The high performance of choline arginate for biomass pretreatment is

Subscriber access provided by READING UNIV

Article

The high performance of choline arginate for biomass pretreatment is due to remarkably strong hydrogen bonding by the anion Amir Karton, Manuel Brunner, Mark J. Howard, Gregory G. Warr, and Rob Atkin ACS Sustainable Chem. Eng., Just Accepted Manuscript • DOI: 10.1021/ acssuschemeng.7b04489 • Publication Date (Web): 08 Jan 2018 Downloaded from http://pubs.acs.org on January 8, 2018

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a free service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are accessible to all readers and citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

ACS Sustainable Chemistry & Engineering is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 20 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ACS Sustainable Chemistry & Engineering

The high performance of choline arginate for biomass pretreatment is due to remarkably strong hydrogen bonding by the anion Amir Karton,a,* Manuel Brunner,b Mark J. Howard,a Gregory G. Warrc and Rob Atkina,* a

School of Molecular Sciences, The University of Western Australia, 35 Stirling Highway, Perth, WA 6009, Australia.

b

School of Environment and Life Sciences, The University of Newcastle, Newcastle, NSW 2300, Australia.

c

School of Chemistry and University of Sydney Nano Institute, The University of Sydney, Sydney, NSW 2006, Australia.

ABSTRACT: The ionic liquid choline arginate [Ch][Arg] is more effective for biomass pretreatment than other choline based amino acid ILs, but the underlying mechanism has been unclear. In the present work we use the high-level CCSD(T)/CBS(MP2) and G4(MP2) thermochemical protocols to probe the H-bonding interactions of [Ch][Arg] with water, and organic functional groups commonly found in biomass. We show that the [Ch][Arg] IL forms unusually strong H-bonding interactions with prototypical H-bond donors. For example, we obtain H-bonding interactions of 76.6, 80.0, and 103.6 kJ mol–1 with water, methanol, and phenol, respectively. Our theoretical results shed light on the capacity of [Ch][Arg] to dissolve biomass, and demonstrates the importance of ion conformation, in addition to speciation, for IL performance more generally. As a point of reference, we compare the Hbonding interactions of [Ch][Arg] with those of a related IL, choline glycinate ([Ch][Gly]), which does not dissolve biomass as effectively as [Ch][Arg]. Keywords: Ionic liquids • CCSD(T) • G4(MP2) theory

*Corresponding Authors E-mail addresses: [email protected] (A. Karton) and [email protected] (R. Atkin). 1

ACS Paragon Plus Environment

ACS Sustainable Chemistry & Engineering 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Introduction Ionic liquids (ILs) have recently attracted considerable attention as safer alternatives to conventional toxic or volatile solvents.1-4 However, some commonly used ionic liquids, such as the popular imidazolium class, have fairly high toxicity5-6 and low biodegradability,6 compromising their green credentials. This has led to the development of ´Bio-ILs´ which consist of naturally occurring biomolecules.7 In 2005 Fukomoto et al. used 20 different amino acids as IL anions with imidazolium cations.8 Later, amino acid anions were combined with choline, a biocompatible cation,9 to produce choline amino acid ILs.10-12 We recently investigated eight choline amino acid ILs for coal pre-treatment.13 Experiments were performed at high (pH > 10.7) where anions are deprotonated. For both thermal and lignite coals, choline arginate ([Ch][Arg]) was clearly the most effective pretreatment agent (solubilised the greatest coal mass). Coal contains many H-bond donor/acceptor groups, which form a cross linked H-bond network. We hypothesised [Arg] was the best performing anion because it has the most H-bond donor/acceptor sites, which disrupt native coal H-bonds. This breaks the coal down into progressively smaller fragments, which can be dissolved or suspended for ultimate conversion to liquid fuels. Other studies have similarly reported that [Ch][Arg] is high performing. Hou et al. screened 10 choline amino acid ([Ch][AA]) ILs and 18 cholinium carboxylate ILs for lignin extraction from lignocellulosic biomass and found that [Ch][Arg] was best performing.14 The enzymatic glucose yield increased from 20.9% for untreated rice straw to 80.6% for rice straw following treatment with [Ch][Arg]. Ren et. al. investigated pretreatment of different biomass feedstocks (wheat straw, rice straw, corncob, sugar cane bargasse, pine) using [Ch][AA] ILs mixed with seawater, as using seawater would reduce process costs at the industrial scale.15 Here to it was found that [Ch][Arg] had significantly higher sugar yields than the next best performing [Ch][AA] IL. Despite these startling experimental outcomes, the mechanism

2


Page 2 of 20

Page 3 of 20 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


behind the high performance of [Ch][Arg] is essentially completely unknown, meaning neither ion structures nor the pretreatment process can be optimised. Here

we

use

the

high-level

G4(MP2)

thermochemical

protocol16

and

the

CCSD(T)/MP2(CBS) procedure with complimentary nuclear magnetic resonance (NMR) spectroscopy measurements to probe the structure and properties of [Ch][Arg] and choline glycinate ([Ch][Gly]), and the strength of their H-bonding interactions with water, and organic groups commonly found in coal and other biomass. In particular, we consider hydroxyl functional groups (MeOH and PhOH) to model H-bond donors commonly found in lignocellulosic biomass. For example, MeOH is a prototypical model of aliphatic hydroxyl groups found in cellulose and hemicellulose and PhOH models aromatic hydroxyl groups found in lignin. For comparison, we also consider amine (MeNH2) and amide (H2C=NH) Hbond donors. We note that the purpose of the present work is to consider the H-bond interactions between one IL pair and prototypical H-bond donors using highly accurate ab initio methods. Nevertheless, it would be interesting to examine larger components of lignocellulosic biomass capable of forming hydrogen bond networks comprised of multiple IL pairs, and further exploration in this direction is underway. However, given the size of these networks such an investigation has to be carried out using more approximate theoretical procedures, e.g., density functional theory (DFT) methods. A first step towards this goal is to identify DFT methods that show good performance for the prototypical H-bond interactions considered here. The current work provides highly accurate benchmark hydrogen-bond energies that could be used for this purpose. In all the aforementioned studies, [Ch][Gly] was also used for pretreatment, but was not as effective as [Ch][Arg] under equivalent conditions, so is a point of comparison. Results are presented with increasing complexity. First, the structures of free [Arg] and [Gly] are examined, followed by their interactions with the model hydrogen bond donor (HBD) groups.

3



Next, [Ch][Arg] and [Ch][Gly] with HBDs are presented, to elucidate the effect of the cation on H-bonding. Finally, the effect of changing the cation to tetramethylammonium (TMA) and pyrrolidinium (PD) is shown, to examine the effect of changing the IL cation on H-bonding.

Computational Details The geometries of all structures were optimized using the B3LYP-D3 density functional theory (DFT) exchange-correlation functional in conjunction with the 6-31+G(2df,p) Poplestyle basis set.17-20 Empirical D3 dispersion corrections21-22 were included using the Becke−Johnson23 damping potential as recommended in Ref. 20 (denoted by the suffix -D3). Harmonic vibrational analyses have been performed at the same level of theory to confirm all the stationary points are equilibrium structures (i.e., they have all real frequencies). Zeropoint vibrational energies and thermal enthalpic corrections have been obtained from these calculations, within the rigid-rotor harmonic oscillator approximation, and have been scaled using literature scaling factors.24 We have used the CCSD(T)/MP2(CBS) approach to obtain accurate interaction energies. In this approach the CCSD(T)/CBS correlation energy (coupled cluster energy with singles, doubles, and quasiperturbative triple excitations at the complete basis set limit) is estimated from the CCSD(T)/cc-pVDZ energy and an MP2-based basis-set-correction term ∆MP2 = MP2/cc-pV{T,Q}Z – MP2/cc-pVDZ. Where the MP2/cc-pV{T,Q}Z correlation energy is extrapolated to the basis-set limit with an extrapolation exponent of 3 and the HF/ccpV{T,Q}Z energy is extrapolated to the basis-set limit with an extrapolation exponent of 5. This additivity scheme has been found to be an efficient way for approximating noncovalent interactions (e.g., hydrogen bonding and dispersion interactions),25-31 as well as for reaction energies32-34 at the CCSD(T)/CBS level. We note that both the CCSD(T)/cc-pVDZ and MP2/cc-pVQZ calculations for the larger systems have strained our computational resources

4


Page 4 of 20

Page 5 of 20 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


to the absolute limit. For example, for the MeNH2•••[Arg][Ch] system, which contains 22 non-hydrogen atoms (H34C13N6O3), the CCSD(T)/cc-pVDZ calculation ran for seven days and the MP2/cc-pVQZ calculation ran for two days on a machine with 28 cores, 256 GB of RAM, and 8TB of scratch disk. For the smaller systems considered in this work we were able to calculate the CCSD(T)/MP2(CBS) energies in conjunction with the augmented (aug-ccpVnZ) basis sets (denoted by CCSD(T)/MP2(CBSaug)). All the high-level ab initio calculations involved in the CCSD(T)/CBS(MP2) procedures were carried out with the Molpro program.35 In addition, the gas-phase electronic energies were obtained using the high-level G4(MP2) variant of the Gaussian-4 (G4) composite thermochemical protocol16, 36 using the B3LYPD3/6-31+G(2df,p) optimized geometries. The G4(MP2) protocol is an efficient composite procedure for approximating the CCSD(T) energy in conjunction with a large triple-ζ-quality basis set.16, 36-37 The G4(MP2) procedure uses a similar additivity scheme to that used in the CCSD(T)/MP2(CBS) procedure. The main difference between the two methods is that G4(MP2) uses the Pople-style basis sets and does not employ basis set extrapolations for the MP2 correlation energies. G4(MP2) theory has been found to produce gas-phase thermochemical properties (such as reaction energies, bond dissociation energies, and enthalpies of formation) with a mean absolute deviation (MAD) of 4.4 kJ mol–1 from the experimental energies of the G3/05 test set.38 We note that the related G3(MP2) method has been found to produce thermochemical properties of ILs with high accuracy, as described in a recent review.39 The Gaussian 09 suite of programs was used for all the DFT and ab initio calculations involved in the G4(MP2) protocol.40

Results and Discussion

5



Page 6 of 20

Before proceeding to examine the chemical implications of the hydrogen bonds considered in the present work, it is of interest to compare between the hydrogen bond strengths obtained with the G4(MP2), CCSD(T)/MP2(CBS), and CCSD(T)/MP2(CBSaug) procedures. Table 1 lists the hydrogen-bond strengths on the electronic potential energy surface (∆Ee) for the 23 hydrogen-bond complexes for which we were able to obtain reference values with both the G4(MP2) and CCSD(T)/MP2(CBS) procedures. The differences between the G4(MP2) and the more accurate CCSD(T)/MP2(CBS) H-bonds are fairly small and do not exceed the threshold of chemical accuracy (arbitrarily defined as 1 kcal mol–1 ≈ 4.2 kJ mol–1). In particular, G4(MP2) tends to systematically underestimate the CCSD(T)/MP2(CBS) H-bond energies by amounts ranging from 0.2 (MeOH•••[Gly][Ch] and CH2=NH•••[Arg][Ch]) to 3.8 (PhOH•••[Gly])

kJ mol–1. Overall, the G4(MP2) method

attains a root-mean-square deviation (RMSD) of merely 2.1 kJ mol–1 relative to the CCSD(T)/MP2(CBS) reference values. It is important to note that ideally we should be using augmented basis sets in the CCSD(T)/MP2(CBS) calculations in light of the anionic character of the arginate and glycinate monomers. However, these calculations proved beyond our computational resources for the larger complexes. For nine complexes we were able to calculate the H-bond strengths with the CCSD(T)/MP2(CBSaug) method (Table 1). For

these

systems

the

differences

between

the

CCSD(T)/MP2(CBS)

and

CCSD(T)/MP2(CBSaug) methods do not exceed 2.5 kJ mol–1 and the overall RMSD is merely 1.1 kJ mol–1. The good agreement between the G4(MP2), CCSD(T)/MP2(CBS), and CCSD(T)/MP2(CBSaug) methods increases our confidence in our reference values. As a side note, we should mention that the CCSD(T)/cc-pVDZ level of theory results in a very large RMSD of 15.3 kJ mol–1 relative to the CCSD(T)/MP2(CBS) reference values. The poor performance of the CCSD(T)/cc-pVDZ level of theory is not surprising, however, the magnitude of the deviations is noteworthy. In the following discussion we will use our

6


Page 7 of 20 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


CCSD(T)/MP2(CBS) reference values for nearly all of the systems. For the large PhOH•••[Arg][Ch] complex, however, we were only able to obtain a G4(MP2) reference value. Table 1. Hydrogen-bond strengths on the electronic potential energy surface (∆Ee, kJ mol–1) for the hydrogen-bond complexes for which we were able to obtain accurate reference values with the G4(MP2) and CCSD(T)/MP2(CBS) procedures.a G4(MP2)

CCSD(T)/MP2(CBS)b

CCSD(T)/MP2(CBSaug)c

Diff.d

Diff.e

1 2

HOH•••[Arg][Ch] HOH•••[Arg]

82.3 53.3

84.7 56.6

56.0

0.6

-2.4 -3.3

3 4

HOH•••[Gly][Ch] HOH•••[Gly]

56.6 54.0

57.3 56.8

55.7

1.0

-0.7 -2.8

5 6

MeOH•••[Arg][Ch] MeOH•••[Arg]

85.8 58.5

87.6 61.5

0.5

-1.8 -3.0

7 8

MeOH•••[Gly][Ch] MeOH•••[Gly]

59.3 57.9

59.5 60.8

1.1

-0.2 -2.9

9 10

PhOH•••[Arg][Ch] PhOH•••[Arg]

106.7 81.7

84.4

-2.7

11 12

PhOH•••[Gly][Ch] PhOH•••[Gly]

95.3 88.8

91.6 92.6

3.7 -3.8

13

MeNH2•••[Arg][Ch]

62.0

61.7

0.3

14

MeNH2•••[Arg]

38.7

40.1

-1.4

15

MeNH2•••[Gly][Ch]

42.4

41.6

0.7

16

MeNH2•••[Gly]

32.6

34.2

17

CH2=NH•••[Arg][Ch]

67.3

67.5

18

CH2=NH•••[Arg]

46.6

47.3

19

CH2=NH•••[Gly][Ch]

45.5

44.9

20

CH2=NH•••[Gly]

40.2

41.6

21 22 23 24

MeOH•••[Arg][TMA] MeOH•••[Gly][TMA] MeOH•••[Arg][PD] MeOH•••[Gly][PD]

74.4 58.6 72.2 54.2

76.8 59.2 74.6 54.6

Countf

61.0 59.7

90.1

33.1

2.5

1.1

-0.2 46.9

0.4

-0.7 0.6

40.7

59.1

0.8

0.1

9 f

-1.6

-1.4 -2.4 -0.6 -2.4 -0.5 23

2.1 RMSD 1.1 f 1.8 MAD 0.4 MSDf 0.9 -1.3 a The structures are shown in Figure S1 and the Cartesian coordinates are given in Table S3 of the Supporting Information. bCCSD(T)/MP2(CBS) values calculated in conjunction with the cc-pVnZ basis sets. c CCSD(T)/MP2(CBS) values calculated in conjunction with the aug-cc-pVnZ basis sets. dDifference CCSD(T)/MP2(CBS) – CCSD(T)/MP2(CBSaug). eDifference G4(MP2) – CCSD(T)/MP2(CBS). fCount = number of systems, RMSD = root-mean-square deviation, MAD = mean-absolute deviation, MSD = meansigned deviation.

7



The structures of two possible free arginate conformations are shown in Figure 1. In the open confirmation (Figure 1(a)), the amino acid side chain points away from the carboxylate group. In the closed conformation (Figure 1(b)), the side chain adopts a cyclic structure with terminal guanidine group forming two H-bonds with the carboxylate group. In both arginate conformations, the carboxylate group H-bonds with the proximal amine moiety. This H-bond is stronger in the open than closed conformer, as indicated by the bond lengths of 2.111 Å and 2.401 Å, respectively. However, the guanidinium to carboxylate H-bonds in the closed conformation are much stronger and shorter (1.893 Å and 1.945 Å) than amine – carboxylate interactions. As a consequence, the closed conformer is more stable, by as much as 57.1 kJ mol–1 on the enthalpic potential energy surface at 298 K. Figure 1(c) shows the optimized structure of [Gly]. [Gly] lacks a guanidine group (which is unique to Arg amongst amino acids), so the only interaction of note is the intramolecular H-bond between the negatively charged carboxylate and the amine. The H-bond length of 2.183 Å is similar to that for the [Arg] open conformer. When tested for biomass pretreatment, [Ch][Arg] and [Ch][Gly] can contain up to 50 wt% water.13-15 At these concentrations cations and anions are not individually solvated by water and exist in domains where cations and anions are associated41-42 (which need not imply ion pairing).43 NMR experiments were performed to confirm the presence of the closed arginate conformer in [Ch][Arg] – water systems. Figure 2 presents the 1H NMR spectra for [Ch][Arg] at ~20% (w/w) in H2O with 10% (v/v) D2O. Spectra for pure arginine are featureless44 due exchange broadening of the labile protons in the amino and guanidino groups.45 However, resonances associated with the amino and guanidino groups are clearly visible in the spectra for the [Ch][Arg] solution (Figure 2). This means these protons exchange slowly on the chemical shift NMR timescale in the ring conformation. This is attributed to stabilisation of H-bonds in the ring conformation, which

8


Page 8 of 20

Page 9 of 20 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


has been observed by NMR for guanidinium groups in hexapeptides. Thus, this NMR data confirms the presence of the [Arg] closed conformer in [Ch][Arg] solutions.

Figure 1. Structures obtained at the B3LYP-D3/6-31+G(2df,p) level of theory for the (a) open and (b) closed conformations of arginate and (c) the glycinate anions. H-bonds are represented by white dashed lines and their distances are given in Å. The relative energy between the two arginate conformations of arginate calculated at the CCSD(T)/MP2(CBS) level is given in kJ mol–1. Atomic colour scheme: H, white; C, gray; N, blue; and O, red.

9



Page 10 of 20

Figure 2. Expansion 1H NMR spectra (14.1 T – 600 MHz 1H) showing the amide region of L-arginine/choline ionic liquid at 20% in H2O with 10% (v/v) D2O obtained using excitation sculptured pure-echo experiments with scan numbers of 256.

Table 2 presents the H-bond strengths calculated by means of the high-level CCSD(T)/CBS(MP2) procedure for the guanidine sp2 nitrogen of [Arg] and the amino N of [Gly] with various HBDs found in biomass (e.g. MeOH, PhOH, MeNH2, and H2C=NH), along with water. For [Arg], the H-bond strength with the guanidine sp2 nitrogen is always stronger than with the amino N (for further details see Table S1 of the Supporting Information), so only the data for the guanidine sp2 nitrogen is presented in Table 2. Structures of representative complexes of [Arg] and [Gly] with water are shown in Figure 3.

Table 2. Hydrogen-bond strength (∆H298, CCSD(T)/CBS(MP2), in kJ mol–1) between the arginate anion ([Arg]), glycinate anion ([Gly]), choline-arginate ([Ch][Arg]), and cholineglycinate ([Ch][Gly]) and various H-bond donors (HOH, HOMe, HOPh, H2NMe, and H2C=NH). The complexes with water are shown in Figure 3. H-bond

∆H298

H-bond

∆H298

HOH•••[Arg]

50.5

HOH•••[Gly]

50.7

MeOH•••[Arg]

56.3

MeOH•••[Gly]

55.6

PhOH•••[Arg]

86.2

PhOH•••[Gly]

88.4

MeNH2•••[Arg]

38.8

MeNH2•••[Gly]

28.8

CH2=NH•••[Arg]

40.9

CH2=NH•••[Gly]

35.9

10


Page 11 of 20 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


HOH•••[Arg][Ch]

76.6

MeOH•••[Arg][Ch]

80.0 a

49.0

MeOH•••[Gly][Ch]

51.6

PhOH•••[Arg][Ch]

103.6

PhOH•••[Gly][Ch]

83.9

MeNH2•••[Arg][Ch]

54.2

MeNH2•••[Gly][Ch]

34.2

CH2=NH•••[Arg][Ch] 59.7 a

HOH•••[Gly][Ch]

CH2=NH•••[Gly][Ch] 37.4

This value was obtained with the G4(MP2) thermochemical protocol.

Figure 3. Hydrogen-bonded complexes formed between water and arginate ([Arg]) and glycinate ([Gly]) anions, and choline-arginate ([Ch][Arg]) and choline-glycinate ([Ch][Gly]). H-bonds are represented by white dashed lines and their distances are given in Å. Atomic colour scheme: H, white; C, gray; N, blue; and O, red. For clarity the hydrogens have been omitted from the sp3 carbons.

11



Table 2 shows that the strength of H-bonds formed between [Arg] or [Gly] with a

given HBD are similar. At first glance this is surprising. As the H-bond strength of guanine sp2 (analogous to [Arg]) with water is 35.1 kJ mol–1 whereas the H-bond strength of ammonia (analogous to [Gly]) with water is 18.3 kJ mol–1, stronger Hbonds with [Arg] are expected. The similarity in H-bond strength for [Arg] or [Gly] with the HBDs could be a consequence of the position of the negatively charged carboxylate group behind the amino nitrogen in glycine, which attracts the H-bonded proton, leading to a stronger interaction. The carboxylate group is much further from the H-bond in arginate (c.f. Figure 3), so does not similarly re-enforce the H-bond. On the other hand, the H-bond strength does vary considerably with HBD type. The strongest H-bonds are formed with HOPh (~84 kJ mol–1), followed by MeOH (~53 kJ mol–1) and water (~47 kJ mol–1), while MeNH2 and H2C=NH form the weakest Hbonds. MeNH2 and H2C=NH are stronger for [Arg] than [Gly] by ~5 kJ mol–1 and ~10 kJ mol-1, respectively. This difference is due to an additional weak H-bond between guanidine and the nitrogen of MeNH2 and CH2=NH. This effect is not noted for oxygen HBDs, because the oxygen lone pairs are orientated away from the guanidine hydrogens. For oxygen HBDs, the overall bond energy trends in Table 2 correlate with the atomic polar tensor (APT) charge46 on the oxygen centres of –0.79 (R = H), –0.87 (R = Me), and –1.16 (R = Ph) a.u. We note that APT charges, which are based on dipole moment derivatives, have been shown to give a reliable picture of the molecular charge distribution.46-47 The similarity of the H-bond strengths for [Arg] or [Gly] with the different HBDs means the anion species alone does not account for differences in biomass pretreatment performance; the cation is required to activate the effect. Table 2 also shows the effect of the presence of [Ch] on the strengths of H-bonds formed by the closed [Arg] conformer and

12


Page 12 of 20

Page 13 of 20 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


[Gly] with the various HBDs. The presence of [Ch] increases the strength of the H-bond formed between [Arg] and the five donor groups by on average 45%, whereas the corresponding average increase for [Gly] is just 8%. The largest increase is 60%, from 50.5 (HOH•••[Arg]) kJ mol–1 to 76.6 (HOH•••[Arg][Ch]) kJ mol–1. There is a corresponding reduction in the

H-bond distances, from 1.730 (HOH•••[Arg]) Å, and 1.686

(HOH•••[Arg][Ch]) Å. For [Ch][Gly], larger increases with [Ch] are noted for weaker Hbonds. The origin of the marked increase in H-bond strength when [Ch] is present for [Arg] but not [Gly] arises from the proximity of the cation charge group to the H-bond. This is demonstrated using water as the HBD in Figure 3, but the argument holds for all the other HBDs, as the orientation of the donor – hydrogen – acceptor atoms are the same. Consider the HOH•••[Arg][Ch] system. The cation and anion charge centres approach closely due to electrostatics, and the hydroxyl group of [Ch] H-bonds with the [Arg] carboxylate group. Because [Arg] is in the closed conformation it allows the cation charge centre to be very close to the oxygen of the water (the HBD); the distance between the water oxygen and nitrogen of choline is 3.610 Å. By contrast, for the HOH•••[Gly][Ch] there is no orienting effect, and the distance from the [Ch] charge centre to the water oxygen is longer at 3.875 Å. Table 3 lists the APT charges on the atoms involved in the O–H•••N hydrogen bonds. The charges on the N and O atoms are more negative, and the charge of the H more positive, for HOH•••[Arg][Ch] than for HOH•••[Gly][Ch]. This leads to a stronger H-bond (Table 2) and a shorter bond distance (Figure 3). It is noteworthy that the strength of the PhOH•••[Arg][Ch] H-bond exceeds 100 kJ mol–1 which is typical for H-bonds between charged species, even though both water and the guanidine moiety are uncharged.

Table 3. Atomic polar tensor (APT) charges (in a.u.) on the OH•••N atoms in the HOH•••[Arg][Ch] and HOH•••[Gly][Ch] complexes shown in Figure 3. 13



System

O

H

Page 14 of 20

N

HOH•••[Arg][Ch] –0.80 +0.54 –0.86 HOH•••[Gly][Ch] –0.74 +0.48 –0.52

To examine whether [Ch] is critical for the strong H-bonding interactions, simulations have also been performed for methanol (a typical HBD found in biomass) with [Arg][X] and [Gly][X], where X is tetramethylammonium (TMA) and N,N-dimethylpyrrolidinium (PD), c.f. Table 4. As with [Ch], the MeOH•••[Arg][X] H-bonds are in both cases approximately 20 kJ mol–1 stronger than MeOH•••[Gly][X]. This indicates the orientation effect of [Arg] holds when the cation is changed. The H-bonds between methanol and both [TMA][Arg] or [PD][Arg] are ~10 kJ mol–1 weaker than that of MeOH•••[Arg][Ch], although the distances between the cation charge centres and H-bond group are similar for all three systems (c.f. Supporting Information). This suggests a secondary H-bond stabilizing effect in HBD•••[Arg][Ch] systems; As the cation and anion charge centres are drawn together, the Hbond between the [Ch] hydroxyl group and the carboxyl group of [Arg] pulls the ring structure into a lower energy conformation, which is more favourable for H-bonding between the guanidinium group and HBD. For [TMA] and [PD] the cation and anion charge centres lack hydroxyl groups so do not affect the anion conformation in a similar manner. This subtle effect is the topic of continued study.

Table 4. Hydrogen-bond strength (∆H298, CCSD(T)/CBS(MP2), in kJ mol–1) between the [Arg][X] and [Gly][X] ILs and methanol, X = tetramethylammonium (TMA) and pyrrolidinium (PD). ∆H298 H-bond

H-bond

∆H298

MeOH•••[Arg][TMA] 70.3

MeOH•••[Gly][TMA] 48.9

MeOH•••[Arg][PD]

MeOH•••[Gly][PD]

67.8

14


47.3

Page 15 of 20 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Conclusions In earlier work, the ability of eight [Ch][AA] ILs to solubilise two different grades of coal was examined, and it was found that [Arg][Ch] was the most effective by a considerable margin, with corresponding results reported for other forms of biomass.14-15 This work reveals in R-OH•••[Arg][Ch] systems, [Arg] adopts a closed (ring) conformation, with the guanidine sp2 nitrogen forming a H-bond with the HBD group. The cation charge group associates closely with the anion charge centre, and the ring structure places the cation charge group in close proximity to the hydrogen bond formed by the HBD and anion guanidine sp2 nitrogen. This leads to the charge on partially negative atoms to become more negative, and to an increase in the partial positive charge of the proton, leading to strong H-bonds. The strength of the H-bonds varied considerably with donor group, but H-bonds with [Arg] were always considerably stronger than with [Gly], which was investigated for comparison. Arginine is the only amino acid which contains a guanidine group, so only it can form the closed structure with exposed guanidine sp2 nitrogen. This explains why [Arg] was the best preforming anion for coal and biomass pretreatment. It forms the strongest hydrogen bonds, so is therefore best able to disrupt the native hydrogen bond network in coal, even when diluted with water. In the wider context, this work, combined with our earlier study, shows that for flexible ions, like those based on amino acids, conformation can be as important as speciation for function. This has wide implications for the rational design of taskspecific ionic liquids and the rapidly emerging deep eutectic solvent class, and for applications ranging from solvency, catalysis, CO2 capture, and for control of reaction outcomes.

15



16


Page 16 of 20

Page 17 of 20 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


SUPPLEMENTARY MATERIAL See supplementary material for a benchmark hydrogen-bond energies on the electronic (∆Ee) and zero point energy-corrected (∆H0) potential energy surfaces (Table S1); hydrogen-bond strengths (∆H298) between the various nitrogens in the arginate anion and a water molecule (Table S2); B3LYP-D3BJ/6-31+G(2df,p) optimized structures for all the considered complexes (Table S3 and Figure S1).

ACKNOWLEDGMENTS We gratefully acknowledge the generous allocation of computing time from the National Computational Infrastructure (NCI) National Facility, and system administration support provided by the Faculty of Science at the University of Western Australia (UWA) to the Linux cluster of the Karton group. A.K. acknowledges the Australian Research Council for a Future Fellowship (FT170100373). R.A. acknowledges UWA new staff start-up funding. M.B. acknowledges the support from his supervisors Brett Neilan and Paul Low.

REFERENCES 1. Hallett, J. P.; Welton, T., Room-Temperature Ionic Liquids: Solvents for Synthesis and Catalysis. 2. Chem. Rev. 2011, 111 (5), 3508-3576. 2. Hayes, R.; Imberti, S.; Warr, G. G.; Atkin, R., Effect of Cation Alkyl Chain Length and Anion Type on Protic Ionic Liquid Nanostructure. J. Phys. Chem. C 2014, 118 (25), 13998-14008. 3. Li, H.; Wood, R. J.; Endres, F.; Atkin, R., Influence of alkyl chain length and anion species on ionic liquid structure at the graphite interface as a function of applied potential. J. Phys.: Condens. Matter 2014, 26 (28). 4. Li Zaijun, S. X., Liu Junkang Ionic Liquid as Novel Solvent for Extraction and Separation in Analytical Chemistry. In Ionic Liquids: Applications and Perspectives, Kokorin, A., Ed. InTech: 2011. 5. Kulacki, K. J.; Lamberti, G. A., Toxicity of imidazolium ionic liquids to freshwater algae. Green Chem. 2008, 10 (1), 104-110. 6. Romero, A.; Santos, A.; Tojo, J.; Rodríguez, A., Toxicity and biodegradability of imidazolium ionic liquids. J. Hazard. Mater. 2008, 151 (1), 268-273. 7. Fukaya, Y.; Iizuka, Y.; Sekikawa, K.; Ohno, H., Bio ionic liquids: room temperature ionic liquids composed wholly of biomaterials. Green Chem. 2007, 9 (11), 1155-1157. 8. Fukumoto, K.; Yoshizawa, M.; Ohno, H., Room Temperature Ionic Liquids from 20 Natural Amino Acids. J. Am. Chem. Soc. 2005, 127 (8), 2398-2399. 9. Hou, X.-D.; Liu, Q.-P.; Smith, T. J.; Li, N.; Zong, M.-H., Evaluation of Toxicity and Biodegradability of Cholinium Amino Acids Ionic Liquids. PLoS ONE 2013, 8 (3), e59145. 17



10. Hou, X.-D.; Smith, T. J.; Li, N.; Zong, M.-H., Novel renewable ionic liquids as highly effective solvents for pretreatment of rice straw biomass by selective removal of lignin. Biotechnol. Bioeng. 2012, 109 (10), 2484-2493. 11. Liu, Q.-P.; Hou, X.-D.; Li, N.; Zong, M.-H., Ionic liquids from renewable biomaterials: synthesis, characterization and application in the pretreatment of biomass. Green Chem. 2012, 14 (2), 304-307. 12. Wang, R.; Chang, Y.; Tan, Z.; Li, F., Applications of choline amino acid ionic liquid in extraction and separation of flavonoids and pectin from ponkan peels. Sep. Sci. Technol. 2016, 51 (7), 1093-1102. 13. To, T. Q.; Shah, K.; Tremain, P.; Simmons, B. A.; Moghtaderi, B.; Atkin, R., Treatment of lignite and thermal coal with low cost amino acid based ionic liquid-water mixtures. Fuel 2017, 202, 296-306. 14. Hou, X.-D.; Xu, J.; Li, N.; Zong, M.-H., Effect of anion structures on cholinium ionic liquids pretreatment of rice straw and the subsequent enzymatic hydrolysis. Biotechnol. Bioeng. 2015, 112 (1), 65-73. 15. Ren, H.; Zong, M.-H.; Wu, H.; Li, N., Utilization of Seawater for the Biorefinery of Lignocellulosic Biomass: Ionic Liquid Pretreatment, Enzymatic Hydrolysis, and Microbial Lipid Production. ACS Sustain. Chem. Eng. 2016, 4 (10), 5659-5666. 16. Curtiss, L. A.; Redfern, P. C.; Raghavachari, K., Gaussian-4 theory using reduced order perturbation theory. J. Chem. Phys. 2007, 127 (12), 124105. 17. Becke, A. D., Density‐functional thermochemistry. III. The role of exact exchange. J. Chem. Phys. 1993, 98 (7), 5648-5652. 18. Grimme, S.; Ehrlich, S.; Goerigk, L., Effect of the damping function in dispersion corrected density functional theory. J. Comput. Chem. 2011, 32 (7), 1456-1465. 19. Lee, C.; Yang, W.; Parr, R. G., Development of the Colle-Salvetti correlation-energy formula into a functional of the electron density. Phys. Rev. B 1988, 37 (2), 785-789. 20. Stephens, P. J.; Devlin, F. J.; Chabalowski, C. F.; Frisch, M. J., Ab Initio Calculation of Vibrational Absorption and Circular Dichroism Spectra Using Density Functional Force Fields. J. Phys. Chem. 1994, 98 (45), 11623-11627. 21. Grimme, S., Density functional theory with London dispersion corrections. Wiley Interdiscip. Rev. Comput. Mol. Sci. 2011, 1 (2), 211-228. 22. Grimme, S.; Antony, J.; Ehrlich, S.; Krieg, H., A consistent and accurate ab initio parametrization of density functional dispersion correction (DFT-D) for the 94 elements HPu. J. Phys. Chem.2010, 132 (15), 154104. 23. Becke, A. D.; Johnson, E. R., A density-functional model of the dispersion interaction. J. Phys. Chem. 2005, 123 (15), 154101. 24. Merrick, J. P.; Moran, D.; Radom, L., An Evaluation of Harmonic Vibrational Frequency Scale Factors. J. Phys. Chem. A 2007, 111 (45), 11683-11700. 25. Brauer, B.; Kesharwani, M. K.; Kozuch, S.; Martin, J. M. L., The S66x8 benchmark for noncovalent interactions revisited: explicitly correlated ab initio methods and density functional theory. Phys. Chem. Chem. Phys. 2016, 18 (31), 20905-20925. 26. Goerigk, L.; Karton, A.; Martin, J. M. L.; Radom, L., Accurate quantum chemical energies for tetrapeptide conformations: why MP2 data with an insufficient basis set should be handled with caution. Phys. Chem. Chem. Phys. 2013, 15 (19), 7028-7031. 27. Jurečka, P.; Hobza, P., On the convergence of the (∆ECCSD(T)−∆EMP2) term for complexes with multiple H-bonds. Chem. Phys. Lett. 2002, 365 (1), 89-94. 28. Kesharwani, M. K.; Karton, A.; Martin, J. M. L., Benchmark ab Initio Conformational Energies for the Proteinogenic Amino Acids through Explicitly Correlated Methods. Assessment of Density Functional Methods. J. Chem. Theory Comput. 2016, 12 (1), 444-454. 18


Page 18 of 20

Page 19 of 20 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


29. Klopper, W.; Luthi, H. P., The MP2 limit correction applied to coupled cluster calculations of the electronic dissociation energies of the hydrogen fluoride and water dimers. Mol. Phys. 1999, 96 (4), 559-570. 30. Liakos, D. G.; Neese, F., Improved Correlation Energy Extrapolation Schemes Based on Local Pair Natural Orbital Methods. J. Phys. Chem. A 2012, 116 (19), 4801-4816. 31. Manna, D.; Kesharwani, M. K.; Sylvetsky, N.; Martin, J. M. L., Conventional and Explicitly Correlated ab Initio Benchmark Study on Water Clusters: Revision of the BEGDB and WATER27 Data Sets. J. Chem. Theory Comput. 2017, 13 (7), 3136-3152. 32. Friedrich, J., Efficient Calculation of Accurate Reaction Energies—Assessment of Different Models in Electronic Structure Theory. J. Chem. Theory Comput. 2015, 11 (8), 3596-3609. 33. Yu, L.-J.; Karton, A., Assessment of theoretical procedures for a diverse set of isomerization reactions involving double-bond migration in conjugated dienes. Chem. Phys. 2014, 441 (Supplement C), 166-177. 34. Yu, L.-J.; Wan, W.; Karton, A., Evaluation of the performance of MP4-based procedures for a wide range of thermochemical and kinetic properties. Chem. Phys. 2016, 480 (Supplement C), 23-35. 35. Werner, H.-J.; Knowles, P. J.; Knizia, G.; Manby, F. R.; Schütz, M., Molpro: a general-purpose quantum chemistry program package. Wiley Interdiscip. Rev. Comput. Mol. Sci 2012, 2 (2), 242-253. 36. Curtiss, L. A.; Redfern, P. C.; Raghavachari, K., Gn theory. Wiley Interdiscip. Rev. Comput. Mol. Sci. 2011, 1 (5), 810-825. 37. Karton, A., A computational chemist's guide to accurate thermochemistry for organic molecules. Wiley Interdiscip. Rev. Comput. Mol. Sci. 2016, 6 (3), 292-310. 38. Curtiss, L. A.; Redfern, P. C.; Raghavachari, K., Assessment of Gaussian-3 and density-functional theories on the G3/05 test set of experimental energies. J. Phys. Chem. 2005, 123 (12), 124107. 39. Izgorodina, E. I.; Seeger, Z. L.; Scarborough, D. L. A.; Tan, S. Y. S., Quantum Chemical Methods for the Prediction of Energetic, Physical, and Spectroscopic Properties of Ionic Liquids. Chem. Rev. 2017, 117 (10), 6696-6754. 40. Frisch, M. J.; Trucks, G. W.; Schlegel, H. B.; Scuseria, G. E.; Robb, M. A.; Cheeseman, J. R.; Scalmani, G.; Barone, V.; Mennucci, B.; Petersson, G. A., Gaussian 09. Revision E.01, Gaussian Inc., Wallingford, CT 2009. 41. Hayes, R.; Imberti, S.; Warr, G. G.; Atkin, R., How Water Dissolves in Protic Ionic Liquids. Angew. Chem. Int. Ed. 2012, 51 (30), 7468-7471. 42. Hayes, R.; Warr, G. G.; Atkin, R., Structure and Nanostructure in Ionic Liquids. Chem. Rev. 2015, 115 (13), 6357-6426. 43. Holloczki, O.; Malberg, F.; Welton, T.; Kirchner, B., On the origin of ionicity in ionic liquids. Ion pairing versus charge transfer. Phys. Chem. Chem. Phys. 2014, 16 (32), 1688016890. 44. Bundi, A.; Wüthrich, K., 1H‐nmr parameters of the common amino acid residues measured in aqueous solutions of the linear tetrapeptides H‐Gly‐Gly‐X‐L‐Ala‐OH. Biopolymers 1979, 18 (2), 285-297. 45. Wüthrich, K.; Wagner, G.; Richarz, R.; Braun, W., Correlations between internal mobility and stability of globular proteins. Biophys. J. 1980, 32 (1), 549-560. 46. Cioslowski, J., A new population analysis based on atomic polar tensors. J. Am. Chem. Soc. 1989, 111 (22), 8333-8336. 47. De Proft, F.; Martin, J. M.; Geerlings, P., On the performance of density functional methods for describing atomic populations, dipole moments and infrared intensities. Chem. Phys. Lett. 1996, 250 (3-4), 393-401. 19



Choline arginate is more effective for biomass treatment than similar amino acid based ionic liquids because arginate adopts a closed structure leading to short, strong H-bonds.


Page 20 of 20

The high performance of choline arginate for biomass pretreatment is

Recommend Documents