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Application of time–temperature–humidity superposition to the mass loss of wood through hygrothermally accelerated ageing at 95–140 °C and different relative humidity levels

  • Nanami Zeniya
  • Eiichi Obataya
  • Kaoru Endo-Ujiie
  • Miyuki Matsuo-Ueda
Research Article
Part of the following topical collections:
  1. 2. Earth and Environmental Sciences (general)


Spruce wood specimens were hygrothermally treated at different temperatures (T, 95–140 °C) and relative humidity during heating (RHh, 0–92%) to measure the loss in dry mass (ML) due to the treatment. The ML was approximated by a power function of the heating duration t, and the plots of ML versus t were successfully superposed as a single master curve by shifting the plots along the t axis using the shift factors aT and aH, representing the effects of T and RHh, respectively. The apparent activation energies calculated from the linear correlation between ln(aT) and the reciprocal of absolute temperature were 109–116 kJ/mol, almost independent of RHh. Plots of aH versus RHh showed sigmoid shapes, suggesting that the aH value depended on the moisture content of the wood. The shift factors allowed the prediction of the ML of wood by hygrothermal treatment at arbitrary T and RHh. The predicted ML values showed good agreement with experimental ML values available in the literature.


Hygrothermal treatment Accelerate ageing Mass loss Shift factor 

1 Introduction

Hygrothermal treatment is one method for the accelerated ageing of wood [16]. The characteristics of aged wood, such as reduced hygroscopicity [14, 35], enhanced stiffness [12, 13, 14, 15, 25, 35], brittleness [12, 13, 35], and darkened color [20], are similar to those obtained by oven-heating and steaming [3, 4, 5, 11, 15, 17, 18, 19, 20, 22, 28, 31]. Therefore, hygrothermal treatment may predict changes in wood properties over long-term ageing at ambient conditions. Accelerated ageing is also attractive for artisans crafting wooden musical instruments, because the acoustic quality of wood is thought to be improved by long-term ageing and the advantageous effects of ageing may be similarly reproduced by hygrothermal treatment [7]. In the same sense, artificially aged wood may be a useful material for the restoration of old wooden cultural properties.

For the precise reproduction of aged wood by hygrothermal treatments, we must determine the effects of the relative humidity during heating (RHh), because humidity affects the thermal degradation of wood constituents in general [11] and natural ageing occurs at ambient temperatures and intermediate relative humidity (RH). However, industrial hydrothermal treatments are usually conducted either in the absence of moisture (0% RHh) or in steam (100% RHh); few investigations have focused on the effects of intermediate RHh [2, 3, 4, 7]. In addition, heating temperature (T) is relatively high (≥ 150 °C) in industrial thermal treatments [11, 16, 31], whereas the chemical reactions in wood induced by heating at ≥ 150 °C are qualitatively different from those at ≤ 130 °C [6]. To realize the true acceleration of ageing, it is necessary to clarify the effects of RHh at lower temperatures.

Several wood properties change non-monotonically upon heating. The Young’s modulus of wood slightly increases initially and then decreases with further heating [3, 5, 7, 22, 28, 29]. The damping coefficient remains almost unchanged by heating in dry conditions, but increases steeply by heating in moist conditions [7]. The equilibrium moisture content (EMC) generally decreases by hygrothermal treatment [4, 23, 32] but begins to increase with prolonged heating [33] or heating in humid conditions [7]. These complicated changes cause difficulties in conducting kinetic analysis such as time–temperature (tT) superposition. On the other hand, the color of wood is a useful parameter reflecting the degree of hygrothermal degradation [19, 20]. In particular, the brightness (L*) value decreases monotonically with heating, and the L*t curves determined at different T are successfully superposed into a single master curve by using a shift factor. This allows the reliable prediction of color changes due to hygrothermal treatment and natural ageing. However, color measurement requires an expensive spectrometer and does not permit prediction of the other physical properties because the relationships between color parameters and physical properties of hygrothermally treated wood remain unclear.

From these considerations above, we focused on the loss in dry mass (ML) as an indicator of thermal degradation. The ML value can be precisely determined without complicated equipment, and it monotonically increases with heating. In addition, the physical properties of hygrothermally treated wood depend strongly on the ML, often independent of the T [3, 4, 7, 22, 28]. Therefore, if we can predict the ML, we can also predict the ML-dependent properties of hygrothermally treated wood.

Although the ML value upon oven-heating (0% RHh) has been frequently measured and analyzed kinetically [8, 21, 22, 32, 34], little information is available for the effects of RHh on the ML. We recently proposed a t–RHh superposition to evaluate the ML at different RHh [7], but in that case, the temperature was limited to 120 °C. In this study, we examined the ML for a wider T range (95–140 °C) to establish a tT–RHh superposition allowing the prediction of ML at arbitrary T and RHh.

2 Materials and methods

2.1 Wood specimens

Sitka spruce wood (Picea sitchensis) selected for harp soundboards was cut into strips measuring 1.6 mm (tangential) × 15 mm (radial) × 120 mm (longitudinal) for use in this study. The average air-dry density of the specimens was 438 kg/m3. To remove the effects of the hygroscopic history during seasoning, the specimens were first moistened at 25 °C and 100% RH for at least 5 days, followed by vacuum drying on P2O5 at 20–25 °C for 1 week. The specimens were then conditioned at 25 °C and 0, 33, 60, 84, or 100% RH for more than 1 month before the hygrothermal treatments described below.

2.2 Hygrothermal treatment

Wood specimens were hygrothermally treated at 120 °C and 140 °C for 1–7 days in an autoclave, equipped with a thermocouple and pressure sensor (PHS-B-500KP, Kyowa Dengyo Co.). The wood specimens previously conditioned at different RH values were placed in the autoclave with various amounts of deionized water depending on the specified RHh, and then the autoclave was tightly closed and heated to the testing temperatures. The temperature and pressure in the autoclave reached the expected levels within 1 h. The RHh was calculated from the water vapor pressure in the autoclave. The specification and performance of the autoclave are detailed in a previous paper [7]. For heating at 95 °C, specimens were treated in a temperature- and humidity-controlled chamber (PHP-2J, ESPEC Co.) for 1–32 days. For heating at 0% RHh, some specimens were heated in an air-circulating oven at 140 °C for 12–47 days to achieve sufficient ML comparable to that obtained by heating in moist conditions. Eight specimens were used for each treatment condition. After the hygrothermal treatments, the specimens were immediately cooled to room temperature (20–25 °C) and vacuum-dried on P2O5 to determine their absolute dry mass. The ML is defined by
$${\text{ML }}\left( {\text{\% }} \right) \equiv 100 \times \frac{{{\text{M}}_{\text{u}} - {\text{M}}_{\text{t}} }}{{{\text{M}}_{\text{u}} }}$$
where Mu and Mt are the absolute dry masses of the unmodified and hygrothermally treated wood specimens, respectively.

2.3 Moisture sorption measurement

The moisture sorption isotherm of unmodified wood was measured at 25 °C to relate the equilibrium moisture content (EMC25) and RH. Absolutely dry wood specimens were placed in a glass desiccator, wherein the RH was increased stepwise by using saturated aqueous solutions of LiCl, CH3COOK, MgCl2, NaCl, KCl, and KNO3 to determine the EMCs of wood at 11, 23, 33, 75, 84, and 94% RH, respectively [9]. For conditioning at 60% RH, a humidity-controlled chamber was used. The wood specimens were conditioned for 1 month at ≤ 33% RH and for more than 2 months at ≥ 60% RH to achieve sufficient mass equilibrium. The EMC is defined by the following equation:
$${\text{EMC }}\left( {\text{\% }} \right) \equiv 100 \times \frac{{{\text{M}}_{\text{H}} - {\text{M}}_{0} }}{{{\text{M}}_{0} }}$$
where the M0 and MH are the masses of a wood specimen in absolutely dry and moistened conditions, respectively.

3 Results

Table 1 lists the T, RHh, and t range employed in this study. Although we planned the RHh values of 35, 60, 85, and 95%, the actual RHh values in the autoclave slightly deviated from these targeted RHh values, probably because of moisture sorption and desorption of the wood during heating as well as the chemical changes in the wood constituents. Hereafter we use the experimentally determined average RHh values of 35, 63, 81, and 92%, respectively.
Table 1

Heating conditions, parameters used for the approximation of ML–t plots obtained at different T and RHh, and shift factor aT used for tT superposition

T (°C)

RHh (%)a

t (day)

k (%/day)


r b

a T c




























60–65 (63)



















72–85 (81)



















91–95 (92)


















aValues in parentheses indicate average values

bCorrelation coefficient in the approximation of ML–t plots with Eq. (3)

cReference temperature is 120 °C

Figure 1 shows the average ML values due to hygrothermal treatment at 63% and 92% RHh as a function of t. Higher temperatures and higher RHh induce faster increases in ML, and the plots of ML versus t are approximated by the following equation:
$${\text{ML}}\left( \% \right) = kt^{b} .$$
This equation is valid for mild heating conditions, i.e., the low ML range (≤ 15%) discussed here. It is not applicable to more severe heating conditions because the ML approaches a constant value as T increases [32]. The parameters k and b for different T–RHh conditions are listed in Table 1. The k values vary widely depending on T and RHh, while the variation in b is relatively small. This suggested that different ML–t curves can be superposed into a single curve by shifting them along the t axis using a shift factor. Assuming that the effect of T can be exchanged with t, we can define a shift factor (aT) representing the effect of temperature as
$$a_{T} \equiv \frac{{t_{T} }}{{t_{ref} }},$$
where tref is the test time at a reference T (Tref) and tT is the time required to yield the same response at the test T. The aT = 1 at Tref; and we select 120 °C as the Tref in the present study. The aT values for 95 °C and 140 °C are determined as the shifted plots are approximated by Eq. (3) with the highest correlation coefficient. The experimentally determined aT values are listed in Table 1, and the results of tT superposition are exhibited in Fig. 2. The plots obtained at different T are successfully superposed into single curves for each RHh.
Fig. 1

Plots of ML versus t for spruce wood hygrothermally treated at different T and RHh. Open plots, hygrothermally treated at 63% RHh; filled plots, hygrothermally treated at 92% RHh; triangles, heated at 95 °C; circles, heated at 120 °C; squares, heated at 140 °C

Fig. 2

Superposed plots of ML versus t/aT for hygrothermally treated spruce wood. Plusses, hygrothermally treated at 0% RHh; circles, hygrothermally treated at 35% RHh; triangles, hygrothermally treated at 63% RHh; squares, hygrothermally treated at 81% RHh; diamonds, hygrothermally treated at 92% RHh

After the tT superposition, the plots are approximated by Eq. (3) again, and the parameters k and b are listed in Table 2. The narrow variation in b values suggests that different curves in Fig. 3 can be further superposed into a single “master” curve. Here we define another shift factor (aH) representing the effect of RHh as
$$a_{H} \equiv \frac{{t_{H} }}{{t_{ref} }},$$
where tref is the test time at a reference RHh (RHhref) and tH is the time required to yield the same response at the test RHh. In the present study, 63% RHh was chosen as RHhref, and the aH values at different RHh were determined by the same manner used to determine aT. The aH values are listed in Table 2 and the results of the t–RHh superposition are exhibited in Fig. 3. The master curve at the reference T (120 °C) and RHh (63%) is expressed by the following equation:
$${\text{ML}}\left( \% \right) = 0.6151 \times t\left( {\text{day}} \right)^{0.7778}\,\left( {r = 0.995} \right).$$
By using aT and aH, that master curve can be re-shifted to predict a ML–t curve at arbitrary T and RHh.
Table 2

Parameters used for the approximation of tT superposed curves at different RHh, and shift factor aH used for t–RHh superposition

T (°C)

RHh (%)a

k (%/day)


r b

a H c































aAverage values

bCorrelation coefficient in the approximation of ML–t/aT plots via Eq. (3)

cReference humidity is 63% RHh

Fig. 3

Superposed plots of ML versus t/aTaH for hygrothermally treated spruce wood. See Fig. 2 for definition of symbols

Figure 4 shows the logarithm of aT plotted against the reciprocal of absolute temperature. This Arrhenius plot varies to some extent, but the variations are negligibly small compared to the RHh dependence of aH, as described later. The apparent activation energy (Ea) calculated from the slope of the regression line is 110–116 kJ/mol at ≥ 63%, and the average Ea is 115 kJ/mol. These values are close to those reported in the literature as calculated from residual mass (119–131 kJ/mol), residual rigidity (123 kJ/mol), residual strength (113–120 kJ/mol), and color change (117 kJ/mol) upon oven-heating [8, 19, 21, 22]. Since the Ea value does not strongly depend on the RHh, the aT is assumed to be independent of RHh, and the RHh dependence of aT is approximated by the following equation:
$${\text{Ln}}\left( {a_{T} } \right) = 13402/T\left( {\text{K}} \right) - 34.165\,\left( {r = 0.996} \right).$$
This empirical equation allows determination of aT for arbitrary T.
Fig. 4

Logarithm of aT as a function of reciprocal of T. See Fig. 2 for definition of the other symbols. Crosses indicate aT values determined by oven-heating of cypress wood [19]

Figure 5 shows the logarithm of aH plotted against RHh. The aH value varies widely by four order of magnitude depending on RHh. Unfortunately the aH–RHh curve cannot be simply formulated, but its sigmoid shape recalls the moisture sorption isotherm of wood. That is, aH is speculated to depend on the moisture content, rather than on RHh.
Fig. 5

Logarithm of aH as a function of RHh. Solid curve indicates values calculated using Eqs. (8) and (9)

To discuss the effect of the moisture content on aH, we must know the EMC at the test temperatures. However, it is technically difficult to precisely determine the mass of wood in the autoclave during hygrothermal treatment. Therefore, here we use the EMC determined at 25 °C (EMC25), which reflects the moisture content or hygroscopicity of wood, to formulate the RHh dependence of aH. The EMC25 of unmodified wood is plotted against RH in Fig. 6. The sigmoid shape of the moisture sorption isotherm can be approximated by the following Hailwood–Horrobin adsorption equation [10]:
$${\text{EMC}}_{25} \left( {\text{\% }} \right) = \frac{{1800K_{1} K_{2} {\text{RH}}}}{{W\left( {100 + K_{1} K_{2} {\text{RH}}} \right)}} + \frac{{1800K_{2} {\text{RH}}}}{{W\left( {100 - K_{2} {\text{RH}}} \right)}}$$
where W is the molecular weight of the polymer substance per sorption site, K1 is an equilibrium constant in the reaction of water and the anhydrous polymer to form the hydrated polymer, and K2 is the equilibrium constant denoting dissolved water assumed in the sorption theory. The W, K1, and K2 values here are determined as 278, 11.5, and 0.738, respectively. In Fig. 6, the result of approximation is exhibited as a solid curve. The excellent approximation (r = 0.998) allows prediction of the EMC25 of wood at arbitrary RH. Here we assume that the RH is equivalent to RHh, and calculate EMC25 values at different RHh. The logarithm of aH is plotted against the calculated EMC25 in Fig. 7. The linear correlation between ln(aH) and EMC25 is approximated by the following equation:
$$\ln \left( {a_{H} } \right) = - 0.1653 \times {\text{EMC}}_{25} + 1.936\,\left( {r = 0.996} \right)$$
Although Eq. (9) does not strictly express the EMC dependence of aH, it is practically useful for determining aH at arbitrary RHh.
Fig. 6

Moisture sorption isotherm of unmodified spruce wood at 25 °C. Solid curve indicates EMC25 values approximated by Eq. (8)

Fig. 7

Logarithm of aH plotted against EMC25

4 Discussion

Thermal treatment is recognized as a method of accelerated ageing, and tT superposition has been applied to changes in the mass, mechanical properties, and color of wood upon heating [8, 19, 22, 34]. However, in many cases, wood is oven-heated (0% RHh) at high temperatures (≥ 150 °C), whereas natural ageing proceeds at intermediate RH. In addition, the chemical reactions in wood at ≥ 150 °C are qualitatively different from those at lower temperatures [6]. As exhibited in Fig. 5, the aH value decreases by four orders of magnitude as RHh is elevated from 0 to 100%; this is equivalent to elevating the temperature from 100 to 150 °C. This large impact of RHh cannot be ignored; otherwise, hygrothermal treatment has little practicality as a method of accelerated ageing.

To verify the validity of tT–RHh superposition, here we compare the ML values calculated by using Eqs. (7)–(9) with the ML values previously reported. The tT–RHh superposition proposed here is only strictly applicable to mild treatment conditions (T ≤ 140 °C and ML ≤ 15%) for spruce wood in closed chambers, because the ML depends not only on t, T, and RHh but also on factors including wood species, heating system (open or closed), heating medium (air, nitrogen or vacuum), and the rate of air ventilation [8, 22, 23, 24, 29, 30]. Therefore, we selected ML values induced by relatively mild heating [21, 22, 26]. In Fig. 8, the calculated ML values are compared to those from oven-heating at 115–160 °C and 0% RHh in the literature. The predicted ML values are slightly higher than the experimental ones, but the overall trends are expressed well by the tT–RHh superposition.
Fig. 8

ML due to heating at 0% RHh as a function of t. Plots, experimental values in previous literature [21, 22, 26]; curves (AG), values calculated from Eqs. (7)–(9); open circles and curve (A), heated at 140 °C; open squares and curve (B), heated at 160 °C; open triangles and curve (C), heated at 130 °C; filled triangles and curve (D), heated at 115 °C; filled circles and curve (E), heated at 135 °C; filled diamonds and curve (F), heated at 150 °C; filled squares and curve (G), heated at 155 °C; bars, variations of four different wood species [22]

Although the effects of oven-heating (0% RHh) have been studied well, few systematic experiments have been conducted on the ML values at intermediate and high RHh: the t, T, and RHh ranges are often limited. In addition, unusual ML values are sometimes reported; the heating of water-saturated wood yielded smaller ML values than oven-heating did [1], despite the accelerated degradation of wood in the presence of moisture. Such unusual ML values are excluded for a convincing discussion. In Fig. 9, selected ML values at 140–160 °C and 8–100% RHh [4, 27] are compared to the calculated results. Particularly in steaming (100% RHh), the ML value tends to scatter, probably from the unpredictable loss of decomposition residue [27], but the calculated values show good agreement with the experimental values. These results suggest that the tT–RHh superposition is useful in generalizing fragmental results and predicting ML by hygrothermal treatment.
Fig. 9

ML due to heating in moist condition as a function of t. Plots, experimental values in previous literature [4, 27]; curves (AE), values calculated from Eqs. (7)–(9); open circles and curve (A), treated at 140 °C and 100% RHh; open squares and curve (B), treated at 160 °C and 100% RHh; filled circles and curve (C), treated at 150 °C and 8% RHh; filled triangles and curve (D), treated at 150 °C and 51–57% RHh; filled squares and curve (E), treated at 150 °C and 100% RHh

The excellent linearity observed in Figs. 4 and 7 implies that the tT–RHh superposition is applicable to lower T values. When wood is treated at room temperature (20 °C), the RHh is regarded as RH, the environmental relative humidity. Figure 10 shows the calculated ML values as a function of t at 20 °C and varied RH. The ML is expected to be < 3% over 2000 years of ageing in dry conditions (≤ 60% RH), whereas it is predicted to increase steeply in humid conditions (≥ 90% RH). This suggests that wood is quite stable unless it is exposed to humid condition. This prediction is difficult to prove experimentally, but it is the most reliable one presently available because it considers the effects of humidity. The validity of the tT–RHh superposition will be further discussed in a subsequent article by comparing the ML-dependent physical properties of hygrothermally treated wood and those of naturally aged wood.
Fig. 10

Predicted ML values as a function of t at 20 °C and indicated RH

5 Conclusions

The ML–t curves determined at 95–140 °C and 0–92% RHh were successfully superposed into a single master curve by using aT and aH, which represent the effects of T and RHh, respectively. The Ea calculated from the ln(aT)–1/T plots (110–116 kJ/mol) were close to those determined by oven-heating, and the RHh dependency of aT was not significant. The aH seemed to depend on the moisture content of wood rather than on RHh, and it was formulated as a function of EMC25. The shift factors allowed the prediction of the ML of wood after hygrothermal treatment at arbitrary T and RHh. The predicted ML values showed good agreement with those in the literature.


Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.


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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Nanami Zeniya
    • 1
  • Eiichi Obataya
    • 1
  • Kaoru Endo-Ujiie
    • 1
  • Miyuki Matsuo-Ueda
    • 2
  1. 1.Graduate School of Life and Environmental SciencesTsukuba UniversityTsukubaJapan
  2. 2.Graduate School of Bioagricultural SciencesNagoya UniversityNagoyaJapan

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