Atomic-Scale 3D Local Hydration Structures Influenced by Water

Jul 9, 2018 - Atomic-scale local hydration measurements have been enabled by ultra-low noise 3D frequency-modulation atomic force microscopy. However ...
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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

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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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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.

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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]

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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.

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************************************************************************* 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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hydration layers increased, which leads to ambiguous hydration contrasts. These results / 31 ACS Paragon16 Plus Environment

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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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339 340

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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364 365

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

391

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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References

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