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Interfaces: Adsorption, Reactions, Films, Forces, Measurement Techniques, Charge Transfer, Electrochemistry, Electrocatalysis, Energy Production and Storage
Atomic-Scale 3D Local Hydration Structures Influenced by Water-Restricting Dimensions Kenichi Umeda, Kei Kobayashi, Taketoshi Minato, and Hirofumi Yamada Langmuir, Just Accepted Manuscript • DOI: 10.1021/acs.langmuir.8b01340 • Publication Date (Web): 09 Jul 2018 Downloaded from http://pubs.acs.org on July 24, 2018
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Atomic-Scale
3D
Local
2
Water-Restricting Dimensions
Hydration
Structures
Influenced
by
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Kenichi Umeda1,3,4, Kei Kobayashi1, Taketoshi Minato2, and Hirofumi Yamada1
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1
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Kyoto University, Katsura, Nishikyo, Kyoto 615-8510, Japan. 2
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Office of Society-Academia Collaboration for Innovation, Kyoto University, Katsura, Nishikyo, Kyoto 615-8510, Japan.
3
11 12
Department of Electronic Science and Engineering,
Department of Advanced Material Science, The University of Tokyo, 5-1-5, Kashiwanoha, Kashiwa, Chiba, 277-8561, Japan.
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Nano Life Science Institute, Institute for Frontier Science Initiative, Kanazawa University, Kakuma, Kanazawa, Ishikawa, 920-1192, Japan.
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Prof. Hirofumi Yamada (corresponding author)
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Department of Electronic Science and Engineering, Kyoto University
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E-mail:
[email protected] 18 19
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Hydration structures at solid–liquid interfaces mediate between the atomic-level
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surface structures and macroscopic functionalities in various physical, chemical,
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and biological processes. Atomic-scale local hydration measurements have been
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enabled by ultra-low noise 3D frequency-modulation atomic force microscopy.
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However, for their application to complicated surface structures, e.g., biomolecular
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devices, understanding the relationship between the hydration and surface
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structures is necessary. Herein, we present a systematic study based on the concept
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of the structural dimensionality, which is crucial in various scientific fields. We
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performed 3D measurements and molecular dynamics simulations with silicate
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surfaces that allow for zero, one, and two degrees of freedom to water molecules.
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Consequently, we found that the 3D hydration structures reflect the structural
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dimensions, and the hydration contrasts decrease with increasing dimension due to
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the enlarged water self-diffusion coefficient and increased embedded hydration
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layers. Our results provide guidelines for the analysis of complicated hydration
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structures, which will be exploited in extensive fields.
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INTRODUCTION
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Next-generation technology for the creation of sustainable energy requires the exploitations of
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various energy-efficient phenomena at the solid–liquid interfaces, such as electrochemical,1,2
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catalytic,3 and biological4,5 processes. To characterize such functionalities based on the surface
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structures,6,7 the concept of dimensionality is crucial across extensive fields, e.g., quantum
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mechanics,8 material science,9 and energy storage.2 Since local hydration structures mediate
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between the atomic-scale surface structures and macroscopic functional phenomena, the
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relationship between the lateral translational degrees of freedom (tDOF) afforded to water
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molecules by the surface structural dimension and the formation of hydration structures must be
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understood clearly. Although the interfacial hydration structures have already been studied
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extensively with X-ray/neutron reflectivity measurements,10,11 atomic resolution has not been
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achieved.
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Emerging high-resolution 3D frequency-modulation atomic force microscopy (FM-AFM) has
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been successful in elucidating the relationship between the physical properties and atomic-scale
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hydration structures.12-20 In previous studies,12,21 we established a fast and nondestructive
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observation protocol that could be applied to any uneven biological surfaces. We also revealed that,
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via exploiting a heterosurface, the lateral periodicities are reflected in the lateral periodicities of the
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hydration structures.12 Namely, the horizontal movements of the water molecules near the charged
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surface are restricted by electrostatic interactions and the surface corrugation, which are the origin
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of the hydration features observed with 3D FM-AFM. Therefore, we need to gain insight into the / 31Environment ACS Paragon 3Plus
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relationship between the local hydration structures and surface structural dimensions for the
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applications to functional devices. Understanding of the relationship is also important in terms of
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the imaging mechanisms of the atomic-scale contrast in the FM-AFM, not only in liquids but also in
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ambient conditions since the hydration structures have also been observed in both the
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environments.22,23
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We define the water-restricting dimensions in the following statements. On the 0D surface
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allowing zero tDOF, each water molecule near the surface is held in hollow sites in all lateral
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directions (Fig. 1a). On the 1D surface allowing one tDOF, water molecules can move freely along
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the groove structures but are relatively restricted along the transverse directions (Fig. 1b). On the
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2D surface allowing two tDOF, water molecules can move relatively freely in all lateral directions
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since the gaps between the surface protrusions are larger than water molecules (Fig. 1c). To discuss
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variation in hydration structures introduced by the differences in the surface structure, we studied
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three types of cleaved silicate surfaces having similar physical characteristics, albite (Alb,
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NaAlSi3O8)10,24,25 in the tectosilicate group, which has two cleavage planes on (001) and (010), and
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apophyllite-(KF) (Apo, KCa4Si8O20F·8H2O)26,27 in the phyllosilicate group. These surfaces allow
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water molecules to have different tDOF because of the peculiar configurations of silicate
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tetrahedrons (SiO4).
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These minerals are also important in geoscience. Since Alb is classified in the feldspar group,
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which is the most abundant in the earth's crust,25,28,29 the reactions with aqueous solutions
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significantly influence the chemical composition of our environment. Apo is an important material / 31Environment ACS Paragon 4Plus
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for the ion exchange process because it almost always occurs together with zeolites, especially in
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traprock environments.27
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METHODS
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FM-AFM Setup
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We used a customized commercial AFM head (Shimadzu: SPM-9600) with a home-built digital
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PXI controller (National Instruments: NI PXI-8196) based on a high-speed field-programmable gate
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array board (National Instruments: NI PXI-7833R) programmed by LabVIEW (National
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Instruments) and a home-built FM detector circuit.30 To achieve quantitative and reproducible force
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measurements in a liquid environment, we employed a photothermal excitation setup.31 We used a
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rectangular cantilever with a gold backside coating (Nanosensors: PPP-NCHAuD), whose nominal
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spring constant was 42 N/m. Those of the cantilevers used in the experiments for Alb (001), Alb
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(010), and Apo were determined to be 38, 36, and 36 N/m by Sader’s method,32 respectively. The
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resonance frequencies of the cantilevers were 127, 125, and 137 kHz in 100 mM KCl solutions,
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respectively. Immediately prior to each experiment, organic contaminations on the tip were
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removed by irradiating it using a UV-ozone cleaner (Filgen: UV253) for a few hours.
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The measurement was performed in 100 mM potassium chloride aqueous solutions (KCl, 99.5%
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purity, Wako Pure Chemical Industries, Ltd.) whose Debye length is 0.97 nm at 298 K. This reagent
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was used without further purification and any pH regulation. The aqueous solution was slightly
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acidified to a pH value of around 5.7 due to the dissolved CO2 gas. All the experiments are
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conducted in a temperature-regulated enclosure (Mitsubishi Electric Engineering Company, Ltd.:
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CN-40A), which can maintain a constant temperature of 298 ± 0.1 K and thus reduce the influence
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of the thermal drift by the AFM head.
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3D FM-AFM Measurement
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More detailed procedure is described in our previous study.12 Acquired 3D ∆f map images of the
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Alb (001), Alb (010), and Apo surfaces contain 6.97 × 6.80 × 1.35 nm3 (128 × 63 × 115 pixels),
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5.81 × 8.00 × 1.35 nm3 (128 × 26 × 115 pixels), and 6.97 × 5.39 × 1.35 nm3 (128 × 93 × 115 pixels)
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in XYZ, respectively. Each dataset was acquired by collecting 2D ZX ∆f map images with a tip
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velocity of about 50–60 nm/s (40–50 Hz) of the ramp signal, and the total acquisition time for Alb
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(001), Alb (010), and Apo were about 3.8, 1.5, and 4.2 minutes, respectively. The approach was
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immediately stopped when the frequency shift signal reached a predetermined threshold value, then
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the tip was retracted to the original position. We set the threshold value to be 1 kHz for all the
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surfaces. The retraction curves were skipped and only the data of the approach curves were acquired
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to reduce the image acquisition time. Because of our instrumental limitation, we did not increase the
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approach speed over 100 nm/s, but we did not observe a significant dependency of the hydration
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structures on the approach speed.
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Post-processing of 3D FM-AFM Data / 31Environment ACS Paragon 6Plus
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We established an automatic post-processing program that was developed in Visual Basic .NET
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(Microsoft), which is essential for the efficient analysis of the large-size 3D map data. First, the 3D
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∆f data were smoothed by using a spatial Gaussian filter with standard deviations of 0.045 nm (xy)
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and 0.012 nm (z), and the 3D force data were obtained by converting each 2D ∆f map to a 2D force
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map using Sader’s method.33 Since the background offset of the 1D curves in the 2D map contained
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fluctuations, they were smoothed using a lateral line-by-line Gaussian filter with a standard
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deviation of 1.23 nm before and after the conversion. Second, the resolution of the 3D data was
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increased to 512 × 496 × 345, 512 × 701 × 345, and 512 × 393 × 345 pixels, respectively, for Alb
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(001), Alb (010), and Apo using a Lanczos interpolation filter with a factor of 3 (Lanczos-3).34
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Finally, the Y scales and X shear angles were adjusted by the drift correction such that the lattice
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constants in the horizontal 2D maps match those in the literature (see Fig. S5 for the extent of the
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filtering).35,36 For the vertical 2D force maps, the boundaries between the pixels with data (blue
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regions) and without data (green regions) were interpolated using Lanczos-3.
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For the creation of the Fourier-filtered images in Fig. 2, an automatic program was used to avoid
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a biased image processing. Namely, after a fast Fourier transform (FFT) processing, all the
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components lower than 2% of the maximum magnitude were set to zero in the frequency domain,
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followed by an inverse FFT processing.
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MD Simulations
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We obtained the crystal structures of Alb and Apo from the American Mineralogist Crystal Structure
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Database.35,36 We constructed (3 × 2), (3 × 3), and (3 × 3) crystal supercells which produced the
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surface dimensions (relevant cell angles) of 2.44 × 2.56 nm2 (γ = 87.7°), 2.15 × 2.42 nm2 (γ = 64.2°),
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and 2.70 × 2.70 nm2 (γ = 90.0°) for the Alb (001), Alb (010), and Apo surfaces, respectively (Fig.
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S1). Thicknesses of the crystals were 2 unit cells for the Alb (001) and Alb (010) surfaces and 1 unit
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cell for Apo. On the directions normal to the surfaces, we introduced water slabs approximately 3
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nm thick, which contains 800–1000 water molecules. In line with earlier experimental10,29,37 and
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theoretical38 studies, all the dangling (non-bridging) oxygens were terminated by hydrogens to form
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the silanol/aluminol groups. For the Alb (001) and Alb (010) surfaces, counter sodium ions were
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initially placed in the cavities of the tetrahedral groups to neutralize the surface negative charges.
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The metal-OH angles and non-bonded parameters in hydroxyl group were set to approximately 122
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degrees which was determined by ab initio calculation for the silanol group on silica.39
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MD simulations were performed using Forcite (Dassault Systèmes BIOVIA)40 under constant
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NVT conditions at 298K using a Nosé–Hoover scheme and a time step of 1 fs. Along all the
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dimensions, periodic boundary conditions were employed. All the interactions (bonded and
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non-bonded forces) between the atoms and electric charges were described by the CLAYFF force
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field41 with the flexible SPC/E water model42 except for the silanol/aluminol groups. To maintain
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the original crystal structures, all the atoms of the surfaces were treated as rigid using the RATTLE
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algorithm.43 After water equilibration for 100 ps, the production MD runs were performed for
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approximately 90 ns. The creations of the time-averaged maps and the computations of the water
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self-diffusion coefficients were carried out from the consecutive trajectory files using a home-built
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Perl conversion script and a Visual Basic .NET program. The zero-point distances were defined as
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the average heights of the outermost oxygens at the bottom of the hollow sites on each surface. The
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3D water density maps were created after smoothing the time-averaged 3D trajectory data using a
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Gaussian kernel filter with a standard deviation of 0.037 nm.
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All the cavities are occupied by the sodium ions for Alb (001), while only half the cavities are
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occupied by the sodium ions for Alb (010). During the course of the simulation, any desorption of
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the ions from the cavity sites was not observed. We confirmed that replacing the sodium ions by
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potassium ions does not significantly change the conclusions.
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RESULTS AND DISCUSSION
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Definitions of Water-Restricting Dimensions
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Figures 1d–f show the crystal structures of the cleaved Alb (001), Alb (010), and Apo surfaces,
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respectively, all of which have negative charges being neutralized by adsorbed protons and cations
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in a solution (Method section describes the details, and Movies S1 and S2 represent 3D crystal
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structures). The adsorbed water molecules are restricted in hollow sites formed by the upward SiO4
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tetrahedrons. Alb (001) has hollow sites having off-centered deeper cavities, all of which are
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occupied by adsorbed cations one by one in solution (Fig. S2 shows detail schematics). This
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anisotropy makes the surface symmetric line along the [100]38 indicated by the purple lines in Fig.
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1d. Alb (010) has hollow sites each of which are continuously connected to neighboring sites, thus
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forming a 1D groove-like structure along the [100] direction (the purple lines in Fig. 1e). Apo has
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large square-arranged hollow sites, resembling a quasi-2D (Q-2D) structure in which water
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molecules have two tDOF, shown in Fig. 1f, which makes the water self-diffusion coefficient (Dw)
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larger than the other surfaces (Fig. S4). We refer to the Apo surface as Q-2D because its structure is
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not a perfectly flat surface such as graphite.6 Although the 0D and 1D surfaces could also be
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classified into the Q-2D surface, we distinguish them because each hollow site of the 0D and 1D
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surfaces holds only single water molecule. In addition, tDOF of the Q-2D surface increases with
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enlarging hollow size.
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Our experiments were conducted in 100 mM KCl solutions for all the surfaces primarily because
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it has been well tested for the high-resolution 3D FM-AFM measurements. Another technical reason
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is that a high concentration of counter ion is required for the MD simulation to minimize the
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simulation time and accurately handle the molecular behaviors. In Fig. 1g,h, atomically resolved
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constant frequency shift (∆ƒ) images of Alb (001) and Alb (010) show clear dot-like
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quasi-hexagonal lattice and zigzag stripe-like patterns,24 respectively; thus they reflect the
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individual structural dimensions. The periodicities of the bright contrasts were 0.7−0.8 nm in both
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the cases (marked by blue circles and zigzag lines). Meanwhile, the Apo surface showed a relatively
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ambiguous atomically resolved image with a square lattice whose periodicity was 0.9 nm (see blue
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circle in Fig.1i). Since these images were acquired with relatively small ∆f being comparable with / 31 ACS Paragon10 Plus Environment
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the 2nd peak maxima, they do not represent the real surface but some of the higher hydration
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structures (see the overlaid real surface structures in Figs. 1g–i).
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3D Force Map Experiments and MD Simulations
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Although the simple constant ∆f mode successfully revealed the dimensional difference, their
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images may represent several hydration layers at the same time, thus preventing quantitative
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discussion regarding tDOF. As such, we performed 3D force map measurements, which showed
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atomically resolved complicated hydration structures in Fig. 2 (Movie S3). To validate these
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experimental results, we simulated water density distributions using molecular dynamics (MD)
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simulation. Several previous studies have often relied on the apparent similarities between the
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observed force and simulated water density distributions.12,15-20,44 However, to realize more
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quantitative comparisons, we converted them to force data using a solvent tip approximation
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model.45 We defined the hydration layers as the 1stL, 1stH, and 2nd layers based on simulated force
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profiles averaged laterally over the entire surfaces (as will be shown later in Figs. 4b,d,f). Note that
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the 1stL and 1stH layers belong to the same peak but are observed as different subpeaks.
209 210
************************************************************************* Atomic-Resolution Hydration Layers
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First, we compared the horizontal (constant height) force maps reconstructed near the apparent
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surfaces, which were defined as contour planes of the threshold values and presumably reflect some
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hydration layers. On the 0D and 1D surfaces, both the experimental/simulated results presented in / 31 ACS Paragon11 Plus Environment
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Fig. 3a,b, show clear hexagonal-lattice dot-like atomically resolved images, but only the 1D surface
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shows a slightly stripe-like contrast along the [001] direction, reflecting the tetrahedral
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anisotropies.24 However, the Q-2D surface did not show such hexagonal-lattice in Fig. 3c but
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dot-like square lattices with a relatively small periodicity of ~0.4 nm, implying that each of them
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correspond to a single water molecule, because several water molecules can be held in each hollow
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site (Fig. S2).
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Meanwhile, in both the experimental/simulated results, the apparent innermost layers, which
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were defined as the first hydration layers above the apparent surfaces, on the 0D and 1D surfaces in
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Fig. 3d,e exhibit honeycomb-like and groove-like structures, respectively, which indicates that the
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hydration structures reflect the expected tDOF. Concurrently, the result on the Q-2D surface
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presented in Fig. 3f exhibit relatively ambiguous atomically resolved images having a square lattice
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that repeats at intervals of 0.9 nm; thus reflecting the hollow structures that are much larger than the
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water molecules. These results show that the apparent innermost layers (Fig. 3d,e,f) effectively
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reflect the structural dimensions of the crystals whereas the apparent surfaces (Fig. 3a,b,c) always
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appears with discrete dot-like structures for all the dimensions. Some adsorbates do appear on the
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surfaces in Figs. 3b,c,e,f (marked with orange arrows), which are presumably organic contaminants
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(Supplementary Note 4) and demonstrate the true atomic-resolution imaging.
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************************************************************************* Comparison of Dot-Like Hydration Structures Second, we compared the vertical force maps which are reconstructed along the atomic rows / 31 ACS Paragon12 Plus Environment
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indicated by the red broken lines in Fig. 3 and laterally averaged force profiles. We aligned the
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profiles to match the vertical positions of the experimental/simulated peaks. On the 0D surface, both
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the experimental/simulated results in Fig. 4a distinctly reveal elongated dot-like hydration structure
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that are tilted slightly in the horizontal direction so that they reflect the surface anisotropy. MD
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simulation revealed that these elongated broad hydration structures comprise continuous dots of the
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1st–2nd layers. The averaged profiles in Fig. 4b showed the broad 1st peaks in both the
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experiment/simulation, but the 2nd peak is barely seen in the experiment because the attractive
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background force canceled it out. The range of the experimentally measured hydration interaction is
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shorter than those measured by conventional nanomechanical tools because of an atomically
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sharpened tip, which can avoid the influence of a macroscopic confinement effect.46,47 On the 1D
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surface, as shown in Fig. 4c, along the 1D groove direction, the apparent surface exhibit
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corrugations reflecting the 1stH hydration layers while the 2nd layers show laterally continuous
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structures. Across the 1D groove direction, a checkerboard-like hydration structure appeared
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(Supplementary Note 3). The averaged profiles in Fig. 4d show shoulder-like 1stH hydration peaks
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in both the experiment/simulation. On the Q-2D surface, the experimental data in Fig. 4e show an
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ambiguous arch-shaped 2nd hydration layer, whose feature was also reproduced in the simulated
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data. In the averaged profiles shown in Figs. 4f, a fairly broad 3rd layer can be seen in both the
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experimental/simulated results. However, the experimental 2nd layer shows a shoulder-like peak
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whereas the simulated result shows an oscillatory peak. This inconsistency originates from not
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considering the atoms other than the apex atom of the tip in the simulation, as elaborated later. Note / 31 ACS Paragon13 Plus Environment
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that the force orders as well as the overall features show good agreement between the
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experiments/simulations on all the surfaces despite its simple approximation, which validates these
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analyses.
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************************************************************************* Comparison of Hydration Forces
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The experimental vertical maps presented in Fig. 4a,c,e suggest that the hydration structures
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become ambiguous with increasing tDOF, but this tendency is not obvious in the simulations. To
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understand this inconsistency, we compare their profiles in detail. For the magnitude of the
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oscillatory force corresponding to the apparent innermost layers shown in Fig. 4b,d,f, the
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experimental (simulated) values are gradually decreased with increasing tDOF, i.e., 76 (130), 35
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(60), and 35 (44) pN for 0D, 1D, and Q-2D, respectively (marked with the green arrows). In the
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solvation measurements in organic solvents, the solvation force decreases with the reducing
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viscosity and increasing self-diffusion coefficient48. As we discussed in a previous study12, this
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tendency seems to be true even in aqueous solutions because it is empirically considered that the
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hydration structures are more easily observed in solutions than water, which can be explained by Dw
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reduced by ions. In Fig. S4, Dw near the surface slightly increases with increasing tDOF, which
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could be one cause of the weakening of the hydration force. However, this may not be the main
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cause because the significant difference cannot been seen between the 0D and 1D structures (Figs.
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S4a and S4c)
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Since both the experimental/simulated results showed the same tendency, the above-mentioned / 31 ACS Paragon14 Plus Environment
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inconsistency originates from different reason. Then, we noticed that the thicknesses of the
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hydrations layers, which were not experimentally observed, become larger with increasing tDOF
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(see the green boxes). From the water density profiles (Fig. S3d,h,l), these missing hydration
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maxima are smaller than the bulk density, which means that they originate from the water molecules
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embedded in the hollow sites. To observe these missing peaks, we further increased the threshold
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value up to 1.6 kHz, but the tip change prevented the consecutive acquisition of the force curves,
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implying that their experimental force maxima would be much larger than their simulated values.
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This discrepancy is because, since the tip has a finite curvature radius, when the tip approaching, all
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the tip apex atoms interact with the hydration layers and confines them to the hollow sites, which
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produces the strong repulsive force. Namely, the thicknesses of the inaccessible hydration layers
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reflect the hollow depths of the individual surfaces. With the increasing dimension, the thicknesses
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of the inaccessible embedded hydration layers increase (Fig. 5), and consequently, the
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experimentally observed hydration layer shifts to outer layer having lower Dw, which is the main
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cause of hydration weakening. When the hollow size becomes sufficiently larger than the water size,
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the embedded hydration layers would be measured.
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Our findings provide guidance for prediction and analysis of the formation of hydration
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structures on complicated biological molecules. Several preliminary experiments have shown the
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hydration structures reflecting the secondary structures (i.e., alpha helices and beta sheets) of
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proteins49,50 and nucleic acids51 rather than the small constituent units of the amino acid groups
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(other investigations are in progress).
Our results have shown that the hydration structures on
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biological surfaces as well as inorganic surfaces can be predicted from the size and dimensions of
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the molecular morphologies using the obtained knowledge and its analysis can be effectively
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facilitated.
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But we also noticed that their contrasts are much less pronounced than those in this study,
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possibly because the periodicity of the molecular corrugation is much larger than the water size.
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Therefore, for future applications to imaging such complicated structures, a method for enhancing
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the hydration contrast is required, e.g., increasing the signal-to-ratio of the system,44 increasing the
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electrolytic strength, and reducing the environmental temperature to suppress Dw and the molecular
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fluctuations.
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*************************************************************************
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CONCLUSIONS
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In this study, we systematically investigated the relationship between the formation of the
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hydration structures and tDOF afforded to water molecules by surface structural dimensions via
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ultra-low noise 3D FM-AFM experiments and MD simulations. For surface structures allowing zero,
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one, and two tDOF, we prepared samples from cleaved silicate surfaces of Alb (001), Alb (010), and
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Apo, respectively, which have different tetrahedral arrangements. We found that the apparent
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innermost layers reflect the surface dimensions, i.e., honeycomb-like, groove-like, and ambiguous
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square-lattice hydration structures, while the apparent surfaces always present laterally discrete
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dot-like structures for all the dimensions. With increasing tDOF, Dw decreases and embedded
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demonstrate that the crystal structure’s restrictions on tDOF for water molecules significantly affect
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vertical as well as horizontal hydration structures. These results will advance basic research in
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determining the relationship between atomic-level biomolecular structures and biofunctions that are
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mediated by local hydration structures.
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Fig. 1 Structures of different lateral water-restricting dimensions. (a–c) Schematics of
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the surface structures that restrict water molecules to 0D (a), 1D (b), and Q-2D (c). (d–f) Surface
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crystal structures of albite (001) (d), albite (010) (e), and apophyllite (f) surfaces, which were
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visualized by the crystallographic software VESTA.52 Yellow and green tetrahedrons indicate the
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downward and upward tetrahedral silicates, respectively. (g–i) Drift-corrected atomically resolved
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images of 0D (g), 1D (h), and Q-2D (i) surfaces acquired with constant frequency shift of 50−100
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Hz, where the insets show the magnified images. Scale bars, 2 nm (g–i).
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Fig. 2 Overview of 3D-FM-AFM results. (a–c) Representations of 3D-force map of 0D (a), 1D
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(b), and Q-2D (c). The blue arrows indicate the vertical positions of the apparent innermost
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hydration layers. The bottom faces show reconstructed constant frequency shift images of 50−100
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Hz, which are obtained at the height where the blue arrows indicate. They correspond to the
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contours of the 2nd–3rd hydration layer forces, which are almost the same height as those in Fig 1.
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Fig. 3 Comparison of atomically resolved images. (a–f) Experimental (left panels) and
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simulated (right panels) horizontal 2D force maps of the apparent surface (a–c) and apparent
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innermost layer (d–f) layers, and top-view crystal structures (lower right panels) (d–f) of the 0D
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(a,d), 1D (b,e), and Q-2D (c,f) surfaces. The insets enclosed by the purple lines show
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Fourier-filtered images. The red, green, and orange broken lines show the positions at which the
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vertical 2D force maps in Fig. 4, S5, and S6 were reconstructed, respectively. The orange arrows
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indicate the organic adsorbate sites. In the crystal structures, green and yellow triangles indicate
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upward and downward tetrahedral silicates, respectively. Scale bars, 1 nm (a–f).
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Fig. 4 Comparison of dot-like hydration structures. (a–f) Experimental (left panels) and
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simulated (right panels) vertical 2D force maps reconstructed along the red broken lines marked in
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Fig. 3 (a,d,g); and experimental (upper panels) and simulated (lower panels) force profiles laterally
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averaged over the whole surfaces at 40 randomly selected pixels (c,f,i) of the 0D (a–d), 1D (e–h),
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and Q-2D (i–I) surfaces. In the 2D maps in (a,d,g), the force maxima enclosed by the red broken
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curves indicate the characteristic shapes of the hydration structures, i.e., dots, lines, and arches.
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Note that density peaks are shifted to further away from the surface by approximately quarter of the
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diameter of the water molecule than the force peaks, but the main contrast features are not changed.
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In the force profiles, the green boxes show the inaccessible hydration regions. Scale bars, 0.3 nm
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(a,d,g).
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Fig. 5 Schematics of hydration structure dependence on surface structure. (a,b)
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Hydration structures formed on surfaces with small (a) and large (b) dimension (or periodicities)
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compared to the diameter of the water molecule. The real surface indicates the positions of the
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centers of the outermost oxygens.
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ASSOCIATED CONTENT
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Supporting Information
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Figure S1: Snapshots from the MD simulations; Figure S2: Schematics of hydration layers; Figure
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S3: Simulated water densities; Figure S4: Water self-diffusion coefficients; Figure S5: Comparison
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of 3D data before/after filtering; Figure S6: Photographs of phyllosilicate minerals; Figure S7: XPS
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spectra of albite; Figure S8: XPS spectra of apophyllite; Figure S9: Topographic images of cleaved
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samples; Figure S10: Comparison of dot-like hydration structures along green lines; Figure S11:
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Cross-sectional force map on an adsorbate; Table S1: Analysis of XPS spectra; Movie S1: Crystal
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structures of albite surfaces; Movie S2: Crystal structure of apophyllite surface; Movie S3: Full
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3D-force map result obtained by 3D FM-AFM.
387 388 389 390
Conflicts of interest
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There are no conflicts of interest to declare.
392 393 394 395
Acknowledgements
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This work was supported by KAKENHI, Japan Society for the Promotion of Science (Grant No.
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24221008, 25286057, 15K17467, and 16J01165); Foundation Advanced Technology Institute; the
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Murata Science Foundation; and Nanotech Career-up Alliance. The computer resources for the MD
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simulation were provided by SuperComputer System, Institute for Chemical Research, Kyoto
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University.
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