Construction of High-Precision Adiabatic Calorimeter and Thermodynamic Study on Functional Materials

Abstract

In this chapter, a high-precision fully automated adiabatic calorimeter for heat capacity measurement of condensed materials in the temperature range from 80 to 400 K was described in detail. By using this calorimeter the heat capacity and thermodynamic properties of two kinds of function materials, ionic liquid and nanomaterials, were investigated. The heat capacities of IL [EMIM][TCB] were measured over the temperature range from 78 to 370 K by the high-precision-automated adiabatic calorimeter. Five kinds of nanostructured oxide materials, Al2O3, SiO2, TiO2, ZnO2, ZrO2, and two kinds of nanocrystalline metals: nickel and copper were investigated from heat capacity measurements. It is found that heat capacity enhancement in nanostructured materials is influenced by many factors, such as density, thermal expansion, sample purity, surface absorption, size effect, and so on.

1. Introduction

Adiabatic calorimetry is one of the most important research methods in the fields of thermochemistry and thermophysics. Many results can be obtained from this method, such as, molar heat capacities over wide temperature range, standard entropy, standard thermodynamic functions; the temperature, enthalpy, entropy and mechanism of phase transition, and other important information concerned with the structure and energetics of substances, which have very significant guiding role for theoretical research and application development of various new substances or materials. But at present high-precision adiabatic calorimeter is not available from commercial apparatus in the world. In this chapter, hence, we introduce a high-precision fully automatic adiabatic calorimeter constructed in our themochemistry laboratory, and report the thermodynamic property studies of two types of functional materials: ionic liquid and nanomaterials performed by this adiabatic calorimeter.

2. Construction of a fully automated high-precision adiabatic calorimeter used for heat capacity measurements of condensed materials in the range from 80 to 400 K

2.1. Introduction

Heat capacity is one of the fundamental thermodynamic properties of materials and is very important in many physical and chemical theoretical research programmes and engineering technology designs. Adiabatic calorimetry is the most reliable technique used to obtain heat capacity and other thermodynamic data of substances [1, 2, 3, 4, 5, 6, 7, 8, 9]. Research on adiabatic calorimetry has been conducted in our thermochemistry laboratory since 1960s and several adiabatic calorimetric apparatus have been constructed to obtain measurements over the temperature ranges of (4.2-90) K [10, 11, 12], (80-400) K [13, 14, 15, 16, 17, 18, 19, 20, 21], (70-580) K [18, 19], (300-600 K) [20] and (400-700) K [22]. Traditional adiabatic calorimetric experiments have the disadvantages of complicated experimental procedures and large amounts of experimental data which needs to be treated in order to obtain high-precision heat capacity values. Therefore, we have constructed an adiabatic calorimeter which greatly simplifies experimental procedures (by using modern computerized technology together with control theory) which can be used to obtain measurements in the temperature range of (80-40) K. The design was based on our previously reported automated adiabatic calorimetric apparatuses [17, 19]. This new calorimetric instrument has the advantages of compact data acquisition and process system; advanced intellectual level resulting in the powerful processing ability of the software; better stability of measurement; and a higher reliability of data acquisition. For a long time, low temperature adiabatic calorimetry has been used to: determine the heat capacities of various condensed materials; investigate phase transitions of materials; and determine the standard thermodynamic properties of the materials.

2.2. The construction of the adiabatic calorimeter

2.2.1. The adiabatic calorimetric system

The calorimetric system includes a calorimetric cryostat, a data collection system, an adiabatic condition control system and a high vacuum pumping system. The calorimetric cryostat consists of a sample cell, inner and outer adiabatic shields and a high vacuum can. The data collection system consisted of a multi-channel data acquisition/switch unit (Agilent 34970A) [23] for electric energy collection, a 7 1/2 Digit nanovolt micro-Ohm meter (Agilent 34420A) [24] for acquisition of the temperature of the sample cell and a P4 computer equipped with a matched module and interface card GPIB (IEEE 488).The adiabatic condition control system consisted of a high-precision temperature controller (Lake Shore, Model 340) and two sets of six-junction chromel-copel (Ni-55%, Cu-45%) thermocouple piles that were installed between the sample cell and the inner adiabatic shield and between the inner and outer adiabatic shield, respectively. The high vacuum pump system consisted of a combined rotational mechanical pump and oil diffusion pump (Edwards, Model NXK 333000). The block diagram of the adiabatic calorimetric system is shown in Figure 1.

Figure 1.

Block diagram of the adiabatic calorimetric system. 1, sample cell; 2, inner adiabatic shield; 3, outer adiabatic shield; 4, vacuum can; 5, silicon controlled regulator; 6, temperature controller (Lake shore 340); 7, data acquisition/switch unit (Agilent 34970A); 8, 71/2 digit nanovolt/micro-Ohm meter (Agilent 34420A); 9, computer; 10, combined rotational mechanical pump and oil diffusion pump (Edwards, model—NXK333000).

2.2.2. Sample cell and adiabatic calorimetric cryostat

The sample cell (see Figure 2A) was made of 0.3 mm thick gold-plated copper, 20 mm long, 20 mm in diameter with inner volume of about 6 cm³. Three sheaths were fixed at the bottom of the cell for inserting the platinum thermometer and thermocouples. Electric heating wires(insulated Karma wire of 0.12 mm in diameter, R = 120 Ω)were coiled on the outer wall of cell A small amount of silicone thermally conductive sealant (type HT916, produced by Shanghai Huitian New Chemical Material Company, Limited) was used to seal the lid to the main body of the cell. On the lid there was a section of copper capillary for pumping out the air in the cell and introducing the helium gas to promote thermal equilibrium inside the cell. The capillary was pinched off and the resultant fracture was soldered by solder to ensure the sealing of the cell.

Figure 2.

(A) Schematic diagram of sample cell of the adiabatic calorimeter. (B) Schematic diagram of main body of the adiabatic calorimeter.

The adiabatic calorimetric cryostat is shown in Figure 2B. Two sets of six-junction chromel-copel thermocouple piles were installed between the sample cell and the inner shield, and between the inner and the outer shield to detect the temperature differences between them. The junctions of the thermocouple piles were inserted in the sheath and fixed on the corresponding surfaces whose temperatures were to be measured. The detected signal of the thermal electromotive force (EMF) created by the temperature differences was fed into the temperature controller which controlled the current through the heating wires on the inner and outer adiabatic shields, This heating was used to minimize the temperature difference between the sample cell and the shields thus maintaining a good adiabatic environment.

The sample cell and the adiabatic shields were placed in the high vacuum can to eliminate the heat loss of the cell caused by convection heat transfer. During the heat capacity measurements the vacuum can was evacuated to (10⁻³~10⁻⁴) Pa by the rotational and diffusion pump.

A precision miniature platinum resistance thermometer (produced by Shanghai Institute of Industrial Automatic Meters, 16 mm long, 1.6 mm in diameter) measured the temperature of the sample cell. The resistance of the thermometer was measured by the 7 1/2 Digit nanovolt/micro-Ohm meter (Agilent 34420A) with four-terminal resistance measurement circuit, and then inputted into the computer for processing after A/D conversion. Then the corresponding temperature was calculated according to the relationship between the resistance and temperature of the thermometer, which was calibrated in terms of ITS-90 by Station of Low-Temperature Metrology and Measurements, Chinese Academy of Sciences. Here R₀ = 100.1384 Ω.

2.2.3. Computer, data collection unit and software

The data acquisition system used a P4 computer with Windows Operation System (OS), which had fast computing power and a parallel processing function. The computer collected and controlled data information through GPIB (IEEE 488) card with PCI interface. The interface card (Agilent 82350A) was used in the data exchange because this card has a transmitting speed of 750 kBs^-1, (here B refers to bytes) which guarantees the information exchanging speed during the experimental process of adiabatic control, collection and control of electrical heating and collection of sample temperatures. The software was programmed to run functions at designated times.

The A/D conversion of all the collected data was done by the data acquisition/switch unit (Agilent 34970A) [23] and 7 1/2 digit nanovolt/micro-Ohm meter, (Agilent 34420A) [24]. The Agilent 34970A had a high precision of data conversion and stability, and had a resolution of 100 nV at 100 mV measuring range, which varies within ±0.0090% over a year. Over the measuring range of our experiments, the resolution of the resistance measurement was 1 mΩ with a variation of ±0.0140%, thus guaranteeing the high precision of data collection. The Agilent 34,420 A nanovolt/ micro-ohm meter was a high-sensitivity multimeter optimized for performing low-level measurements. It combined low-noise voltage measurements with resistance and temperature functions, setting a new standard in low-level flexibility and performance. It has 7 1/2 digits resolution and 100 pV/100 nΩ sensitivity (equivalent to the temperature resolution of 2.5 × 10⁻⁵ K for the platinum thermometer with R₀ = 100 Ω).

The software of the system consisted mainly of three modules (Figure 3): data collection and control module, adiabatic environment control module and the module for the setting and revision of the experimental conditions and the data displaying.

Figure 3.

The block diagram of the software for calorimetric measurements programmed by computer.

The heat capacity measurement was done using an intermittent direct heating method, i.e., loading a certain number of moles (m) of sample in the sample cell of the calorimeter followed by the input of an appropriate amount of electric energy (Q) to induce a temperature rise of the cell (ΔT). From the measured values Q and ΔT the heat capacity of the sample cell (C_p) was determined:

E1

where

$$Q=IV\tau$$E2

and I, V and τ are current, voltage and duration of heating, respectively.

Accordingly, the heat capacity measurement was made as follows. First the temperature of the sample cell was kept stable under strict adiabatic conditions for a time which is called the temperature equilibrium period. During this period the temperature inside the sample cell was kept in equilibrium by the excellent thermal conductivity of the helium gas which fills the cell and two radial copper vanes fixed to the cell. When the temperature of the sample cell reached equilibrium, the computer system controlled (34970A) the input of an appropriate amount of current I and voltage V used to heat the sample cell to induce a temperature rise of ΔT. The computer system reads the I and V data at intervals (e.g., 30 s) during the heating process. The computer controlled the heating duration and calculated Q from Eq. (2). Following the heating period, the temperature T of sample cell was measured at the next temperature equilibrium period. The temperature increment of the sample cell, ΔT, caused by the energy input was calculated on the basis of the difference in temperatures between the neighboring two equilibrium periods. The heat capacity, C_p, was then obtained from Eq. (1). Through repetitions of the above procedures the heat capacity from low temperature to high temperature could be calculated. In order to ensure adequate precision of heat capacity measurements, some problems had to be solved, such as: the determination of the beginning of the equilibrium temperature during the thermal equilibrium period; the precise measurement of the equilibrium temperature of the sample cell; and the temperature correction resulted from the heat exchange between the sample cell and its environment under non-ideal adiabatic conditions.

Following the heating period, the temperature of the sample cell continued to change as a result of the uneven distribution of the temperature of the sample cell caused by the continuous transferring of heat energy and the heat exchange between the sample cell and its environment owing to the non-ideal adiabatic conditions. After some time, however, the temperature variation of the sample cell due to the transferring of heat energy decreased while the heat exchange between the sample cell and its environment continued. Under the condition that the temperatures of the inner and outer shields were keep stable, the heat exchange between the sample cell and its environment become stable and thus there was a linear relationship between the temperature of sample cell and the time of the experimental measurement. According to this principle, the computer fitted several collected temperature points of the sample cell versus time to get the lines l_i or l_i + 1 (see Figure 4), whose slope was the variance ratio of the temperature as a function of time. The temperature of the calorimetric system can be regarded as reaching equilibrium if the variance ratio become small enough, e.g., 0.001 K min⁻¹, where min refers to minutes.

Figure 4.

The principle diagram of the temperature rise correction.

On the other hand, except for the temperature variation, the deviation of the data collection also influences the slope of the line. The effect can be evaluated from the correlation coefficient of the fitted line. The closer the correlation coefficient is to 1, and the more the temperature points are focused around the line, the smaller will be the data collection random error. The present system took the average of the absolute values of the differences between the measured values and the fitted values as the estimation criterion. When the average value was less than some value, e.g., 0.001 K, the random error of the data collection could be neglected.

The collected temperature data were processed automatically by the computer to determine the arrival of temperature equilibrium; when the above two criteria were satisfied the computer deemed that the temperature of the calorimeter had reached equilibrium. Otherwise the temperature measurement time would be prolonged and another temperature point would be collected and the last ten temperature points would be processed with the same method as mentioned above until the two criteria were met.

The precision of the temperature measurement of sample cell correlated with the random error of the temperature data collection. To avoid this kind of error, the system collected a number (e.g., 10) of temperature points after the temperature of sample cell reached equilibrium, ranking them according to the magnitude of the collected values, discarding the maximum and minimum values among them and correcting the error by the figure filter technique:

E3

in which $\overline{T}$ is the corrected temperature value, K = n−2, T_i is the collected temperature value, n is the times of the temperature data collection after the temperature equilibrium. The corrected temperatures are shown on l_i and l_i + 1 (see Figure 4).

The temperature rise during the heating period is the result of a combination of the heating of the sample cell by the introduced energy and the heat exchange between the sample cell and its environment caused by the non-ideal adiabatic condition; the latter will lead to some error in the measurement results. In order to correct this error, lines li and li + 1 are extrapolated to intersect with the vertical line of the time axis at the middle point between the beginning and the end of the heating time] (Figure 4, ${\tau }_2=\left({\tau }_1+{\tau }_3\right)/2$). The distance between the two crossing points is the corrected temperature rise, $\mathrm{\Delta }T$, which is just the temperature rise caused by the heat energy introduced during the heating period. This correction is performed through extending lines l_i and l_i + 1, which are obtained when determining the start of the equilibrium temperature.

Introducing $\mathrm{\Delta }T$ into Eq. (1) produces, C_p, which is the heat capacity value at the temperature of (Ti + Ti₊₁)/2 (see Figure 4). The processing procedures are shown in Figure 5.

Figure 5.

Block diagram of acquisition and processing for heat-capacity data controlled by computer.

2.2.4. Adiabatic environment control module

The premise of good adiabatic conditions is to keep the temperatures of the inner and outer adiabatic shields close to that of the sample cell. In order to do this the heating current introduced into the sample cell is gradually and smoothly increased in the initial period, keeping it at a constant value in the middle period and then decreasing it in the final period. If the temperatures of the inner and outer adiabatic shields are kept increasing synchronously with that of the sample cell, the temperature of sample cell will decrease after the heating period and the speed of the temperature decrease will vary with the species, mass, heat conductivity of the samples and the temperature range of the measurement because of the uneven distribution of the interior temperature of the cell during the heating period. As a result the temperature of the inner shield will become higher than that of the sample cell; this will influence the calculated heat capacity. This system can be considered as an intelligent control of the temperatures of the inner and outer adiabatic shields, that is, it corrects the heating current of the inner adiabatic shield during the latter heating period according to the thermal properties of the sample and the actual condition of the measurement in the corresponding temperature range and controls the temperature of the inner shield at a slightly lower temperature than that of the sample cell to avoid the over regulation of temperature of the inner adiabatic shield, especially for samples with small heat conductivities or samples with phase transitions.

2.2.5. The module of setting and revision of operation conditions and data displaying

This system refreshes the screen every time it collects data, displaying in real time the various parameters and states, such as, the electric energy introduced into the sample cell, the temperature of the sample cell, the adiabatic control condition and the environment temperature.

The measuring conditions can be set on the screen before the measurement and revised on the screen during the measurement. At the same time information can be displayed, such as, the heat capacity of the sample which might vary with the temperature and the occurrence of a phase transition, so as to understand the change of thermal properties of the sample at anytime. The parameters and states mentioned above can be displayed on the screen at the same time and can be processed because the software of the system is developed under a multi-file application program with a multi-channel module.

2.3. Calibration of the calorimeter and discussion of results

The reliability of the constructed adiabatic calorimetric system was verified by measuring the molar heat capacities of synthetic sapphire (α-Al₂O₃, Standard Reference Material 720).The results are listed in Table 1. In order to compare the values with those recommended by NIST [25], we calculated the molar heat capacities of α-Al₂O₃ in the temperature range of (80–400) K at intervals of 10 K using a non-linear insert method based on the measured molar heat capacity data. The results are listed in Table 2 and shown in Figure 6, from which it can be seen that the deviations of our values from the recommended values are within ± 0.1%, which indicates that the performance of the constructed calorimetric apparatus has been improved compared with previous calorimeters.

T (K)	Cp (J K^−1 mol^−1)	T (K)	Cp (J K^−1mol^−1)	T (K)	Cp (J K^−1mol^−1)
78.636	6.377	159.716	35.898	280.221	74.988
79.621	6.725	163.370	37.371	283.636	76.003
80.914	7.105	166.940	38.836	286.970	76.623
82.612	7.649	170.434	40.202	289.848	77.225
84.261	8.043	173.857	41.462	292.652	78.015
85.868	8.526	177.215	42.745	295.379	78.494
87.435	9.002	180.512	43.985	298.106	79.019
88.968	9.467	183.752	45.191	301.288	79.646
90.466	9.920	186.939	46.442	304.545	80.502
91.933	10.366	190.075	47.587	307.229	80.953
93.370	10.812	193.163	48.720	309.918	81.498
94.780	11.264	196.591	49.964	312.585	82.032
96.163	11.722	200.349	51.294	315.238	82.527
97.522	12.178	204.043	52.561	317.878	83.033
98.858	12.627	207.679	53.872	320.502	83.476
100.171	13.065	211.258	55.055	323.493	84.108
101.464	13.501	214.781	56.284	326.855	84.726
102.736	13.952	221.677	58.482	330.201	85.325
103.990	14.438	225.053	59.618	333.529	86.152
106.588	15.363	228.384	60.716	336.818	86.670
110.464	16.756	231.671	61.722	340.706	87.329
114.184	18.093	234.923	62.690	345.119	88.148
119.983	20.085	238.140	63.684	349.510	88.825
120.933	20.668	241.288	64.568	353.864	89.563
123.067	21.594	244.470	65.503	358.182	90.249
126.341	22.851	247.582	66.492	362.435	90.734
129.520	24.083	250.679	67.275	366.655	91.608
132.614	25.297	253.746	68.197	370.843	92.381
135.628	26.489	256.786	69.051	374.999	93.160
138.569	27.649	259.773	69.865	378.887	93.546
141.441	28.771	262.804	70.671	383.002	94.013
144.251	29.854	265.768	71.443	387.425	94.611
147.308	31.010	268.706	72.194	391.816	95.131
149.304	32.036	271.620	72.936	396.207	95.735
152.497	33.269	274.509	73.667	400.363	96.183
155.971	34.693	277.377	74.360

Table 1.

Experimental molar heat capacities ofα-Al₂O₃ (M = 101.96 g.Mol⁻¹).

T (K)	Cp (Fit) (J K^−1 mol^−1)	Cp (NIST) (J K^−1 mol^−1)	δ* (%)	T (K)	Cp (Fit) (J K^−1 mol^−1)	Cp (NIST) (J K^−1 mol^−1)	δ* (%)
80	6.901	6.90	0.01	250	67.08	67.06	0.03
90	9.678	9.67	0.08	260	69.82	69.80	0.03
100	12.85	12.84	0.08	270	72.42	72.41	0.01
110	16.34	16.34	0.00	280	74.87	74.88	−0.01
120	20.07	20.07	0.00	290	77.20	77.23	−0.04
130	23.95	23.95	0.00	300	79.41	79.45	−0.05
140	27.93	27.93	0.00	310	81.51	81.56	−0.06
150	31.95	31.94	0.03	320	83.49	83.55	−0.07
160	35.95	35.94	0.03	330	85.37	85.44	−0.08
170	39.90	39.89	0.03	340	87.16	87.23	−0.08
180	43.75	43.74	0.02	350	88.84	88.92	−0.09
190	47.50	47.50	0.00	360	90.45	90.52	−0.08
200	51.12	51.12	0.00	370	91.97	92.04	−0.08
210	54.61	54.61	0.00	380	93.41	93.48	−0.07
220	57.95	57.95	0.00	390	94.91	94.84	0.07
230	61.14	61.14	0.00	400	96.18	96.14	0.04
240	64.18	64.17	0.02

Table 2.

Comparison of experimental molar heat capacities of α-Al₂O₃ with the recommended values by NIST, *δ = 100·(C_p (Fit) - C_p (NIST))/C_p (NIST). δ is the deviation of the fit value of the experimental molar heat capacities from the recommended values by NIST.

Figure 6.

Plot of deviations 100·(C_p (fit) - C_p (NIST)))/C_p (NIST) of our results for the molar heat capacities ofα-Al₂O₃ from the recommended values by NIST, where C_p (fit) denotes the fit value of our experimental molar heat capacities, C_p (NIST) denotes the recommended values by NIST.

Compared with the previous calorimetric system, the newly improved system has the advantages of: compaction; is a simplified device, exhibits great stability and precision; and operates at a higher intellectual level with greater software power than previous reported calorimeters. After operating and testing the equipment for one and a half years we can confirm that the calorimetric system is: easy to operate; performs in a stable manner; and is able to perform with complete automatic control which includes data processing. All the controlling and measuring procedures can be accomplished through the computer after the sample is loaded in the calorimeter cell. The calorimetric apparatus is now being commercially manufactured.

3. Thermodynamic study on functional materials by adiabatic colorimeter

3.1. Heat capacity and thermodynamic properties of novel ionic liquid 1-ethyl-3-methylimidazolium tetracyanoborate [EMIM] [TCB]

3.1.1. Introduction

During the past decade ionic liquids (ILs) have attracted increasing attention for several reasons. The most striking property is their very low vapor pressure, which suggests their applications as ideal solvents to replace conventional solvents in the frame of “green chemistry.” Their highly polar character opens new ways for chemical reactions in homogeneous as well as in biphasic catalyst systems. Special selective solubility for particular components in fluid mixtures give them the potential for use in separation processes. Moreover, properties such as high inherent conductivities, good thermal stability and liquidity over a wide temperature range, opens the way for ILs to be considered as lubricants, thermofluids, plasticizer and electrically conductive liquids in electrochemistry [26] However, the focus by many scientists has been on synthetic, applications in organic chemistry, electrochemistry, and in catalysis, [27, 28, 29, 30, 31, 32, 33] while few researchers have worked on the fundamental thermodynamic properties of ILs [26], [34, 35, 36, 37, 38, 39, 40, 41] We believe that this has limited the development of using ILs in industry and in the laboratory, and has led us to systematically investigate the thermodynamic properties of ILs.

The novel ionic liquid 1-ethyl-3-methylimidazolium tetracyanoborate ([EMIM] [TCB]) has one of the lowest reported viscosities among ILs. In response to the need for stable hydrophobic ionic liquids, as well as the continuing search for novel materials with technically-relevant properties, Merck KGaA has pursued the development of ionic liquid systems based on the tetracyanoborate (TCB) [42] and tris(pentafluoroethyl)trifluorophosphate (FAP) [43] anions. The resultant IL, [EMIM] [TCB], combines high electrochemical stability with low viscosity; thus providing an ideal ionic liquid for various kinds of electrochemical applications, especially in electrolyte formulations. In addition, its polar nature enables the selective extraction of small polar molecules from aqueous media, like butanol from a fermentation broth.31 Although the novel ionic liquid is very useful in many fields, some of its basic thermodynamic properties are unknown. [34]. As a continuation of our series of research on thermodynamic properties of ionic liquids [34, 38] we have investigated the thermodynamic properties of [EMIM][TCB] including the heat capacity, melting temperature, entropy and enthalpy of fusion, and thermostability by adiabatic calorimetry (AC) and thermogravimetric analytic technique (TG-DTG).

3.1.2. Material of the ionic liquid sample and TG analysis

The ionic liquid, 1-ethyl-3-methylimidazolium tetracyanoborate [C₁₀H₁₁BN₆, CAS No. 742099–80-5] was donated by Merck KGaA with labeled purity of 99.9% mass fraction and batch No.S5202031. The clear, colorless, adhesive, liquid sample was transported by an injector and dried under vacuum for 1 day at T = 343 K before the calorimetric measurements were made. The structural formula of the sample is shown in Figure 7.

Figure 7.

Structural formula of 1-ethyl-3-methylimidazolium tetracyanoborate ([EMIM] [TCB]) ionic liquid.

The thermogravimetric (TG) measurements of the sample were carried out by a Thermogravimetric analyzer (Model: Setaram setsys 16/18, SETARAM, France) under high purity argon with a flow rate of 85 ml⋅min⁻¹ at the heating rate of 10 K⋅min⁻¹ from 300 to 1000 K. The sample mass of 45.65 mg was filled into alumina crucible with cover.

From the TG-DTG curve in Figure 8, it can be seen that the mass loss of the sample was completed in a single step. The [EMIM][TCB] sample was stable below 570 K. It begins to lose weight at 592.83 K, reaching a maximum rate of weight loss at 677.72 K and completely lost its weight when the temperature reached 791.03 K.

Figure 8.

TG-DTG curve of [EMIM][TCB] under high purity argon.

3.1.3. Heat capacity measurements

The heat capacity measurements were carried out in the high-precision automated adiabatic calorimeter mentioned above. The [EMIM] [TCB] sample mass used for the heat capacity measurement was 4.08282 g, which is equivalent to 18.062 mmol based on its molar mass of 226.047 g⋅mol⁻¹.

Experimental molar heat capacities of [EMIM][TCB] measured by the adiabatic calorimeter over the temperature range from 78 to 370 K are listed in Table 3 and plotted in Figure 9. From the Figure, a phase transition was observed at the peak temperature of 283.123 K. According to its reported melting point 286.15 K (MerkK GaA, MSDS) this transition corresponds to a solid–liquid phase change.

T /K	$C_{p,\mathit{m}}^0$/J·K^−1·mol^−111	T/K	$C_{p,\mathit{m}}^0$/J·K^−1·mol^−1	T/K	$C_{p,\mathit{m}}^0$/J·K^−1·mol^−1
Series 1 (from 78 to 370 K)
77.927	146.085	177.977	241.097	277.4682	555.844
79.764	148.203	179.839	243.870	279.087	767.118
81.937	150.983	181.735	246.025	280.419	1202.296
83.884	152.847	183.669	246.969	281.389	1903.955
85.792	155.052	185.587	249.368	281.965	3018.912
87.718	157.914	187.499	252.239	282.399	5399.792
89.635	159.949	189.397	254.425	282.734	5575.762
91.542	161.869	191.284	256.181	282.874	7564.957
93.467	163.909	193.154	258.871	283.092	18761.467
95.387	165.461	195.014	260.989	283.252	7044.798
97.295	167.908	196.902	263.212	284.307	591.611
99.207	169.054	198.825	265.888	286.576	415.399
101.872	171.515	200.738	268.572	287.845	411.977
104.544	175.164	203.085	270.781	290.772	411.977
106.458	176.259	205.410	273.551	293.390	412.401
108.385	178.515	207.274	275.657	295.463	412.949
110.292	180.116	209.130	278.699	297.539	411.530
112.211	181.765	211.039	280.437	299.615	412.321
114.147	183.947	213.004	282.428	301.688	412.158
116.064	184.777	214.959	284.195	303.756	412.836
117.953	186.418	216.904	286.319	305.827	412.703
119.862	189.272	218.842	288.634	307.894	412.786
121.790	190.890	220.770	290.950	309.958	413.649
123.696	192.142	222.689	293.965	312.022	414.143
125.580	194.343	224.603	296.706	314.083	414.797
127.486	195.460	226.505	298.783	316.143	415.195
129.403	197.570	228.393	302.507	318.200	415.380
131.309	199.620	230.268	305.150	320.255	415.469
133.195	200.338	232.182	307.864	322.307	416.111
135.096	202.129	234.157	309.324	324.357	417.116
137.021	203.775	236.133	311.267	326.407	416.497
138.924	205.730	238.103	313.130	328.452	416.062
140.817	206.818	240.060	316.506	330.493	417.738
142.689	208.471	242.369	317.531	332.537	418.451
144.581	211.013	244.629	319.621	334.575	418.810
146.497	212.679	246.494	321.418	336.611	420.356
148.391	213.957	248.351	323.883	338.648	421.073
150.275	215.662	250.275	327.124	340.680	422.044
152.701	217.712	252.267	330.913	342.714	422.640
155.148	220.702	254.246	334.647	344.743	421.688
157.060	221.969	256.213	337.673	346.769	422.576
158.957	223.435	258.168	341.429	348.795	423.433
160.842	225.899	260.113	346.133	350.823	423.405
162.717	225.968	262.048	351.913	352.846	424.452
164.624	228.546	263.977	358.940	354.871	425.316
166.570	230.426	265.896	365.659	356.888	427.998
168.501	232.637	267.794	376.041	358.907	427.481
170.422	234.547	269.819	385.715	360.912	427.964
172.328	236.398	271.924	389.540	362.920	429.779
174.224	238.394	273.809	428.291	364.928	429.515
176.109	239.032	275.671	483.464	366.927	432.775
Series 2 (from 200 to 350 K)
200.914	263.743	263.694	356.567	305.827	412.703
204.523	267.795	264.853	357.329	309.958	413.649
208.166	272.154	265.489	365.472	312.022	414.143
211.126	275.978	268.275	379.717	315.143	415.195
214.070	279.667	271.734	389.851	318.200	415.380
216.988	282.792	273.883	444.189	321.307	416.111
219.952	285.992	275.895	506.737	324.357	417.116
222.955	289.335	277.703	618.242	327.452	418.062
225.939	293.441	279.236	832.848	330.493	418.738
228.900	294.685	280.434	1224.335	333.575	418.810
231.807	298.703	281.294	1876.568	336.611	420.356
234.776	302.820	281.897	2768.224	339.680	421.044
237.799	304.937	282.310	3848.881	342.714	422.140
240.796	309.951	282.603	5161.454	345.769	422.576
241.316	312.567	282.820	6533.372	348.795	423.433
243.839	317.567	282.982	7973.548	351.846	424.452
246.762	321.567	283.106	9917.953	354.871	425.316
249.985	324.567	283.295	5149.314	357.907	426.481
251.862	330.829	284.559	409.393	360.912	427.964
254.943	336.749	286.799	411.977	363.928	429.015
257.427	339.322	290.762	411.976	366.927	432.975
259.972	342.567	294.390	411.989	369.927	435.075
261.233	347.567	297.539	411.530
262.148	349.567	301.688	412.158
Series 3 (from 200 to 340 K)
198.627	222.413	249.208	255.056	288.134	347.592
202.314	221.805	252.242	273.365	292.152	371.843
206.065	216.489	255.264	277.024	295.213	332.434
209.052	224.270	258.244	268.206	298.368	419.994
212.132	231.179	261.148	266.542	301.254	419.994
215.313	174.192	264.050	273.986	305.664	382.918
217.887	199.884	266.864	294.272	309.117	265.313
220.719	245.593	269.792	307.914	312.366	277.570
223.749	232.252	272.608	317.557	315.485	259.491
226.696	240.415	275.334	390.096	318.765	223.573
229.815	243.594	278.062	510.599	321.536	285.323
232.774	255.469	280.873	462.126	324.117	471.394
235.826	269153	282.575	8988.111	328.883	200.130
238.890	260902	282.990	9847.518	331.993	462.769
242.563	262.842	283.172	10867.388	335.827	176.378
246.192	265.801	284.767	483.962

Table 3.

Experimental molar heat capacities of [EMIM][TCB] (M = 226.047 g·Mol⁻¹).

Figure 9.

Experimental molar heat capacity of [EMIM][TCB] as a function of temperature: outer part from 78 to 370 K for the first series of measurements in the whole temperature range; inner part, from 200 to 350 K of three series of measurements in the melting process.

The values of experimental heat capacities were fitted to the following polynomial equations using least square method: [44, 45]. For the solid phase over the temperature range 78 to 275 K:

$$C_{p,m}^0/\mathrm{J}\cdot {\mathrm{K}}^{-1}\cdot {\mathrm{mol}}^{-1}=239.740+111.820\mathrm{x}+58.242{\mathrm{x}}^2–65.454{\mathrm{x}}^3–146.940{\mathrm{x}}^4+88.43{\text{3x}}^5+133.050{\mathrm{x}}^6$$E4

where x is the reduced temperature x = [T – (T max + T min) / 2] / [(T max – T min) / 2], T is the experimental temperature, thus, in the solid state (78 to 275 K), x = [(T / K) – 176.5] / 98.5, T max is the upper limit (275 K) and T min is the lower limit (78 K) of the above temperature region. The correlation coefficient of the fitting R² = 0.9984.

For the liquid phase in the temperature range from 285 to 370 K:

$${C_{p,m}^0}_{/}\mathrm{J}\cdot {\mathrm{K}}^{-1}\cdot {\mathrm{mol}}^{-1}=417.200+10.749x+6.957x^2–0.848x^3–12.377x^4+0.277x^5+13.870x^6$$E5

where x is the reduced temperature, x = [(T/K) − 327.5]/42.5, T is the experimental temperature, 327.5 was obtained from polynomial $\left(T_{\max }+T_{\min }\right)/2$, and the 42.5 was obtained from the polynomial $\left(T_{\max }-T_{\min }\right)/2$. Tmax and Tmin are the upper (370 K) and lower (285 K) limit temperature respectively. The correlation coefficient of the fitting R² = 0.9872.

3.1.4. The temperature, enthalpy and entropy of solid: liquid phase transition

The standard molar enthalpies and entropies of the solid–liquid phase transition ${∆}_{\mathrm{fus}}{\mathrm{H}}_{\mathrm{m}}^0$ and ${∆}_{\mathrm{fus}}{\mathrm{S}}_{\mathrm{m}}^0$ of the compound were derived according to the following equations:

$${\mathrm{∆}}_{\mathit{fus}}{H}_m^0=\frac{Q-n{\int }_{T_i}^{{\mathrm{ }T}_m}{C}_{p,m}^0\left(s\right)\mathit{dT}-n{\int }_{T_i}^{{\mathrm{ }T}_m}{C}_{p,m}^0\left(l\right)\mathit{dT}-{\int }_{T_i}^{{\mathrm{ }T}_m}{H}^0\left(s\right)\mathit{dT}}{n}$$E6

$${∆}_{\mathit{fus}}{S}_m^0=\frac{{∆}_{\mathit{fus}}{H}_m^0}{T_m}$$E7

where T_i is the temperature that is somewhat lower than the temperature of the onset of a solid–liquid transition and Tf is the temperature slightly higher than that of the transition completion. Q the total energy introduced into the sample cell from T_i to T_f,H₀ the standard heat capacity of the sample cell from T_i to T_f, ${\mathit{C}}_{p,\mathrm{m}}^0$(s) the standard heat capacity of the sample in solid phase from T_i to T_m, $C_{p,\mathrm{m}}^0$(l) the standard heat capacity of the sample in liquid phase from T_m to T_f and n is molar amount of the sample. The heat capacity polynomials mentioned above were used to calculate the smoothed heat capacities, and were numerically integrated to obtain the values of the standard thermodynamic functions above T = 298.15 K. The calculated results of molar enthalpy and entropy of fusion obtained from the three series of heat-capacity were listed in Table 4.

No	Melting temperature Tm /K	${\mathrm{∆}}_{\mathrm{fus}}{H}_{\mathrm{m}}^0$/ kJ·mol^−1	${\mathrm{∆}}_{\mathrm{fus}}{\mathit{S}}_{\mathrm{m}}^0$/J·K^−1·mol^−1
1	283.092	12.957	45.770
2	283.106	12.985	45.867
3	283.172	12.976	45.825
Mean Value	283.123 ± 0.025	12.973 ± 0.008	45.821 ± 0.028

Table 4.

The melting temperature, enthalpy and entropy of fusion of [EMIM][TCB] obtained from three series of heat-capacity measurements.

3.1.5. Thermodynamic functions

The thermodynamic functions of the [EMIM][TCB] relative to the reference temperature 298.15 K were calculated in the temperature range from 80 to 370 K with an interval of 5 K, using the polynomial equation of heat capacity and thermodynamic relationships as follows:

Before melting,

$$H_T^0-H_{298.15}^0={\int }_{298.15}^{\mathrm{ }T}{C}_{p,\mathrm{m}}^0\left(\mathrm{s}\right)dT$$E8

$$S_T^0\mathbf{-}{S}_{298.15}^0={\int }_{298.15}^{\mathrm{ }T}\frac{C_{p,\mathrm{m}}^0\left(\mathrm{s}\right)}{T}dT$$E9

After melting,

$$H_T^0-H_{298.15}^0={\int }_{298.15}^{T_{\mathrm{i}}}{C}_{p,\mathrm{m}}^0\left(\mathrm{s}\right)dT+{\mathrm{∆}}_{\mathrm{fus}}{H}_{\mathrm{m}}^0+{\int }_{T_{\mathrm{f}}}^{\mathrm{ }T}{C}_{p,\mathrm{m}}^0\left(\mathrm{l}\right)\mathit{dT}$$E10

$${\mathrm{S}}_{\mathrm{T}}^0\mathbf{-}{\mathrm{S}}_{298.15}^0={\int }_{298.15}^{{\mathrm{ T}}_{\mathrm{i}}}\left[\frac{{\mathrm{C}}_{\mathrm{p},\mathrm{m}}^0\left(\mathrm{s}\right)}{T}\right]\mathit{dT}\mathbf{+}\frac{{\mathrm{∆}}_{\mathrm{fus}}{\mathrm{H}}_{\mathrm{m}}^0}{{\mathrm{T}}_{\mathrm{m}}}\mathbf{+}{\int }_{{\mathrm{T}}_{\mathrm{f}}}^{\mathrm{ T}}\left[\frac{{\mathrm{C}}_{\mathrm{p},\mathrm{m}}^0\left(\mathrm{l}\right)}{T}\right]\mathit{dT}\mathit{.}$$E11

where T_i is the temperature at which the solid–liquid phase transition started; T_f is the temperature at which the solid–liquid phase transition ended; ${\mathrm{∆}}_{\mathrm{fus}}{H}_{\mathrm{m}}^0$ is the standard molar enthalpy of fusion; T_m is the temperature of solid–liquid phase transition. The standard thermodynamic functions, [$H_T^0-H_{298.15}^0$], [$S_T^0-S_{298.15}^0$], are listed in Table 5.

T/K	$C_{p,\mathrm{m}}^0$/ J·K^−1·mol^−1	${\mathit{H}}_T^0-H_{298.15}^0$/kJ·mol^−1	$S_T^0-S_{298.15}^0$/ J·K^−1·mol^−1
80	150.104	−70.915	−360.705
90	158.233	−69.378	−342.560
100	169.437	−67.740	−325.218
110	180.604	−65.989	−308.533
120	190.456	−64.133	−292.444
130	198.919	−62.185	−276.919
140	206.588	−60.157	−261.921
150	214.303	−58.053	−247.393
160	222.826	−55.868	−233.258
170	232.631	−53.592	−219.424
180	243.784	−51.211	−205.797
190	255.944	−48.713	−192.298
200	268.461	−46.091	−178.874
210	280.574	−43.345	−165.506
220	291.727	−40.483	−152.208
230	301.977	−37.514	−139.010
240	312.513	−34.443	−125.924
250	326.284	−31.253	−112.889
260	348.719	−27.888	−99.696
270	388.568	−24.221	−85.874
280	Melting
290	412.609	−5.282	−18.601
298.15	412.020	0.000	0.000
300	412.204	1.385	4.868
310	413.721	10.475	36.838
320	415.513	23.248	81.985
330	417.856	41.426	146.718
340	420.859	67.316	239.595
350	424.059	103.928	371.805
360	427.723	155.130	557.707
370	435.829	225.809	815.441

Table 5.

Calculated thermodynamic functions of [EMIM][TCB].

3.2. Heat capacity and thermodynamic properties of nanostructured materials

3.2.1. Introduction

Nanostructured materials have attracted worldwide attention owing to their special properties. Due to their small grain size and large specific surface, nano materials exhibit many distinctive properties [46]. What are the special thermodynamic properties of nano materials? Can classical thermodynamic theories be used to explain the thermal behavior of nano- materials? These are some of the important questions that must be answered in order to understand the properties of nano- materials more thoroughly and broaden their application areas.

In this chapter we have reported the results of heat capacity measurements of several kinds of nanostructured oxides, metals and zeolites, obtained by low-temperature adiabatic calorimetry, and compared heat capacity enhancement in these materials with the corresponding coarse-grained materials. These data are discussed in the context of properties such as density, thermal expansion, sample purity, surface effect, and size effect. Synthesis of nano materials has been accompanied by adiabatic calorimetry measurements, and materials have been characterized with differential scanning calorimetry (DSC), thermogravimetric (TG) analysis, thermal expansion coefficient measurements, X-ray diffraction (XRD), transitional electron microscopy (TEM), scanning electron microscopy (SEM), X-ray fluorescence (XRF) and infrared spectroscopy (IR). Full details about the synthesis and characterization of materials were published elsewhere [47].

3.2.2. Nanostructured oxides

Nano oxide materials constitute a rich source of materials. We selected five kinds of oxide materials, Al₂O₃, SiO₂, TiO₂, ZnO₂, and ZrO₂, which have been widely used, can be prepared by classical methods and obtained with confined size range and high quality.

3.2.2.1. Nano Al₂O₃

We studied molar heat capacity of nano Al₂O₃ in the temperature range from 78 to 370 K, and compared with the coarse-grained Al₂O₃ [48]. The nanopowder Al₂O₃ was processed by hydrolysis of pure aluminum sheet after activation, and the sample purity is more than 99%. The coarse-grained sample of α- Al₂O₃ is a commercial reagent purchased from Shanghai Chemical Reagent factory with the mass purity of 99.9%. Figure 10 shows the experimental results indicating that no thermal anomaly took place over the investigated temperature range, but the heat capacities of the nano Al₂O₃ was larger than the coarse-grained one and increased with the size decreased. The nano Al₂O₃ has excess heat capacity from 6 to 23% as comparing with the coarse-grained one in the temperature range from 200 to 370 K. In the study of infrared spectra, we found that nano Al₂O₃ exhibited a blue shift in wave number. This shift indicates that energy structure of nano Al₂O₃ is higher than that in coarse-grained state, which is in agreement with the results of heat capacity measurement. To further study the enhancement of heat capacity in nano Al₂O₃, we measured the density of nano Al₂O₃ to be 89% of the coarse-grained one, and thermal expansion of nano Al₂O₃ has been reported to be twice as that of the conventional. All these suggest that the grain boundary of nano materials possesses an excess volume with respect to the perfect crystal lattice, so it seems that the heat capacity enhancement in nano Al₂O₃ results from the excess volume.

Figure 10.

Heat capacity of nano and coarse-grained Al₂O₃.

3.2.2.2. Nano amorphous SiO₂

The molar heat capacity of nano amorphous SiO₂ (na-SiO₂) was measured over the temperature range from 9 to 354 K. The samples used for experiment were synthesized by using the sol–gel route with hydrolyzing the ethyl tetrasilicate and controlling the chemical reaction conditions. Those samples possess a very high purity (>99.9%). The experimental results were plotted in Figure 11 together with the molar heat capacity of coarse-grained SiO₂ (ca- SiO₂). The average grain size of two amorphous SiO₂ is also 20 nm and their specific surfaces resulted from BET measurement are 160 m²/g (SiO₂–1) and 640 m²/g (SiO₂–2) respectively. Significant difference in heat capacity between na-SiO₂ and ca- SiO₂ can be identified from Figure 11. The heat capacity enhancement from 150 to 350 K for na- SiO₂–1 and na-SiO₂–2 are about 2–7% and 4–10% higher than those of ca-SiO_2, respectively. The heat capacity values of na-SiO₂–2 with larger specific surface are higher about 3% than those of na-SiO₂–1. The heat capacity enhancements in the nanomaterials are usually associated with an increase in the configuration and vibrational entropy of grain boundaries, and the boundaries with larger specific surface will have more configuration and vibrational entropy. So it agrees well with the experimental results that larger grain surface has much contribution to the heat capacity enhancement. We calculated the thermodynamic functions of na-SiO₂ based on the heat capacity data. The calculated results were plotted in the Figure 12. From the figure, we can conclude that the entropy, enthalpy and Gibbs free energy of larger specific surface na-SiO₂ is higher than those of the small one, and the Gibbs free energy is lower, implying larger specific surface materials have complicated disorder, large potential energy and high activity.

Figure 11.

Heat capacity of nano amorphous and coarse-grained SiO₂ as functions of temperature.

Figure 12.

Entropy, enthalpy and Gibbs free energy of nano amorphous SiO₂ as functions of temperature.

3.2.2.3. Nanocrystalline ZnO

The two nanocrystalline forms of ZnO studied are ZnO-1 and ZnO-2 with grain size of 65 and 18 nm, respectively. The purity of both two samples is more than 99%. Heat capacity of nanocrystalline ZnO was compared with the literature data [49] of coarse-grained ZnO (c-ZnO) in Figure 13. It can be seen that the heat capacities of ZnO-1 is no obviously difference from that of c-ZnO. However, there is large excess heat capacity of 4–17% for ZnO-2 compared with c-ZnO. The similar result was also reported by other researchers. Heat capacity of a material is directly related to its atomic structure, or its vibrational and configurational entropy which is significantly affected by the nearest-neighbor configurations. Nanocrystals are structurally characterized by the ultrafine crystalline grains, and a large fraction of atoms located in the metastable grain boundaries in which the nearest-neighbor configurations are much different from those inside the crystallites. In other words, the grain-boundary possesses an excess volume with respect to the perfect crystal lattice. Therefore, heat capacities of nanocrystals are higher than those of the corresponding coarse-grained polycrystalline counterparts. Although slight impurity can enhance the heat capacity obviously [50], the impurity effect on those two specimens should be very slight. The samples were heated at temperature up to 570 K for 2 h and sample cells were evacuated to be high vacuum (10⁻⁵ Pa), which can remove the absorbed gas and vapor. So the main contribution of the excess heat capacity of nanocrystaliline ZnO-2 should be introduced by vibrational and configurational entropy due to grain boundaries and lattice defects.

Figure 13.

Heat capacity of nanocrystalline ZnO and the literature heat capacity data of coarse-grained crystalline ZnO.

It seems to contradict our understanding of the above excess heat capacity, that nanocrystalline ZnO-1 and the more coarse-grained ZnO display very little difference. In fact, the grain size effect of nanocrystals on heat capacity has a size limit [50]. If the grain size is lower than the limit, the heat capacity will exhibit a great increase. Otherwise, heat capacity of nanocrystals and conventional polycrystals has little difference.

3.2.2.4. Nanocrystalline TiO₂

We measured heat capacity of nanocrystalline TiO₂ with three grain sizes by adiabatic calorimetry. TiO₂–2 and TiO₂–3 are anatase phase with the purity of 99% and TiO₂–1 is mainly anatase with a small amount of brookite phase. The experimental results were compared with reported heat capacity of coarse-grained anatase phase TiO₂ [51] in Figure 14. It is very obvious that the heat capacity of nanocrystalline was enhanced, and the heat capacities increase with grain size decreasing. The heat capacity enhancement of TiO₂–1 and TiO₂–2 was plotted in Figure 14. In the temperature range from 100 to 300 K, the heat capacity enhancement of TiO₂–1 and TiO₂–2 were 7–13% and 4–7%, respectively. The heat capacity enhancement of TiO₂–1 relative to TiO₂–2 was 3–6%, while the enhancement of TiO₂–2 relative to TiO₂–3 was only about 1%. Considered the size decreasing step is equal from TiO₂–3 to TiO₂–2 and from TiO₂–2 to TiO₂–1, the nanocrystalline size is not the main factor affected the heat capacity enhancement in this case. The sample of TiO₂–1 contains mainly anatase phase with a small amount of brookite phase and the samples of TiO₂–2 and TiO₂–3 are all anatase phase, so we can draw a conclusion that the small amount of heteromorphic impurity makes more contribution to the heat capacity enhancement than the grain size. Recently research work by Boerio-Goats et al. reported that the water or other solvents absorbed on nanoparticle surfaces lead to heat capacity enhancement of anatase phase nanopartiles [52] (Figures 15–17).

Figure 14.

Heat capacity of anatase phase nanocrystalline TiO₂ with different grain sizes.

Figure 15.

Heat capacity enhancement of nanocrystalline TiO₂ as a function of temperature, δC_p,m (%) = 100%*[C_p,m(nano) – C_p,m(coarse)]/C_p,m(coarse).

Figure 16.

Heat capacity of nanocrystalline ZrO₂ and the literature heat capacity data of coarse-grained crystalline ZrO₂.

Figure 17.

Heat capacity of nanocrystalline nickel and the literature heat capacity data of coarse-grained crystalline nickel, insert is heat capacity enhancement of nanocrystalline nickel.

3.2.2.5. Nanocrystalline ZrO₂

Nanocrystalline ZrO₂ with grain size of 18 nm was measured by adiabatic heat capacity calorimetry and compared with literature data of coarse-grained ZrO₂ [53]. The sample was prepared with the method of azeotropic distillation, and the purity is more than 99%. The heat capacity enhancement of nanocrystalline ZrO₂ was much larger than those of above nanostructured oxides. The enhancement was about 2–21% in the temperature range from 100 to 300 K, and exhibited a rising tendency with the temperature increasing. Many researchers theoretically explained the excess heat capacity of nano materials by excess volume, and some theoretical calculations have indicated that heat capacity enhancement sharply increases with the excess volume increasing when temperature rises [54]. We measured the density of the nanocrystalline ZrO₂ sample (5.2 g·cm³) to be 93% of the coarse-grained ZrO₂ (5.6 g·cm³). This difference in density is not very obvious and can hardly lead to 2–21% of heat capacity enhancement. We also measured the chemical purity of the nanocrystalline ZrO₂ to be 98.4%, so the contribution of impurity contained in the nanocrystalline to heat capacity enhancement cannot be neglected. We presume that heat capacity enhancement in the nanocrystalline ZrO₂ is mainly caused by impurity contained in it. Impurity in nano materials is not the general case of adulteration, since it is not avoided in the process of sample preparation, but it can bring activity to the materials. So nanocrystalline ZrO₂ has higher activity than coarse-grained one and is mostly used as a catalyst in some reactions.

3.2.3. Nanocrystalline metal

Nanocrystalline metals are studied mostly in theory because its molecular structure is simple and easily calculated and explained. Those materials differ from glasses and crystals in the sense that they exhibit little short-range or long-range order. A series of novel physical and chemical properties of the nanocrystals, such as high diffusivity and reactivity, great ductility, large thermal expansion, enhanced phonon specific heat, and a significant change in the magnetic susceptibility, relative to the corresponding coarse-grained polycrystals, have captured the attention of the scientists and engineers because of their potential application. We measured heat capacities of nanocrystalline nickel and copper in the temperature range from 78 K to 370 K, and studied the heat capacity enhancement relative to the corresponding coarse-grained metal crystal. The two samples were produced by Zhengyuan Nano-materials Engineering Corp. (Shandong, China). The labeled chemical purity is not less than 99%.

3.2.3.1. Nanocrystalline nickel

Heat capacity of 40 nm nanocrystalline nickel was plotted in Figure 17 and compared with the literature data [55] of coarse-grained crystalline nickel. From insert in the figure we can see that heat capacity enhancement varies between 2 and 4% in the temperature range from 100 to 370 K. The heat capacity enhancement in nanocrystalline materials are usually associated with an increase in the configurational and vibrational entropy of the grain boundaries, which constitute a large volume fraction of the material. The atomic fraction of the grain-boundary component can be approximately estimated to be 3δ/d, where d is the average size of crystalline grain and δ is the average thickness of interfaces which is known to be on the order of three or four atomic layers. For the nanocrystalline nickel with d = 40 nm, about 10% atoms are on the grain boundaries. Thus, the grain-boundary configurations or the grain-boundary energy should be responsible for the heat capacity enhancement.

3.2.3.2. Nanocrystalline copper

Figure 18 shows the heat capacity of 50 nm nanocrystalline copper and the literature data [56] of coarse-grained one. The heat capacity enhancement is about 3–6% in the temperature range from 100 to 370 K. The purity of nanocrystalline copper is more than 99%, so the contribution of impurity to the enhancement is almost negligible. The relative density of nanocrystalline copper to the coarse-grained is 51% indicating a more open atomic structure of the grain-boundary component than coarse-grained polycrystalline copper, so the interatomic coupling becomes weaker and enhances heat capacity. In the theoretical calculation by Fecht et al., [57], thermal expansion coefficient is related to heat capacity, and the larger thermal expansion coefficient becomes, the more heat capacity enhances. We measured thermal expansion coefficient of nanocrystalline copper (3 × 10⁻⁵ K⁻¹) to be about two times of the coarse-grained copper’s (1.6 × 10⁻⁵ K⁻¹). Thus, we can also explain the heat capacity enhancement of nanocrystalline copper with the increasing thermal expansion coefficient.

Figure 18.

Heat capacity of nanocrystalline copper and the literature heat capacity data of coarse-grained crystalline copper, insert is heat capacity enhancement of nanocrystalline copper.

3.2.4. Nanosized and microsized zeolite

Nanosized zeolite is only different from microsized zeolite in the size, but its properties have varied much in some aspects when it changes into microsized zeolite. We carried out adiabatic heat capacity measurement on nanoszied and microsized ZMS-5, and compared their thermodynamic properties. From Figure 19 it can be clearly seen that the heat capacities of nanosized ZMS-5 are larger than the microsized one. The heat capacity enhancement in the low temperature is not very obvious, but becomes larger with the temperature increasing. Nanosized ZMS-5 possesses excess specific surface and behaves more activity than the microsized. This excess specific surface supplies more surface energy for nanosized ZMS-5 and enhances heat capacity.

Figure 19.

Heat capacity of nanosized and microsized ZSM-5.

4. Conclusions

A fully automated high-precision adiabatic calorimeter used for heat capacity measurement in the temperature range of 80–400 K was constructed. The reliability of the calorimeter was verified by measuring the heat capacities of synthetic sapphire (α-Al₂O₃), Standard Reference Material 720. The deviation of the data obtained by this calorimeter from those published by NIST was within ±0.1% in the temperature range from 80 to 400 K. The adiabatic calorimeter can be used for precise measurement of molar heat capacities of condensed materials with important scientific value.

The heat capacities of IL [EMIM][TCB] were measured over the temperature range from 78 to 370 K by the high-precision-automated adiabatic calorimeter. Based on the heat capacity measurement experiments, the thermodynamic properties of fusion were calculated, and the thermodynamic functions [$H_T^0-H_{298.15}^0$] and [$S_T^0-S_{298.15}^0$] were derived in the range from 78 to 370 K with temperature interval of 5 K. The melting temperature, standard molar enthalpy and entropy of fusion were determined to be (283.123 ± 0.025) K, (12.973 ± 0.008) kJ⋅mol⁻¹ and (45.821 ± 028) J⋅K⁻¹⋅mol⁻¹, respectively. The IL was shown to be thermostable below 570 K and began to lose weight at 592.83 K.

Five kinds of nanostructured oxide materials, Al₂O_3, SiO₂, TiO₂, ZnO₂, ZrO₂, and two kinds of nanocrystalline metals: nickel and copper were investigated from heat capacity measurements. It is found that heat capacity enhancement in nanostructured materials is influenced by many factors, such as density, thermal expansion, sample purity, surface absorption, size effect, and so on. But the dominant factor affected heat capacity enhancement is different in different nanostructured materials. Only with careful and entire investigation on the particular properties of nanostructured materials, we can discuss and analyze the heat capacity enhancement. On the other hand, adiabatic calorimetry is the most direct method to measure heat capacity enhancement in nanostructured materials, however in order to set up thermodynamic theoretical model to describe and understand heat capacity enhancement, more theoretical calculation study and other experimental measurements should be further carried out.

Acknowledgments

This work was financially supported by the National Natural Science Foundation of China under the grant NSFC No.21473198 and No. 20073047. Some parts of this chapter are reproduced from authors’ recent conference publication, work, etc.