Comparison of dynamic mechanical measurements and Tg determinations with two different instruments

Hagen, R.W.; Salmén, Lennart; Lavebratt, H.; Stenberg, Bengt

doi:10.1016/0142-9418(94)90020-5

Cited by 64 publications

(33 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this study, the temperature at which tanδ reached its maximum was defined as the softening temperature (T g ) of the in-situ lignin, because it is independent of the specimen's dimension (Hagen and Salmén 1994). The apparent activation energy (ΔH a ) for the softening process was determined by Equation (1).…”

Section: Methodsmentioning

confidence: 99%

“…In addition, noncovalent interactions (mainly hydrogen bonding interactions) among the wood components are much weaker than that between water and the wood cell wall. Under soaked condition, the T g is between 50°C and 100°C, depending on the native lignin structure and the frequency of the measurement (Sadoh 1981;Hagen and Salmén 1994;Song et al 2014;Zhan et al 2016). A clear relation between lignin structure and wood softening has not yet been established.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Effects of thermo-hygro-mechanical (THM) treatment on the viscoelasticity of in-situ lignin

et al. 2017

Self Cite

View full text Add to dashboard Cite

For producing wood products without fractures based on thermo-hygro-mechanical (THM) treatments, it is essential to understand how steaming and compression change the wood softening and cell wall components. In this paper, the effects of compression combined with steam treatment (CS) on the viscoelasticity of the in-situ lignin of Chinese fir has been investigated through dynamic mechanical analysis (DMA) under fully saturated conditions. Several variations were studied, such as the softening temperature (T g ) and apparent activation energy (ΔH a ) of the softening process in response to CS treatment conditions (such as steam temperature and compression ratio) under separate consideration of earlywood (EW) and latewood (LW). No difference between EW and LW with respect to the viscoelasticity was noted. T g and ΔH a of the lignin softening were nearly unaffected by the compression ratio, but were highly influenced by the steam temperature. The T g decreased significantly with CS treatments at or above 160 o C, but showed no appreciable change, compared to the native wood, at the lower steaming temperature of 140 o C. ΔH a increased at higher steam temperatures, while ΔH a showed a decreasing tendency with decreasing T g . This indicates that lignin undergoes a simultaneous depolymerization as well as a condensation during CS treatment.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Effects of thermo-hygro-mechanical (THM) treatment on the viscoelasticity of in-situ lignin

et al. 2017

Self Cite

View full text Add to dashboard Cite

show abstract

“…The MAEs for the predicted results estimated by SVR were less than those of QSPR for both the training set and validation set. Thus, the prediction errors for the calculations based on [8,34,35] or even over 10 degrees [36] in T g values of a polymer measured by different experimental techniques. These imply that the established SVR model can be used, in practice, to satisfactorily predict the T g of an unknown structurally similar polymer outside of the training set.…”

Section: Resultsmentioning

confidence: 99%

Prediction of the Glass Transition Temperatures of Styrenic Copolymers by Using Support Vector Regression Combined with Particle Swarm Optimization

Pei

Cai

Tang

et al. 2011

Journal of Macromolecular Science, Part B

View full text Add to dashboard Cite

Based on three quantum chemical descriptors (the average polarizability of a molecule (α), the most positive net atomic charge on hydrogen atoms in a molecule (q + ) and the heat capacity at constant volume (C v ) derived from the monomers using the density functional theory (DFT), the support vector regression (SVR) approach combined with particle swarm optimization (PSO), is proposed to establish a model for prediction of the glass transition temperature (T g ) of random copolymers including poly(styrene-co-acrylamide) (SAAM), poly(styrene-co-acrylic acid) (SAA), poly(styrene-co-acrylonitrile) (SAN), poly(styrene-co-butyl acrylate) (SBA), poly(styrene-co-methyl acrylate) (SMA), poly(styrene-co-ethyl acrylate) (SEA), and poly(acrylonitrile-co-methyl acrylate) (ANMA). The mean absolute error (MAE = 1.6 K), mean absolute percentage error (MAPE = 0.45%), and correlation coefficient (R 2 = 0.9978) calculated by SVR model are superior to those (MAE = 5.47 K, MAPE = 1.51%, and R 2 = 0.9829) achieved by a quantitative structure-property relationship (QSPR)/multivariate linear regression (MLR) model for the identical training set, whereas the MAE = 3.03 K, MAPE = 0.90%, and R 2 = 0.9952 calculated by SVR also outperform those (MAE = 5.38 K, MAPE = 1.61%, and R 2 = 0.9778) achieved by the QSPR/MLR model for the identical validation set, respectively. The prediction results strongly support that the modeling and generalization ability of the SVR model consistently surpasses that of the QSPR/MLR model by applying identical training and validation samples. It is demonstrated that the established SVR model is more suitable to be used for prediction of the T g values for unknown polymers possessing similar structure than the conventional MLR model. It is also shown that the hybrid PSO-SVR approach is a promising and practical methodology to predict the glass transition temperature of styrenic copolymers.

show abstract

“…So the dynamic mechanical method is certainly one of the simpler forced non-resonance techniques to understand, but nevertheless to perform accurate measurements and to ensure the relevance of the collected experimental data, a lot of precautions have to be taken. Indeed, large discrepancies among data obtained in DMA by different apparatus or various analysis methods, or even different laboratories using identical instruments have been sometimes underlined by diverse authors [4][5]. These discrepancies are principally due to different well-identified factors:…”

Section: Introductionmentioning

confidence: 99%

“…There are many ways to identify the value of T g based on the dynamic mechanical measurements, such as the peak value of the loss tangent, the peak value of the loss modulus, and the onset of the drop of the storage modulus. However, one has to be aware of the fact that the obtained T g value depends on the method [5]. When the T g values determined using different definitions are compared, large differences are often underlined.…”

Section: Introductionmentioning

confidence: 99%

Is Dynamic Mechanical Analysis (DMA) a non-resonance technique?

Placet

Foltête

2010

EPJ Web of Conferences

View full text Add to dashboard Cite

Abstract. Dynamic Mechanical Analysis is an experimental technique commonly used to study the viscoelastic behaviour of materials over a range of temperatures and frequencies. Although considered as a forced non-resonance technique, the warned users perfectly know that resonant frequencies are inevitably encountered on the typical frequency range of DMA apparatus. In consequences, the measured properties in the area of the resonant frequencies are completely perturbed. This work proposes an analysis of the dynamic behaviour of a Bose Electroforce DMA. The resonant and perturbed frequencies have been identified in different experimental configurations using several materials. A straightforward analytical model was developed to simulate and predict the dynamic behaviour of our apparatus. The model parameters are identified using different experimental configurations. The simulations delivered by the model allow the user to predict the perturbed frequency areas and by this way authorise a strategic definition of the experimental protocol according to the sample characteristics.

show abstract

Comparison of dynamic mechanical measurements and Tg determinations with two different instruments

Cited by 64 publications

References 9 publications

Effects of thermo-hygro-mechanical (THM) treatment on the viscoelasticity of in-situ lignin

Effects of thermo-hygro-mechanical (THM) treatment on the viscoelasticity of in-situ lignin

Prediction of the Glass Transition Temperatures of Styrenic Copolymers by Using Support Vector Regression Combined with Particle Swarm Optimization

Is Dynamic Mechanical Analysis (DMA) a non-resonance technique?

Contact Info

Product

Resources

About