atoms of the adsorbate are in cyan, and water (several molecules in contact

zone) in light blue. The rest of the water and other ions are not shown for clarity

Following the procedure described with the assumption Eq. (3c), we obtain an

estimate for the free energy of ASP acid anion adsorption on the Mg4/Al2-LDH surface of

–45 kJ/mol (minimum M1 in Fig.3). This is a very high value, indicating strong adhesion

within the hard matter. Such strong interaction energy within HSI allows the formation of

hybrid organic-inorganic multimolecular complexes, as was demonstrated in unbiased

(non-steered) molecular dynamics simulations [33].

Adhesion Effects within Hard Matter – Soft Matter Interface: Molecular Dynamics 275

The half-width of the “corridor” between forward and reverse PMF profiles is

∆ = ±6 kJ/mol, which provides a rough estimate of entropy generation during the forced

processes.

3.2. Arginine and chloride adsorption on cationic nanosheet

Free energy of adsorption of anionic molecules on an LDH nanosheet was considered

in the previous section as well as in other works [33, 34]. The behavior of cationic amino

acid residues such as arginine (ARG), lysine and protonated histidine at a cationic nanosheet

is also an important question since these also are typical building blocks of proteins and

polypeptides, and the possibility of adsorption is not obvious due to electrostatic repulsion.

Here the COPFEE procedure was applied to characterize the interaction of arginine amino

acid with a [Mg4Al2(OH)12
2+

2Cl
–
] nanosheet. The all-atom 3D structure of Mg4/Al2-LDH

nanosheet was built based on crystallographic data from [36] as in the previous case,

wherein the interlayer CO3
2–

anion was replaced by dissolved Cl
–
.

Fig. 4 Amino acid cation (arginine) adsorption on a cationic nanosheet of LDH in

comparison with an inorganic anion (chloride ion), using COPFEE method.

The gray curve corresponds to COPFEE result for chloride anion adsorption onto

the LDH nanosheet. Colors of atoms is similar to the colors of Fig.3, except for

carbon atoms of arginine, which are reddish, and chlorine, which is yellow

The obtained profile for ARG adsorption (Fig. 4, black curve) has a minimum M1 (6-

7 Å), in which the carboxylic group of ARG forms several hydrogen bonds with LDH

hydroxyl groups, while the positively charged amino group prefers to be located away from

the LDH surface (Fig.4). Carboxylic groups of ARG as well as those of ASP amino acid are

proton acceptors, while the surface hydroxyl-groups of LDH are proton donors. There is also

a plateau M2 (8-10 Å) on the free energy profile, where the arginine carboxylic group is

separated from the adsorbent by a one-molecule-thick water layer (Fig. 4, M2 inset).

276 A. TSUKANOV, S. PSAKHIE

Using the COPFEE procedure the surprisingly high estimation for free energy of

adsorption of –26 kJ/mol was obtained with the half-width of the forward-reverse PMF

corridor ∆ = ±3.5 kJ/mol. The result means that, despite the fact that ARG is a cation, its

adsorption onto the positively charged Mg4/Al2-LDH nanosheet is favorable. This result is

quite non-obvious, especially considering that arginine adsorption is even more favorable

than adsorption of the chloride anion (Fig.4, grey curve), which has a free energy of –12

kJ/mol (using COPFEE as well).

3.3. Adsorption of carboxyl-less cation on aluminum oxyhydroxide nanosheet

In both the previous cases, the considered organic ions had one (ARG) or two (ASP)

carboxylic groups, which are good terminals (especially in deprotonated state) for H-

bonding with the hydroxide surface of LDH. Thus, to understand the behavior of

carboxyl-less cationic molecules, a SMD simulation of protonated histamine interacting

with an aluminum oxyhydroxide (boehmite) nanosheet was additionally conducted.

The full-atom model of AlOOH was made using structural data from [37].

Oxyhydroxide model parametrization was performed in accordance with the CLAYFF

force field, but null Lennard-Jones parameters were replaced by r0 = 0.449 Å, ε = 0.046

kcal/mol [15, 33] to allow proper interactions with the CHARMM subsystem of the

model. The net charge of the AlOOH nanosheet is zero. However, its surface has positive

charge due to oriented hydroxylic groups with exposed protons outside.

In the all-atom histamine model, CHARMM-compatible parametrization was utilized,

using the SwissParam [38] web-service (http://www.swissparam.ch). Partial atomic

charges were obtained using self-consistent field (SCF) calculation in the NWChem

package [39] with Hartree-Fock basis HF/6-31G** [40, 41].

The histamine molecule in the protonated state has a charge of +1 e, which is

concentrated in the amino-group region, where the partial atomic charge of hydrogen

atoms in the amino-group is +0.390 e, while the nitrogen contributes –0.642 e.

Using the COPFEE procedure we obtain a value of –3.6 kJ/mol for the free energy of

adsorption of protonated histamine (pHST) on the AlOOH nanosheet (Fig. 5, black

curve). The depth of the free energy well is comparable to the kT level, which is about

2.5 kJ/mol at model temperature T = 310 K (p = 0.101 MPa.). The obtained result shows

that, despite electrostatic repulsion, the soft molecule can assume a suitable conformation

to allow hydrogen bonding and thus make the adsorbed state energetically favorable, but

not as stable as in previous cases. As can be seen in Fig.5, in the adsorbed state pHST is

oriented with its NH3
+
-group towards the boehmite nanosheet. Furthermore, the hydrogen

atoms of the boehmite OH-groups that are closest to pHST are pushed apart due to

Coulombic repulsion, and one of the NH3
+
-group protons found contact with hydroxyl

oxygens between the hydroxyl hydrogens of the AlOOH.

Using the COPFEE procedure we obtain a value of –3.6 kJ/mol for the free energy of

adsorption of protonated histamine (pHST) on the AlOOH nanosheet (Fig. 5, black

curve). The depth of the free energy well is comparable to the kT level, which is about

2.5 kJ/mol at model temperature T = 310 K (p = 0.101 MPa.). The obtained result shows

that, despite electrostatic repulsion, the soft molecule can assume a suitable conformation

to allow hydrogen bonding and thus make the adsorbed state energetically favorable, but

not as stable as in previous cases. As can be seen in Fig.5, in the adsorbed state pHST is

http://www.swissparam.ch/

Adhesion Effects within Hard Matter – Soft Matter Interface: Molecular Dynamics 277

oriented with its NH3
+
-group towards the boehmite nanosheet. Furthermore, the hydrogen

atoms of the boehmite OH-groups that are closest to pHST are pushed apart due to

Coulombic repulsion, and one of the NH3
+
-group protons found contact with hydroxyl

oxygens between the hydroxyl hydrogens of the AlOOH.

Fig. 5 Combined process for histamine (in protonated state) adsorption-desorption on an

aluminum oxyhydroxide nanosheet. Colors for atoms: aluminum – purple, bridging

oxygen – black, hydroxyl oxygen – grey, hydrogen – white, nitrogen – blue, carbon

– orange, chlorine – yellow. Water is not shown

Thus, the current case is unusual in that the adsorbed molecule is a proton donor,

while the hydroxyl oxygens of the nanosheet are proton acceptors, unlike the previous

cases.

4. CONCLUSION

In the present work, three different soft matter – hard matter couples of nanomaterials

are studied to reveal regularities in the nanohybrid formation and the stability of supermolecular

complexes, as well as to analyze the energy aspects of adhesion between bio-molecules

and layered metal hydroxides, which holds great promise in a wide range of biomedical

applications.

The conducted SMD study shows that anionic and cationic bio-molecules can form

(conditionally) stable nanocomplexes with positively charged layered hydroxide

nanosheets, even despite the electrostatic repulsion in the case of a cationic adsorbate.

Since both anionic and cationic amino acids (in zwitterionic state) are capable of being

adsorbed on the [Mg4Al2(OH)12
2+

2Cl
–
] surface, all 20 amino acids in zwitterionic state

could exhibit the same behavior. Comparing the free energy of adsorption of ASP, having

two carboxylic groups, and ARG with one carboxylic group onto [Mg4Al2(OH)12
2+

2Cl
–
]

surface, it may be concluded that each deprotonated carboxylic group adds about 20-

25 kJ/mol to the depth of the free energy well; however, the exact mechanism can be very

278 A. TSUKANOV, S. PSAKHIE

complicated, and many different aspects such as charge, shape, size, hydrophilicity and so

on must be taken into consideration.

Comparing the free energy profiles obtained for ARG and chlorine adsorption, it

seems that the flexibility of the molecule and non-uniform spatial distribution of the

electric charge on the molecule allow it to “sneak” in between the hydroxylic surface and

the surrounding water molecules, thus minimizing the energy of the system more

efficiently than the simple chlorine anion.

Looking at the interaction of pHST with the boehmite nanosheet, it can be concluded

that layered metal hydroxides can act not only as proton donors in hydrogen bonding but

also as proton acceptors. In this case, the depth of free energy well is much lower,

however. Moreover, in the case of a deprotonated surface hydroxyl group, the remaining

oxygen atom can be a stronger proton acceptor, which may produce strong adsorption

sites in defective zones, edges and cleavages.

As shown in the considered cases, the interactions within the interface of hard and soft

matter may be quite nontrivial, while playing a crucial role in the formation of hybrid

multimolecular nanocomplexes and in the modification of cellular environments via

selective adsorption of bio-molecules and ions, both of which is important in modern

nanomedical and biomedical applications.

Despite first steps in this direction, the interface between living and nonliving matter

remains a rich object for multidisciplinary investigation, including contact mechanics,

chemistry, biology, medicine and computational methods, especially molecular simulations.

All MD simulations are performed using the LAMMPS package (Sandia National

Laboratory, USA) [42] on the Lomonosov-1 cluster Supercomputing Center of Lomonosov

Moscow State University (MSU, Russia) [43]. VMD [44] and Avogadro [45] packages

are used in systems preparation and visualization.

Acknowledgements: The paper is a part of the research done within the Russian Science Foundation

Grant No. 14-23-00096. The work was supported by the Fundamental Research Program of the state

academies of sciences on 2013-2020 years. The authors would like to thank Mikhail Popov (Berlin

University of Technology, Germany) for useful ideas, discussions and help with the preparation of the

paper.

REFERENCES

1. Li, C., Strachan, A., 2011, Molecular dynamics predictions of thermal and mechanical properties of

thermoset polymer EPON862/DETDA, Polymer, 52(13), pp. 2920-2928.

2. Shamardina, O., Kulikovsky, A.A., Chertovich, A.V., Khokhlov, A.R., 2012, A Model for High-

Temperature PEM Fuel Cell: The Role of Transport in the Cathode Catalyst Layer, Fuel Cells, 12(4),

pp. 577-582.

3. Komarov, P.V., Khalatur, P.G., Khokhlov, A.R., 2013, Large-scale atomistic and quantum-mechanical

simulations of a Nafion membrane: Morphology, proton solvation and charge tra nsport, Beilstein

journal of nanotechnology, 4(1), pp. 567-587.

4. Chughtai, A.H., Ahmad, N., Younus, H.A., Laypkov, A., Verpoort, F., 2015, Metal–organic frameworks:

versatile heterogeneous catalysts for efficient catalytic organic transformations, Chemical Society Reviews,

44(19), pp. 6804-6849.

5. de Clippel, F., Dusselier, M., Van de Vyver, S., Peng, L., Jacobs, P.A., Sels, B.F., 2013, Tailoring nanohybrids

and nanocomposites for catalytic applications, Green Chemistry, 15(6), pp. 1398-1430.

Adhesion Effects within Hard Matter – Soft Matter Interface: Molecular Dynamics 279

6. Zeng, X., Li, S., 2012, A three dimensional soft matter cell model for mechanotransduction, Soft

Matter, 8(21), pp. 5765-5776.

7. Poon, W.C., Andelman, D. (eds.)., 2006, Soft condensed matter physics in molecular and cell biology,

CRC Press.

8. Cranford, S.W., Buehler, M.J., 2012, Biomateriomics, Vol. 165, Springer Science Business Media.

9. Li, L., Gu, W., Chen, J., Chen, W., Xu, Z.P., 2014, Co-delivery of siRNAs and anti-cancer drugs using

layered double hydroxide nanoparticles, Biomaterials, 35(10), pp. 3331-3339.

10. Jain, S., Datta, M., 2014, Montmorillonite-PLGA nanocomposites as an oral extended drug delivery

vehicle for venlafaxine hydrochloride, Applied Clay Science, 99, pp. 42-47.

11. Hu, H., Xiu, K.M., Xu, S.L., Yang, W.T., Xu, F.J., 2013, Functionalized layered double hydroxide

nanoparticles conjugated with disulfide-linked polycation brushes for advanced gene delivery,

Bioconjugate chemistry, 24(6), pp. 968-978.

12. Li, D., Zhang, Y.T., Yu, M., Guo, J., Chaudhary, D., Wang, C.C., 2013, Cancer therapy and fluorescence

imaging using the active release of doxorubicin from MSPs/Ni-LDH folate targeting nanoparticles,

Biomaterials, 34(32), pp. 7913-7922.

13. Jakubikova, B., Kovanda, F., 2010, Utilization of layered double hydroxides in medical applications,

Chem. List, 104, pp. 906-912.

14. Lozhkomoev, A.S., Kazantsev, S.O., Lerner, M.I., Psakhie, S.G., 2016, Acid-base and adsorption

properties of the AlOOH 2D nanostructures as factors for regulating parameters of model biological

solutions, Nanotechnologies in Russia, 11(7-8), pp. 506-511.

15. MacKerell, A.D., Jr., et al, 1998, All-atom Empirical Potential for Molecular Modeling and Dynamics

Studies of Proteins. J. Phys. Chem. B, 102, pp. 3586-3616.

16. Berendsen, H.J.C., van der Spoel, D., van Drunen, R., 1995, GROMACS: A Message-Passing Parallel

Molecular Dynamics Implementation, Comp. Phys. Comm., 91, pp. 43-56.

17. Pearlman, D.A., et al, 1995, AMBER, a Package of Computer Programs for Applying Molecular

Mechanics, Normal Mode Analysis, Molecular Dynamics and Free Energy Calculations to Simulate the

Structural and Energetic Properties of Molecules, Comp. Phys. Comm., 91, pp. 1-41.

18. Mayo, S.L., Olafson, B.D., Goddard, W.A., 1990, DREIDING: A Generic Force Field for Molecular

Simulations, J. Phys. Chem., 94, pp. 8897-8909.

19. Daw, M.S., Baskes, M.I., 1986, Semiemperical, Quantum Mechanical Calculation of Hydrogen

Embrittlement in Metals, Phys. Rev. Lett., 50, pp. 1285-1288.

20. Foiles, S.M., Baskes, M.I., Daw, M.S., 1986, Embedded-atom-method functions for the fcc metals Cu,

Ag, Au, Ni, Pd, Pt, and their alloys, Phys. Rev. B, 33, pp. 7983-7991.

21. Mendelev, M.I., Han, S., Srolovitz, D.J., Ackland, G.J., Sun, D.Y., Asta, M., 2003, Development of new

interatomic potentials appropriate for crystalline and liquid iron, Phil. Mag., 83, pp. 3977-3994.

22. Belashchenko, D.K., 2006, Application of the Embedded Atom Model to Liquid Metals: Liquid

Mercury, High Temperature, 44, pp. 675-686.

23. Cygan, R.T., Liang, J.-J., Kalinichev, A.G., 2004, Molecular Models of Hydroxide, Oxyhydroxide, and

Clay Phases and the Development of a General Force Field, J. Phys. Chem. B, 108, pp. 1255-1266.

24. Stuart S.J., Tutein A.B., Harrison J.A., 2000, A reactive potential for hydrocarbons with intermolecular

interactions, J. Chem. Phys., 112, 14, pp. 6472.

25. Tersoff J., 1988, Empirical Interatomic Potential for Carbon, With Application to Amorphous Carbon,

Phys. Rev. Lett., 61, pp. 2879-2882.

26. Prodanov N.V., Khomenko A.V., 2010, Computational investigation of the temperature influence on

the cleavage of a graphite surface, Surface Science, 604, 7-8, pp. 730–740.

27. Heinz, H., Lin, T.J., Kishore Mishra, R., Emami, F.S., 2013, Thermodynamically consistent force fields

for the assembly of inorganic, organic, and biological nanostructures: the INTERFACE force field ,

Langmuir, 29(6), pp. 1754-1765.

28. Hockney, R.W., Goel, S.P., Eastwood, J.W., 1973, A 10000 particle molecular dynamics model with

long range forces, Chemical Physics Letters, 21(3), pp. 589-591.

29. Hockney, R.W., Eastwood, J.W., 1988, Computer simulation using particles, CRC Press.

30. Ewald, P.P., 1921, Ewald summation, Ann. Phys, 369, pp. 253.

31. de Leeuw, S.W., Perram, J.W., Smith, E.R., 1980, Simulation of electrostatic systems in periodic

boundary conditions. I. Lattice sums and dielectric constants, In Proceedings of the Royal Society of

London A: Mathematical, Physical and Engineering Sciences, The Royal Society, 373, 1752, pp. 27-56.

32. Jorgensen, W.L., Chandrasekhar, J., Madura, J.D., Impey, R.W., Klein, M.L., 1983, Comparison of

simple potential functions for simulating liquid water, J. Chem. Phys., 79(2), pp. 926-935.

280 A. TSUKANOV, S. PSAKHIE

33. Tsukanov, A.A., Psakhie, S.G., 2016, Energy and structure of bonds in the interaction of organic

anions with layered double hydroxide nanosheets: A molecular dynamics study, Scientific reports, 6,

pp. 19986.

34. Tsukanov, A.A., Psakhie, S.G., 2016, Adsorption of charged protein residues on an inorganic nanosheet:

Computer simulation of LDH interaction with ion channel, In Physics of Cancer: Interdisciplinary Problems and

Clinical Applications (PC’16), AIP Publishing, 1760, 1, pp. 020066.

35. Izrailev, S., Stepaniants, S., Isralewitz, B., Kosztin, D., Lu, H., Molnar, F., ..., Schulten, K., 1999, Steered

molecular dynamics, In Computational molecular dynamics: challenges, methods, ideas. Springer Berlin

Heidelberg, pp. 39-65.

36. Arakcheeva, A.V., Pushcharovskii, D.Yu., Atencio, D., Lubman, G.U., 1996, Crystal structure and

comparative crystal chemistry of Al2Mg4(OH)12(CO3) 3H2O, a new mineral from the hydrotalcite -

manasseite group, Crystallography Reports, 41, pp. 972-981.

37. Noel, Y., Demichelis, R., Pascale, F., Ugliengo, P., Orlando, R., Dovesi, R., 2009, Ab initio quantum

mechanical study of γ-AlOOH boehmite: structure and vibrational spectrum, Physics and Chemistry of

Minerals, 36(1), pp. 47-59.

38. Zoete, V., Cuendet, M.A., Grosdidier, A. Michielin, O., 2011, SwissParam, a fast force field generation

tool for small organic molecules, J. Comput. Chem. 32, pp. 2359–2368.

39. Valiev, M., Bylaska, E.J., Govind, N., Kowalski, K., Straatsma, T.P., Van Dam, H.J., ... De Jong, W.A.,

2010, NWChem: a comprehensive and scalable open-source solution for large scale molecular

simulations, Computer Physics Communications, 181(9), pp. 1477-1489.

40. Krishnan, R., Binkley, J.S., Seeger, R. Pople, J.A., 1980, Self-consistent molecular orbital methods. XX.

A basis set for correlated wave functions, J. Chem. Phys. 72, pp. 650–655.

41. Hariharan P.C., Pople, J.A., 1973, Influence of Polarization Functions on MO Hydrogenation Energies,

Theor. Chim. Acta, 28, pp. 213–222.

42. Plimpton, S., 1995, Fast parallel algorithms for short-range molecular dynamics, J. Comp. Phys., 117,

pp. 1–19.

43. Sadovnichy, V., Tikhonravov, A., Voevodin, Vl. Opanasenko, V., 2013, “Lomonosov”: Supercomputing at

Moscow State University, In Contemporary High Performance Computing: From Petascale toward

Exascale (Chapman Hall/CRC Computational Science), Boca Raton, USA, CRC Press, pp. 283–307.

44. Humphrey, W., Dalke, A. Schulten, K., 1996, VMD - visual molecular dynamics, J. Molec. Graphics 14,

pp. 33–38.

45. Hanwell, M.D., Curtis, D.E., Lonie, D.C., Vandermeersch, T., Zurek, E., Hutchison, G.R., 2012, Avogadro: an

advanced semantic chemical editor, visualization, and analysis platform, Journal of cheminformatics, 4(1),

pp. 1.