Hydrogen Bond Networks in Binary Mixtures of Water and Organic

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B: Liquids, Chemical and Dynamical Processes in Solution, Spectroscopy in Solution

Hydrogen Bond Networks in Binary Mixtures of Water and Organic Solvent Simon Stehle, and Andreas Siegfried Braeuer J. Phys. Chem. B, Just Accepted Manuscript • DOI: 10.1021/acs.jpcb.9b02829 • Publication Date (Web): 02 May 2019 Downloaded from http://pubs.acs.org on May 2, 2019

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The Journal of Physical Chemistry

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Hydrogen Bond Networks in Binary Mixtures of

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Water and Organic Solvent

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Simon Stehle‡,§ and Andreas Siegfried Braeuer‡,*

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‡

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Institute of Thermal-, Environmental- and Resources‘ Process Engineering (ITUN), Technische Universität Bergakademie Freiberg (TUBAF), Leipziger Strasse 28, 09599 Freiberg, Germany

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§

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Universitaet Erlangen-Nuernberg (FAU), Paul-Gordan-Straße 6, 91052 Erlangen, Germany

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*[email protected]

Erlangen Graduate School in Advanced Optical Technologies (SAOT), Friedrich-Alexander-

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ABSTRACT. We here present an approach for the optical in situ characterization of hydrogen

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bond networks in binary mixtures of water and organic solvent, such as methanol, ethanol and

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acetonitrile. Hydrogen bond networks are characterized based on (i) the analysis of experimental

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molar Raman spectra of the mixture, (ii) partial molar Raman spectra of the mixture constituents

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and (iii) computed ideal molar Raman spectra of the mixture. Especially the consideration of the

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partial molar Raman spectra provides insights into the development of hydrogen bonds of

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molecules of one species to their neighbors. The obtained Raman spectra are evaluated with

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respect to the centroid of the symmetric stretching vibration Raman signal of water and to the

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hydroxyl stretching vibration of alcohols. We show the influence of composition and

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temperature on the development of the hydrogen bond network of the mixtures, the hydrogen

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bond network of water and the hydrogen bond network of the organic solvent molecules.

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1 Introduction

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Binary mixtures of water and an organic solvent as acetonitrile, methanol or ethanol are

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miscible in a single liquid and transparent phase over the entire composition range at moderate

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temperature and pressure. These binary mixtures have in common that their electric conductivity,

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their permittivity, their specific volume, enthalpy of mixing or their scattering behavior exhibit a

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non-monotonic behavior when regarded as a function of the composition of the mixture. A

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controversial discussion about the origin of this non-monotonic behavior has grown over the last

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70 years and still theories of the intermolecular interactions in these mixtures are ambiguous. As

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the “organic solvent” contains a hydrophobic part, the terms “hydrophobic solvation” or

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“hydrophobic effects” can summarize all the subsequently mentioned theories.

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The most debated theory is the so called “iceberg theory” from Frank and Evans who

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discussed in 1945 entropic anomalies in several water diluted binary mixtures.1 They have

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chosen the term iceberg because they proposed that water molecules surrounding a strong diluted

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hydrophobic or amphiphile compound create a stronger hydrogen bond network to their water

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neighbors – like in ice – than those in bulk water. Later, in accordance to the hydration of salt

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ions dissolved in water, also the term “hydrophobic hydration” was common2–5 in order to

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describe the development of “hydrate-like” or “ice-like” formations of water molecules.6 This

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concept was confirmed2,7–11 but also challenged12–16 by experimental and theoretical

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investigations. However, not only the formation of water molecules in these mixtures is under

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discussion. For example, other theories about the development of

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 an incomplete mixing on a molecular scale,13,17,18


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 water diluted mixtures without strengthening the structure of water,19–22

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 a

stronger

network

between

the

water

molecules

surrounding

a

hydrophobic/amphiphile molecule,4,9,11,14,23–29

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 hydration shells around single or few hydrophobic/amphiphile molecules,30,31

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 hydrophobic/amphiphile clusters at low concentration of the hydrophobic/amphiphile compound,4,14,19,22–24,30,32,33

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 water clusters at low water concentration,13,22,30,34–36

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 greater percolating networks of water and the hydrophobic/amphiphile compound around equimolar compositions,15,20,22,27,37–41

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 hydrophilic and hydrophobic/amphiphile clusters over a broad composition range,42– 44

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and

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 a complete and homogeneous mixing over a defined composition range28,31,32

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contribute to the current debate. This incomplete above listed abstract of the debate about

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liquid binary water/alcohol and water/nitrile mixtures shows the dispute and the challenging task

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to draw a complete and coherent picture from the comprehensive results stemming from

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thermodynamic studies, molecular dynamic simulations and a variety of measurement

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techniques.

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Common to the systems analyzed in the above listed studies is that their molecular formation

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and the dominant intermolecular forces are strongly influenced by the development of a

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hydrogen bond network (HBN). The unique ability of water to form as many hydrogen (H)-

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bonds as covalent bonds per molecule45 is supposed to be one reason for the abnormalities

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observable in these mixtures. As the intermolecular H-bonds affect the intramolecular covalent

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bonds of water and alcohols, spectroscopic analysis of the intramolecular covalent bond

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vibrations is – beside thermodynamic and theoretical studies – often used to investigate into the

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intramolecular HBN of the mixture. In this context infrared (IR) absorption is one frequently

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applied spectroscopic technique. For example, Takamuku et al. investigated water/acetonitrile


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mixtures over the whole composition range with X-ray diffraction and IR spectroscopy.29 At

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acetonitrile (Acn) molar fractions of 𝑥𝐴𝑐𝑛 < 0.6 the “X-ray radial distribution functions and IR

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spectra suggested that the hydrogen bond network of water is enhanced”. Furthermore within the

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composition range 0.2 < 𝑥𝐴𝑐𝑛 < 0.6 they observed a microheterogeneity with coexisting water

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and acetonitrile clusters. They supposed that the clustering is an explanation for the maximum of

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the enthalpy of mixing at 𝑥𝐴𝑐𝑛 = 0.6. Many other examples of the application of IR spectroscopy

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can be found in the literature.20,21,46–50

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Raman spectroscopy is an alternative and also frequently applied technique for the

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investigation into HBN.7,11,31,38,51–53 In 2012, Lin et al. evaluated polarized Raman spectra from

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different water/alcohol mixtures (methanol, ethanol, 1-propanol and n-propanol) over the whole

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composition range.31 The stronger the intermolecular interactions are, the slower are the

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translational motions that can be deducted from the Raman spectra. They observed a sharp

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increase in the translational relaxation time during the addition of small amounts of alcohol to

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water and interpreted this with the development of water hydration shells around the alcohol

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molecules. In the water rich regime, they interpreted this as a confirmation for the “iceberg

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model”.

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In contrast to the majority of previous Raman investigations we here do not analyze the Raman

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spectrum of the mixture as a whole, but separate the shares originating from each species in the

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mixture. This makes possible the extraction of information about the involvement of each species

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in the HBN in the mixture. The information about the development of the HBN is deduced from

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the symmetric stretching vibration of water and of the OH stretching vibration of alcohols.

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Unfortunately, both Raman signatures completely overlap in the spectral range of Raman shifts

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between 3000 cm-1 and 3800 cm-1. Therefore, we introduce a method for the efficient separation


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of the two overlapping Raman signatures that is based on the consideration of partial molar

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spectra. Finally, from the analysis of the partial molar spectra of each compound in the mixture

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information about the role of this compound in the HBN network can be gathered, while the

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analysis of the spectrum of the mixture provides information of the overall development of the

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HBN.

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2 Experimental

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2.1 Materials

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Experiments were carried out with acetonitrile (Acn) (Merck LiChrosolv®, purity > 99.9 %,

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Germany), methanol (MeOH) (VWR HiPerSolv®, purity > 99.8 %, USA), ethanol (EtOH)

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(Merck Uvasol®, purity > 99.9 %, Germany) and distilled water (W) (KERNDL, conductivity

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< 10 μS cm-1, Germany).

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2.2 Experimental setup

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The binary mixtures were analyzed via Raman spectroscopy in a microcapillary setup (MCS)

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that according to Figure 1 consists of the microcapillary itself (1), three syringe pumps (2) and

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(2-1), a microcapillary heating system (3) and a Raman system (4).


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Figure 1. Schematic of the experimental setup (1-3) and the Raman system (4); L1,2: Convex

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lenses; O: Microscope objective; D: Dichroic mirror; F1,2: Optical Fibers; R: Long pass filter

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(535 nm); S: slit.

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The investigated compounds (water and organic solvent) flow through the MCS from a starting

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point to an end, wherefore the functionality of the MCS and the function of its components will

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be described along the flow direction. At the starting point, two of the three syringe pumps ((2)

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in Figure 1) (2x Teledyne Isco 100 DX, USA) one containing water and the other one containing

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either MeOH, EtOH or Acn reduce their volumes to feed a specific volume flow (+-1 µl min-1)

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into the MCS. The three-way valves next to the outlets of the syringe pumps serve for the

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refill/renew or the cleaning of the respective syringe pump. Within the subsequent T-junction,

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the two fed compounds merge and mix within a stainless steel capillary (ID = 1 mm,

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length = 0.6 m) from which 0.25 m are located within the heating system area (3), to preheat the

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mixture before it reaches the fused silica microcapillary. The temperature conditioning of the


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binary mixture is assured by the microcapillary heating system (3). A fan channels air above a

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heating coil according to the simple principle of a hairdryer whereupon a nozzle guides the

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heated air laminar along the fused silica microcapillary ((1) in Figure 1). A controller (JUMO,

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iTRON 32, Switzerland) that receives the temperature actual value from a temperature sensor

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located 5 mm beside the measuring volume automatically determines the heating power of the

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heating coil required for a certain temperature set point. The transition from the stainless steel

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capillary towards the fused silica microcapillary (ID = 700 µm, OD = 850 µm) (Molex,

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Polymicro TechnologiesTM) is sealed by a PEEK sleeve – located between the stainless steel

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capillary and the fused silica microcapillary – and two component glue. Further downstream,

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immediately after the transition from the microcapillary to a short stainless steel capillary, a

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Coriolis densitometer (Bronkhorst, Mini Cori-Flow ML120, Germany) determines the density

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and the mass flow of the mixture. The Coriolis densitometer is conditioned to exactly the

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temperature and the pressure of the fluid mixture in the measuring volume. A further stainless

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steel capillary connects the Coriolis densitometer with the third syringe pump ((2-1) in Figure 1)

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(Teledyne Isco 500 D). This pump runs reverse and takes up the binary mixture in a way that the

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desired pressure within the entire microcapillary path is constant. According to the maximal

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volume flow of the summation of all delivered compounds of 220 µl min-1 the maximal flow rate

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is 0.95 cm s-1 at the lowest inner diameter of the MCS. The pressure indications of the two feed

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pumps at the start point of the MCS and the one reverse running pump at the end point of the

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MCS do not show a measurable pressure drop along the MCS.

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The Raman system ((4) in Figure 1) whereof the Raman sensor is sketched, includes also the

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excitation continuous wave diode pumped solid-state laser (SmabaTM, Cobolt, 531.93 nm,

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0.250 W, Sweden) and for the signal detection a spectrometer (QE Pro, Ocean Optics, 100 µm


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entrance slit, USA) including a cooled 1024x58 (pixels) charge coupled device (CCD)-detector.

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An optical fiber (F1) guides the excitation laser beam towards the Raman sensor where the beam

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is collimated (L1) and reflected through a high power microscope objective (High Power

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MicroSpot LMH-20x, ThorLabs, NA = 0.4, USA) (O) that focuses the excitation laser beam into

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the probe volume in the center of the microcapillary (C). The high NA of the microscope

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objective ensures that no signals from the microcapillary walls reach the spectrometer and

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interfere with the desired Raman signal of the fluids contained inside the capillary. An aperture

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before the objective (S) lets pass only the high intensity part of the laser beam with originally a

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Gaussian intensity profile. The red-shifted Raman signal scattered in the probe volume passes

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straight the dichroitic mirror (reflecting wavelengths smaller than 535 nm and transmitting

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wavelengths larger than 535 nm) (D) whereon a razor edge long-pass filter (R) blocks the

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remaining elastically scattered light. The second lens (L2: f = 60 mm and Ø = 25.4 mm;

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NA = 0.21) focuses the Raman signals into the detection fiber (core Ø = 200 µm) (F2). The

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detection fiber guides the detected signals to the spectrometer.

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2.3 Raman spectra acquisition using MCS

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At the beginning of each experimental run, we flush the system with pure liquid water at the

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desired temperature of 308 K, 318 K or 328 K. Therefore, the first water containing syringe

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pump delivers 200 µL min-1 of water until the pressure within the third syringe pump at the end

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of the microcapillary reaches 0.4 MPa. Now the third syringe pump starts to run reverse and

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takes up the fed water in a way that the pressure within the MCS remains constant at 0.4 MPa.

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We record the first Raman spectra from pure water at the set temperature that corresponds to a

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mixture composition of the molar fraction 𝑥𝑊 = 1. Afterwards, the second syringe pump


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containing either Acn, EtOH or MeOH starts delivering the compound into the MCS while at the

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same time the feed flow of the water is reduced accordingly. The two compounds mix at the T-

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junction and stream afterwards through the stainless steel capillary through the heating system,

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before the mixture enters the fused silica microcapillary. Via the set flow rates of the two feed

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syringe pumps the composition of the mixture inside the capillary system can be adjusted. For

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example, 152 µl min-1 ethanol and 47 µl min-1 water were set to achieve an equimolar binary

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mixture. The overall volumetric flow rate with respect to the summation of the pure substances

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water and solvent is kept between 200-220 µL min-1. The small flow velocities (less than 1 cm s-

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1)

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system, before they pass the Raman measurement location. Gradually the composition of the

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binary mixture is varied from pure water 𝑥𝑊 = 1 to pure organic solvent 𝑥𝑊 = 0. When the

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mixture is varied from one composition to the next one, it takes approximately 20 minutes to

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reach stationary conditions. Stationary conditions are firstly indicated by the stationary and non-

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fluctuating mixture density and mass flow (Coriolis) and secondly by a constant Raman

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spectrum. At the end of the experimental run, the MCS is flushed (200 µL min-1) with the

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organic solvent in order to record a pure organic solvent spectrum 𝑥𝑊 = 0. During the entire

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procedure, the mixture density and the mass flow are recorded (Coriolis). The density of the

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mixture is required to convert the molar compositions (mol mol-1) of the mixture into

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concentrations (mol L-1).

assure that the fluids inside the capillary adopt the temperature of the air inside the heating

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For each stationary mixture composition 100 Raman spectra are taken with an exposure time

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of 3.4 s spectrum-1. Consequently, the acquisition of 100 Raman spectra takes ~340 s per

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adjusted mixture composition. The Raman spectra are processed and evaluated with respect to


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the development of hydrogen bonds according to the procedure described in the section that

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follows.

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3 Data evaluation

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3.1 Processing of the spectra

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“OH stretching vibration” from now on refers to the symmetric stretching vibration of water

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and to the OH stretching vibration of the hydroxyl functional group of alcohols. For every single

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analyzed mixture composition, a mean spectrum is averaged from the 100 Raman spectra. Each

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experiment was triplicated, in total on three different days. The standard deviation of the

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triplication is provided as error bars in the figures that follow.

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Figure 2 summarizes from the top to the bottom how the mean spectra were treated in order to

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determine (i) the experimental molar Raman spectra of the mixture and (ii) the partial molar

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Raman spectra of the mixture constituents. A detailed description of the chain of processing the

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spectra is provided in the supporting information (SI). Here a short overview is given.


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Figure 2. Raman spectra of an example W/MeOH mixture (𝑥𝑊 = 0.84) at 308 K and 0.4 MPa

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showing the Raman shift region of the CH- and the OH stretching vibration. From top to bottom:

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Pure spectrum as recorded 𝑆𝑚𝑖𝑥(𝜈𝑆), spectrum after the baseline correction (BLC) 𝑆𝑒𝑥𝑝 𝑚𝑖𝑥(𝜈𝑆),

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isolated OH Raman spectrum 𝑆𝑂𝐻 𝑚𝑖𝑥(𝜈𝑆) after the subtraction of the CH Raman spectrum (CHS),

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𝑂𝐻 molar OH Raman spectrum 𝑠𝑂𝐻 𝑚𝑖𝑥(𝜈𝑆) and partial molar OH Raman spectra of water 𝑠𝑊(𝑀𝑒𝑂𝐻)(𝜈𝑆)

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in MeOH and methanol 𝑠𝑂𝐻 𝑀𝑒𝑂𝐻(𝑊)(𝜈𝑆) in water. The blue shaded rectangles mark the Raman shift

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region from which the centroid is calculated. A detailed description of the chain of processing

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the spectra is provided in the supporting information (SI).

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Figure 2 shows at the top the raw mean spectrum 𝑆𝑚𝑖𝑥(𝜈𝑆) acquired from a water/methanol

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(W/MeOH) mixture (𝑥𝑊 = 0.84) as a function of the Raman shift 𝜈𝑆. The background is fitted by

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a cubic spline function and subtracted from 𝑆𝑚𝑖𝑥(𝜈𝑆) in order to achieve a background

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compensated spectrum 𝑆𝑒𝑥𝑝 𝑚𝑖𝑥(𝜈𝑆) that is shown as second spectrum in Figure 2. The Raman

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spectral features that can be assigned to the CH vibration of the organic solvents and to the OH

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stretching vibration of water and the alcohols are labelled with “CH” or “OH”, respectively. The

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CH Raman signatures are subtracted in order to obtain an isolated OH Raman spectrum 𝑆𝑂𝐻 𝑚𝑖𝑥(𝜈𝑆)

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of the mixture, which is shown as third spectrum in Figure 2. 𝑆𝑂𝐻 𝑚𝑖𝑥(𝜈𝑆) (capital letter “𝑆”) is

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divided by the concentration (mol L-1) of the mixture in order to obtain a molar Raman spectrum

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𝑠𝑂𝐻 𝑚𝑖𝑥(𝜈𝑆) (lowercase letter “𝑠”) of the OH vibration of the mixture that is shown as fourth

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spectrum in Figure 2. The concentration of the mixture is known from the density measurements

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(Coriolis), the molar masses and the set composition. Finally, the molar Raman OH spectrum of

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the mixture is deconstructed (for details see the supporting information (SI)) into the shares


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assignable to water and the organic solvent. As the construction method is identical to the

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determination of partial molar properties from molar mixture properties, the corresponding and

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resulting spectra shown in Figure 2 at the bottom are referred to as partial molar Raman spectra

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𝑂𝐻 𝑠𝑂𝐻 𝑖(𝑗)(𝜈𝑆) of the respective compound 𝑖 in a mixture with compound 𝑗. For example 𝑠𝑀𝑒𝑂𝐻(𝑊)(𝜈𝑆)

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shows the partial molar Raman spectrum of the OH vibration of MeOH in the mixture with

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water. 𝑠𝑂𝐻 𝑊(𝑀𝑒𝑂𝐻)(𝜈𝑆) shows the partial molar Raman spectrum of the OH vibration of water in the

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mixture with MeOH. The partial molar Raman spectrum of 𝑖 in 𝑗 represents (exactly as partial

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molar thermodynamic properties do), how the molar Raman spectrum of the mixture changes if

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an infinite small amount of 𝑖 is added to the mixture. The molar fraction weighted summation 𝑂𝐻 𝑂𝐻 𝑠𝑂𝐻 𝑊/𝑀𝑒𝑂𝐻(𝜈𝑆) = 𝑥𝑊𝑠𝑊(𝑀𝑒𝑂𝐻)(𝜈𝑆) + (1 ― 𝑥𝑊)𝑠𝑀𝑒𝑂𝐻(𝑊)(𝜈𝑆)

(1)

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𝑂𝐻 of the partial molar spectra 𝑠𝑂𝐻 𝑊(𝑀𝑒𝑂𝐻)(𝜈𝑆) and 𝑠𝑀𝑒𝑂𝐻(𝑊)(𝜈𝑆) is the molar spectrum of the

236

mixture 𝑠𝑂𝐻 𝑊/𝑀𝑒𝑂𝐻(𝜈𝑆). According to the authors’ knowledge, the deconstruction of mixture

237

spectra into their spectrally overlapping shares based on the computation of partial molar spectra

238

is new.

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Figure 3 shows for the example binary system W/MeOH, how the ideal molar mixture spectrum 𝑂𝐻,0 𝑂𝐻,0 𝑠𝑂𝐻,𝑖𝑑𝑒𝑎𝑙 𝑊/𝑀𝑒𝑂𝐻(𝜈𝑆) = 𝑥𝑊𝑠𝑊 (𝜈𝑆) + (1 ― 𝑥𝑊)𝑠𝑀𝑒𝑂𝐻(𝜈𝑆)

(2)

241

is computed from the molar Raman spectra of the pure (upper index 0) compounds 𝑠𝑂𝐻,0 𝑊 (𝜈𝑆) and

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𝑠𝑂𝐻,0 𝑀𝑒𝑂𝐻(𝜈𝑆) as molar fraction weighted average. Figure 3 also shows that the ideal spectrum

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(𝜈𝑆) is different from the real molar spectrum of the mixture 𝑠𝑂𝐻 𝑠𝑂𝐻,𝑖𝑑𝑒𝑎𝑙 𝑚𝑖𝑥 𝑚𝑖𝑥(𝜈𝑆), exactly as it is the

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case for many thermodynamic properties, such as entropy or Gibbs energy. As it will be shown

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in the next section, the difference between the two OH spectra can be quantified based on the


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Raman shifts of their centroids. This is why also the centroids are indicated in Figure 2 and

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Figure 3.

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Figure 3. Isolated OH stretching vibration of the molar Raman spectra of pure water and pure

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methanol at 308 K and 0.4 MPa (upper row). Molar Raman spectra of the real (black) and ideal

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(blue) W/MeOH-mixture at 𝑥𝑊 = 0.84 (lower row). The blue shaded rectangle marks the Raman

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shift region from which the centroid is calculated

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In Figure 2 and Figure 3 the positive and negative zig-zag peaks between 2800 and 3000 cm-1

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remain as mathematical residual after the subtraction of the CH Raman signal. They do not have

256

any physical meaning and they are not regarded in the further processing of the data.

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3.2 Determination of the centroid of the OH stretching vibration Raman signal

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The Raman shift of the centroid 𝑣𝑂𝐻 (centroid position) of the OH stretching vibration is computed as generally described in Reference54 𝑣𝑂𝐻 =

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



267

(3)

In equation (3) we consider the molar OH Raman spectrum of the mixture 𝑠(𝜈𝑆) = 𝑠𝑂𝐻 𝑚𝑖𝑥

We consider the partial molar spectra of the constituents of the mixture 𝑠(𝜈𝑆) = 𝑠𝑂𝐻 𝑖(𝑗)(𝜈𝑆) 𝑂𝐻

for the computation of their centroid position 𝑣𝑂𝐻 = 𝑣𝑖(𝑗).

265 266

∫3033 𝑐𝑚 ―1𝑠(𝜈𝑆)𝜈𝑆 𝑑𝜈𝑆.

(𝜈𝑆) for the computation of its centroid position 𝑣𝑂𝐻 = 𝑣𝑂𝐻 𝑚𝑖𝑥.

263 264

3798 𝑐𝑚 ―1

1 3798 𝑐𝑚 ―1 ∫3033 𝑐𝑚 ―1𝑠(𝜈𝑆)𝑑𝜈𝑆



𝑖𝑑𝑒𝑎𝑙( ) We consider the ideal molar mixture spectra 𝑠(𝜈𝑆) = 𝑠𝑂𝐻, 𝜈𝑆 for the computation of 𝑚𝑖𝑥 𝑂𝐻,𝑖𝑑𝑒𝑎𝑙

𝑣𝑂𝐻 = 𝑣𝑚𝑖𝑥

.

268

The calculation of the centroid of the OH stretching vibration is a straightforward method to

269

observe and characterize changes in the shape of the OH stretching vibration that is affected by

270

the average development of the HBN of the mixture. The stronger the HBN is developed, the less

271

energy is stored in the OH vibration of alcohols and/or water and therefore the smaller is the

272

centroid position 𝑣𝑂𝐻.

273


15


274

Page 16 of 31

4 Results and Discussion

275

Figure 4 shows the centroid positions of the molar OH Raman spectra of the three binary

276

mixtures water/methanol (W/MeOH), water/ethanol (W/EtOH) and water/acetonitrile (W/Acn)

277

as a function of the water molar fraction in the mixture 𝑥𝑊. The centroids 𝜈𝑂𝐻 𝑚𝑜𝑙𝑎𝑟 computed from

278

𝑂𝐻 𝑂𝐻 the real mixture spectra 𝑠𝑂𝐻 𝑊/𝑀𝑒𝑂𝐻(𝜈𝑆), 𝑠𝑊/𝐸𝑡𝑂𝐻(𝜈𝑆) and 𝑠𝑊/𝐴𝑐𝑛(𝜈𝑆) are given as solid discs, while

279

𝑂𝐻,𝑖𝑑𝑒𝑎𝑙 the centroids 𝜈𝑂𝐻,𝑖𝑑𝑒𝑎𝑙 computed from the ideal mixture spectra 𝑠𝑂𝐻,𝑖𝑑𝑒𝑎𝑙 𝑊/𝑀𝑒𝑂𝐻(𝜈𝑆), 𝑠𝑊/𝐸𝑡𝑂𝐻(𝜈𝑆) and 𝑚𝑖𝑥

280

𝑠𝑂𝐻,𝑖𝑑𝑒𝑎𝑙 𝑊/𝐴𝑐𝑛 (𝜈𝑆) are given as black crosses. The very right values (𝑥𝑊 = 1) represent the centroid

281

positions of the OH Raman spectrum of pure water and the very left values (𝑥𝑊 = 0) represent

282

the centroid positions for the OH Raman spectrum of pure organic solvents. While the alcohols

283

MeOH and EtOH feature an OH Raman signal, Acn – simply due to the lack of the hydroxyl

284

group – does not feature an OH Raman signal. Therefore, no data points are given for pure Acn (

285

𝑥𝑊 = 0). The Acn-richest W/Acn mixture, in which the OH Raman spectrum of water is still

286

observable is 𝑥𝑊 = 0.02 (see supporting information). Therefore, only in the case of W/Acn the

287

ideal mixture spectra 𝑠𝑂𝐻,𝑖𝑑𝑒𝑎𝑙 𝑊/𝐴𝑐𝑛 (𝜈𝑆) were not computed according to equation (2) but according to 𝑠𝑂𝐻,𝑖𝑑𝑒𝑎𝑙 𝑊/𝐴𝑐𝑛 (𝜈𝑆) =

(𝑥𝑊 ― 0.02) 0.98

𝑠𝑂𝐻,0 𝑤 (𝜈𝑆) +

(1 ― 𝑥𝑊) 𝑂𝐻,𝑥 = 0.02 𝑤 𝑠 (𝜈𝑆) 0.98 𝑊/𝐴𝑐𝑛

(4)

288

from the molar Raman spectrum of pure water 𝑠𝑂𝐻,0 𝑊 (𝜈𝑆) and the molar Raman spectrum

289

𝑤 = 0.02 (𝜈𝑆) of the Acn-rich mixture with 𝑥𝑊 = 0.02. The centroid positions were then 𝑠𝑂𝐻,𝑥 𝑊/𝐴𝑐𝑛

290

computed as always according to equation (3).


16

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291 292

Figure 4. Centroid positions 𝜈𝑂𝐻 𝑚𝑖𝑥 of the molar spectra as a function of the mixture composition

293

for the binary mixtures W/MeOH, W/EtOH and W/Acn at 308 K, 318 K and 328 K. The dashed

294

lines are to guide the eyes and the error bars represent the standard deviation of the triplication of

295

each data point (here smaller than the data points).

296 297

The centroid position 𝑣𝑂𝐻 𝑚𝑖𝑥 increases if water is diluted with Acn, but decreases when water is

298

diluted with MeOH or EtOH. The addition of acetonitrile to water weakens the HBN of the

299

mixture in the entire composition range, while the HBN of the mixture is strengthened when

300

MeOH or EtOH are added. The centroid positions 𝑣𝑂𝐻,𝑖𝑑𝑒𝑎𝑙 (black crosses) of the ideal molar OH 𝑚𝑖𝑥

301

𝑖𝑑𝑒𝑎𝑙 Raman spectra 𝑠𝑂𝐻, (𝜈𝑆) are close to the ones (𝑣𝑂𝐻 𝑚𝑖𝑥 𝑚𝑖𝑥) computed from the real molar OH

302

Raman spectra 𝑠𝑂𝐻 𝑚𝑖𝑥(𝜈𝑆) for every investigated mixture. With increasing temperature the HBN

303

gets less developed. Therefore 𝜈𝑂𝐻 𝑚𝑖𝑥 increases with increasing temperature.

304 305

𝑂𝐻,𝑖𝑑𝑒𝑎𝑙 In order to quantify the deviation of the real 𝜈𝑂𝐻 centroid positions, the 𝑚𝑖𝑥 and the ideal 𝜈𝑚𝑖𝑥

relative deviations


17


∆𝑖𝑑𝑒𝑎𝑙𝜈𝑂𝐻 𝑚𝑖𝑥

=

𝑂𝐻,𝑖𝑑𝑒𝑎𝑙 𝜈𝑂𝐻 𝑚𝑖𝑥 ― 𝜈𝑚𝑖𝑥

𝜈𝑂𝐻,𝑖𝑑𝑒𝑎𝑙 𝑚𝑖𝑥

Page 18 of 31

(5)

306

for the three mixtures are provided as a function of the mixture composition for three different

307

temperatures in Figure 5.

308 309

Figure 5. Relative deviations ∆𝑖𝑑𝑒𝑎𝑙𝜈𝑂𝐻 𝑚𝑖𝑥 of the real and ideal centroid positions as a function of

310

the composition of the binary mixtures W/MeOH, W/EtOH and W/Acn at 308 K, 318 K, 328 K.

311

The dashed lines are to guide the eyes and the error bars represent the standard deviation of the

312

triplication of each data point.

313 314

Here negative values imply that the HBN represented by the mixture real spectrum is more

315

developed than the HBN represented by the mixture ideal spectrum. Vice versa, positive values

316

imply that the HBN shown by the mixture real spectrum is less developed than in the ideal one.

317

It should be underlined here that according to equation (2) the ideal molar OH Raman spectra

318

𝑖𝑑𝑒𝑎𝑙 (𝜈𝑆) are simply computed as molar fraction weighted average of the pure compound OH 𝑠𝑂𝐻, 𝑚𝑖𝑥

319

Raman spectra. Therefore, any decay of ∆𝑖𝑑𝑒𝑎𝑙𝜈𝑂𝐻 𝑚𝑖𝑥 from zero indicates that the HBN in the real

320

mixture not simply is a weighted average of the HBN of the pure compounds but the result of a


18

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321

change in the intermolecular forces and of the orientation of the molecules relative to each other.

322

Figure 5 shows that the negative deviations of ∆𝑖𝑑𝑒𝑎𝑙𝜈𝑂𝐻 𝑚𝑖𝑥 increase with decreasing temperature

323

and that the positive deviations of ∆𝑖𝑑𝑒𝑎𝑙𝜈𝑂𝐻 𝑚𝑖𝑥 increase with increasing temperature. Therefore,

324

cold temperatures support the formation of HBN in real mixtures that are more intense than in

325

ideal mixtures. Warm temperatures support the formation of HBN that are less intense than in the

326

ideal mixture case. The HBN deviations from the ideal mixture behavior can explain the

327

anomalies found for the respective mixtures with respect to their density, their conductivity and

328

other properties.27,55–58 ∆𝑖𝑑𝑒𝑎𝑙𝜈𝑂𝐻 𝑚𝑖𝑥 was found to be most temperature sensitive for the system

329

W/Acn. This can be explained by the proximity of the analyzed temperatures to the upper critical

330

solution temperature of this binary system, which at ambient pressure is at 272 K.59

331

𝑂𝐻 𝑂𝐻 Figure 6 shows the centroid positions 𝑣𝑂𝐻 𝑖(𝑗) and 𝑣𝑗(𝑖) of the partial molar Raman spectra 𝑠𝑖(𝑗)

332

(𝜈𝑆) and 𝑠𝑂𝐻 𝑗(𝑖)(𝜈𝑆), respectively, for all three analyzed mixtures in three columns and for all three

333

analyzed temperatures as a function of the binary mixture composition 𝑥𝑤. The upper three

334

diagrams show the centroid position of the partial molar Raman spectrum of water in the mixture

335

with the organic solvent and thus represent the development of the water-HBN in the mixture. In

336

this context, water-HBN refers to the HBN that water molecules develop to their neighbors,

337

which can be other water molecules and/or organic solvent molecules. The lower three diagrams

338

show vice versa the centroid position of the partial molar Raman spectrum of the organic solvent

339

(OS) in the mixture with water and thus represent the development of the OS-HBN of the

340

mixture. In this context, OS-HBN refers to the HBN that organic solvent molecules develop to

341

their neighbors, which can be other organic solvent molecules and/or water molecules.

342

𝑂𝐻 In the following paragraph we first describe in detail the behaviors of 𝑣𝑂𝐻 𝑊(𝑀𝑒𝑂𝐻) and 𝑣𝑀𝑒𝑂𝐻(𝑊).


19


Page 20 of 31

343

𝑂𝐻 For pure water 𝑥𝑤 = 1 it can be seen that 𝑣𝑂𝐻 𝑊(𝑀𝑒𝑂𝐻) and 𝑣𝑀𝑒𝑂𝐻(𝑊) increase with increasing

344

temperature. Thus, the water-HBN and the OS-HBN get less developed with increasing

345

temperature.

346 347

𝑂𝐻 𝑂𝐻 𝑂𝐻 Figure 6. Centroid positions 𝑣𝑂𝐻 𝑖(𝑗) and 𝑣𝑗(𝑖) of the partial molar Raman spectra 𝑠𝑖(𝑗)(𝜈𝑆) and 𝑠𝑗(𝑖)

348

(𝜈𝑆), for the binary mixtures W/MeOH, W/EtOH and W/Acn and for 308 K, 318 K and 328 K as

349

a function of the binary mixture composition 𝑥𝑤.

350 351

For molar fractions 1 > 𝑥𝑊 > 0.8 (regime 1) 𝑣𝑂𝐻 𝑊(𝑀𝑒𝑂𝐻) decreases to a minimum at 𝑥𝑊 ≈ 0.8,

352

when pure water is diluted with MeOH. This means that in regime 1 the water-HBN develops

353

stronger the more MeOH is added to the mixture until a maximum is reached at 𝑥𝑊 ≈ 0.8. On the


20

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354

contrary 𝑣𝑂𝐻 𝑀𝑒𝑂𝐻(𝑊) (lower diagram in Figure 6) increases in the same regime when MeOH is

355

added to pure water to a maximum at 𝑥𝑊 ≈ 0.8. This implies that MeOH at 𝑥𝑊 ≈ 0.8 develops

356

least H-bonds to its neighbors. Obviously the minimum of 𝑣𝑂𝐻 𝑊(𝑀𝑒𝑂𝐻) and the maximum of

357

𝑣𝑂𝐻 𝑀𝑒𝑂𝐻(𝑊) can be found at the same mixture composition 𝑥𝑊 ≈ 0.8, meaning that the maximum

358

development of the water-HBN exists when the minimum development of the OS-HBN exists.

359

These observations are in support of theories that suppose a formation of an intense water-HBN

360

around organic solvent molecules, where the organic solvent molecules participate the less in the

361

HBN, the more intense the water-HBN growth. This development turns around in the

362

composition regime 2 for molar fractions 0.8 > 𝑥𝑊 > 0.2. With the addition of more MeOH

363

𝑂𝐻 𝑣𝑂𝐻 𝑊(𝑀𝑒𝑂𝐻) increases and 𝑣𝑀𝑒𝑂𝐻(𝑊) decreases. Therefore, the water-HBN gets less developed and

364

the OS-HBN develops stronger in regime 2 with the addition of more MeOH. One explanation is

365

that when more than 𝑥𝑊 ≈ 0.8 MeOH molecules are present in the mixture, their dissolution is no

366

more accomplished by surrounding them in a strong water-HBN, but by integrating them into the

367

HBN of the mixture. Therefore, the OS-HBN gets more intense, while the water-HBN gets less

368

intense. At the left border of regime 2 for mixture compositions of 𝑥𝑊 ≈ 0.2 𝑣𝑂𝐻 𝑊(𝑀𝑒𝑂𝐻) shows a

369

local maximum while 𝑣𝑂𝐻 𝑀𝑒𝑂𝐻(𝑊) has already reached approximately the value that we also

370

measured for pure MeOH 𝑥𝑊 = 0. The local maximum of 𝑣𝑂𝐻 𝑊(𝑀𝑒𝑂𝐻) implies that at 𝑥𝑊 ≈ 0.2

371

water molecules develop least H-bonds to their neighbors. Diluting the mixture with even more

372

MeOH in regime 3, which covers the compositions 0.2 > 𝑥𝑊 > 0.0, shows that 𝑣𝑂𝐻 𝑀𝑒𝑂𝐻(𝑊) remains

373

at a constant level, irrespectively of the mixture composition. Thus, the development of the OS-

374

HBN seems not to be influenced by the mixture composition in regime 3. This is different for

375

𝑣𝑂𝐻 𝑊(𝑀𝑒𝑂𝐻), whose course in regime 3 very much depends on the mixture composition and on


21


Page 22 of 31

376

temperature. At 308 K 𝑣𝑂𝐻 𝑊(𝑀𝑒𝑂𝐻) decreases with increasing MeOH content in the mixture. This

377

indicates that the water molecules develop the more H-bonds to their neighbors, the more MeOH

378

is in the mixture. As at the same time the OS-HBN remains unaltered, we speculate that in

379

regime 3 water molecules tend to develop H-bonds preferentially to other water molecules and

380

seem to avoid MeOH molecules. This interpretation is in agreement with the theory of the

381

formation of water-rich and MeOH-rich sub-micro domains (nanostructured fluids) that were

382

found in water/alcohol mixtures.13,22,30 At 328 K 𝑣𝑂𝐻 𝑊(𝑀𝑒𝑂𝐻) shows a local minimum at 𝑥𝑊 ≈ 0.1.

383

Therefore, the accumulation of water molecules in water-rich sub-micro domains, in which the

384

water molecules tend to develop H-bonds mainly to other water-molecules, has a maximum at

385

𝑥𝑊 ≈ 0.1. In mixtures that at 328 K are even richer in MeOH 0.1 > 𝑥𝑊 > 0.0, these nanodomains

386

disintegrate again, which is represented by the increase of 𝑣𝑂𝐻 𝑊(𝑀𝑒𝑂𝐻) towards 𝑥𝑊 = 0.

387

What has been described above for the mixture W/MeOH can be transferred directly to the

388

mixture W/EtOH. Therefore, we skip the description of the mixture W/EtOH. Nonetheless, the

389

mixture compositions at which transitions from regime 1 to regime 2 and from regime 2 to

390

regime 3 occur are slightly different. For both systems W/MeOH and W/EtOH the composition

391

at which the transition from regime 1 to regime 2 occurs (local minima of 𝑣𝑂𝐻 𝑊(𝑀𝑒𝑂𝐻) and

392

𝑣𝑂𝐻 𝑊(𝐸𝑡𝑂𝐻)) coincide with the composition range at which the binary systems feature the extremes

393

of their molar excess enthalpy.

394

In the mixture, W/Acn the course of 𝑣𝑂𝐻 𝑊(𝐴𝑐𝑛) as a function of the mixture composition is very

395

different compared to the mixtures W/MeOH and W/EtOH. When diluting water with Acn

396

𝑣𝑂𝐻 𝑊(𝐴𝑐𝑛) increases monotonically. Therefore the water-HBN is weakened the more, the more Acn

397

is added to the mixture. Putting this observation into the context of the known existence of


22

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398

water-rich and acetonitrile-rich clusters for mixture compositions 0.4 < 𝑥𝑊 < 0.8,29,60 we must

399

conclude that the water-HBN in the water-rich clusters are less developed than in pure water. It

400

has been mentioned already above that the partial molar Raman spectrum of Acn contains an OH

401

Raman signal, though the Acn molecule does not feature an OH vibration. This is due to the fact

402

that partial molar properties show how the molar property of a mixture changes when

403

infinitesimal small amounts of Acn are added to the mixture. Thus, the partial molar Raman

404

spectrum of Acn shows how the OH Raman signal of the mixture is influenced when the mixture

405

is diluted with Acn. In this context large values of 𝑣𝑂𝐻 𝐴𝑐𝑛(𝑊) imply that Acn interacts with water

406

molecules that develop a less intense HBN and small values of 𝑣𝑂𝐻 𝐴𝑐𝑛(𝑊) imply that Acn interacts

407

with water molecules that develop an intense HBN.

408

5 Conclusion

409

We here showed some insight into the mixtures of water and organic solvent that are based on

410

the consideration of partial molar Raman spectra. The idea behind partial molar Raman spectra is

411

identical to the concept of partial molar thermodynamic properties such as partial molar volume,

412

enthalpy, entropy, energy and others, but in our case only applied to Raman spectra.

413

Figure 6 and what has been discussed in its context show that information can be extracted

414

from partial molar Raman spectra that is not extractable from mixture Raman spectra. The

415

consideration of partial molar Raman spectra of water and of the organic solvent made possible

416

the analysis of the hydrogen bond network that water molecules develop to their neighbors and

417

that organic solvent molecules develop to their neighbors. Because of this, for the mixtures

418

water/methanol and water/ethanol we found three different regimes, in which the interaction

419

mechanisms between water and alcohol changes.


23


Page 24 of 31

420

In general, the computation of partial molar Raman spectra is not limited to binary mixtures.

421

However, the more constituents are present in the mixture, the more experimental Raman spectra

422

have to be determined in order to compute the partial molar Raman spectra of each compound.

423

What we showed for the hydrogen bond network is possible for any intermolecular interaction

424

that modulates a signal peak in the Raman spectra. We carried out these experiments at a

425

pressure of 0.4 MPa, as some pressure is required to obtain reproducible operational conditions

426

in the microcapillary setup. Due to the low compressibility of the binary systems analyzed, we

427

speculate that the binary systems at ambient pressure would show very similar results.


24

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428 429


ASSOCIATED CONTENT Supporting Information. Detailed description of the chain of processing the spectra and a list

430

of analyzed mixture compositions with their measured densities.

431

AUTHOR INFORMATION

432

Corresponding Author

433

*E-Mail: [email protected]

434

Author Contributions

435

The manuscript was written through contributions of all authors. All authors have given approval

436

to the final version of the manuscript.

437 438

ACKNOWLEDGMENT

439

The project leading to this contribution has received funding from the European Union’s Horizon

440

2020 research and innovation programme under grant agreement No. 637654 (Inhomogeneities).

441

The authors also gratefully acknowledge the funding of the Erlangen Graduate School in

442

Advanced Optical Technologies (SAOT) by the German Research Foundation (DFG) in the

443

framework of the German excellence initiative.

444

445

6 References

446 447 448 449

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(2) Titantah, J. T.; Karttunen, M. Long-Time Correlations and Hydrophobe-Modified Hydrogen-Bonding Dynamics in Hydrophobic Hydration. J. Am. Chem. Soc. 2012, 134, 9362–9368, DOI: 10.1021/ja301908a.

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(3) Straatsma, T. P.; Berendsen, H. J. C.; Postma, J. P. M. Free Energy of Hydrophobic Hydration: A Molecular Dynamics Study of Noble Gases in Water. J. Chem. Phys. 1986, 85, 6720–6727, DOI: 10.1063/1.451846.

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(4) Tan, M.-L.; Miller, B. T.; Te, J.; Cendagorta, J. R.; Brooks, B. R.; Ichiye, T. Hydrophobic Hydration and the Anomalous Partial Molar Volumes in Ethanol-Water Mixtures. The Journal of chemical physics 2015, 142, 64501, DOI: 10.1063/1.4906750.

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(5) Pangali, C.; Rao, M.; Berne, B. J. Hydrophobic Hydration around a Pair of Apolar Species in Water. J Solution Chem 1979, 71, 2982, DOI: 10.1063/1.438702.

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(6) Blokzijl, W.; Engberts, J. B. F. N. Hydrophobic Effects. Opinions and Facts. Angew. Chem. Int. Ed. Engl. 1993, 32, 1545–1579, DOI: 10.1002/anie.199315451.

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(7) Dolenko, T.; Burikov, S.; Hojo, M.; Patsaeva, S.; Yuzhakov, V. Hydrogen Bonding in Aqueous Ethanol Solutions Studied by Raman Spectroscopy 2010, DOI: 10.1117/12.871101.

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(8) Rezus, Y. L. A.; Bakker, H. J. Observation of Immobilized Water Molecules around Hydrophobic Groups. Phys. Rev. Lett. 2007, 99, 148301, DOI: 10.1103/PhysRevLett.99.148301.

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Hydrogen Bond Networks in Binary Mixtures of Water and Organic

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