A new approach to obtain chitosan films – Characteristics of films prepared with tea and coffee kombucha as natural chitosan solvents
2023, Stefanowska, Karolina, Woźniak, Magdalena, Majka, Jerzy, Sip, Anna, Mrówczyńska, Lucyna, Waśkiewicz, Agnieszka, Kozak, Wojciech, Dobrucka, Renata, Ratajczak, Izabela
Chemical Composition and Related Properties of Lime (Tilia cordata Mill.) Bark and Wood as Affected by Tree Growth Conditions
2022, Kusiak, Władysław, Majka, Jerzy, Zborowska, Magdalena, Ratajczak, Izabela
Tilia cordata Mill. is a favourite tree used in urban spaces. For this reason, it is important to know its sensitivity to environmental stress, which is particularly burdensome for vegetation in urban spaces. The aim of the study was to investigate the properties necessary to control the growth of these trees and their subsequent use, i.e., chemical properties (percentage contents of cellulose, holocellulose, lignin, pentosans and substances soluble in NaOH and EtOH) as well as the chemical elements (K, Na, Mg, Ca and Fe, Zn, Cu, Pb, Cd, B, Ni, Cr, Al, As and Hg) and selected hygroscopic properties (hysteresis and sorption isotherms). Trees of Tilia cordata Mill. growing in environments exposed to environmental stress of varying severity were examined. Regardless of the growth conditions, in terms of its chemical composition, bark differs significantly from wood, showing twice the contents of soluble substances in NaOH and lignin and half the content of polysaccharides. Growth conditions clearly affect the range of selected chemical components in bark, e.g., substances soluble in ethanol, cellulose, or lignin. The main inorganic elements in bark and wood are Na, K, Ca, Mg and Zn. In bark, a relationship was found between the content of most chemical elements and differing environmental growth conditions. It was shown that environmental stress influenced the hygroscopic properties of wood and bark, which are a consequence of the percentage of chemical components.
Interlaboratory study of automated sorption measurements in wood: method for correcting systematic errors with the commonly used 0.002% min−1 stop criterion
2025, Zelinka, Samuel L., Glass, Samuel V., Farkas, Natalia, Thybring, Emil E., Altgen, Michael, Rautkari, Lauri, Curling, Simon, Cao, Jinzhen, Wang, Yujiao, Künniger, Tina, Nyström, Gustav, Dreimol, Christopher Hubert, Burgert, Ingo, Roper, Mark G., Broom, Darren P., Schwarzkopf, Matthew, Yudhanto, Arief, Subah, Mohammad, Lubineau, Gilles, Fredriksson, Maria, Olek, Wiesław, Majka, Jerzy, Pedersen, Nanna Bjerregaard, Burnett, Daniel J., Garcia, Armando R., Dreisbach, Frieder, Waguespack, Louis, Schott, Jennifer, Esteban, Luis G., García‑Iruela, Alberto, Colinart, Thibaut, Rémond, Romain, Mazian, Brahim, Perré, Patrick, Emmerich, Lukas
Abstract Many studies that use an automated sorption balance to determine a water vapor sorption isotherm for wood collect data until the moisture content change is less than or equal to 0.002% min−1 (20 µg g−1 min−1). This stop criterion has been claimed to give errors in equilibrium moisture content (EMC) predictions of less than 0.001 g g−1 but over the past 10 years, studies have shown that the actual errors can be greater than 0.01 g g−1 because the measurements are stopped well before equilibrium is reached. Despite the large errors associated with this stop criterion, it remains popular due to the speed at which isotherms can be measured. This paper utilizes data from a worldwide interlaboratory study on automated sorption balances to develop a correction method for estimating EMC of western larch (Larix occidentalis Nutt.) from the moisture content corresponding to the 20 µg g−1 min−1 criterion. The study uses data from 72 relative humidity absorption steps with hold times of 7–10 days from 21 different laboratories and eight different instrument models. EMC is defined based on the inherent mass stability of automated sorption balances determined in the first part of this interlaboratory study. On average the sorption process is less than 80% complete when the 20 µg g−1 min−1 criterion is reached, resulting in a mean absolute error (MAE) of 0.006 g g−1. The correction equation for estimating EMC reduces the MAE to 0.001 g g−1. The analysis presented in this paper, along with the correction equation, can be considered for certain use cases to reduce systematic errors and shorten measurement times.
Interlaboratory study of the quality of water vapor sorption data for wood from automated sorption balances
2025, Zelinka, Samuel L., Glass, Samuel V., Farkas, Natalia, Thybring, Emil E., Altgen, Michael, Rautkari, Lauri, Curling, Simon, Cao, Jinzhen, Wang, Yujiao, Künniger, Tina, Nyström, Gustav, Dreimol, Christopher Hubert, Burgert, Ingo, Roper, Mark G., Broom, Darren P., Schwarzkopf, Matthew, Yudhanto, Arief, Subah, Mohammad, Lubineau, Gilles, Fredriksson, Maria, Olek, Wiesław, Majka, Jerzy, Pedersen, Nanna Bjerregaard, Burnett, Daniel J., Garcia, Armando R., Dreisbach, Frieder, Waguespack, Louis, Schott, Jennifer, Esteban, Luis G., García‑Iruela, Alberto, Colinart, Thibaut, Rémond, Romain, Mazian, Brahim, Perré, Patrick, Emmerich, Lukas
Abstract Automated sorption balances are widely used for characterizing the interaction of water vapor with hygroscopic materials. This paper is part of an interlaboratory study investigating the stability and performance of automated sorption balances. A previous paper in this study investigated the mass, temperature, and relative humidity (RH) stability of automated sorption balances by looking at the mass change of a non-hygroscopic sample over time. In this study, we examine the mass stability of wood samples held at constant RH for seven to ten days after a step change. The reason for the long hold times was to collect data to “operational equilibrium” where the change in mass is on the order of the inherent operational stability of the instrument. A total of 80 datasets were acquired from 21 laboratories covering absorption with final RH levels ranging from 10 to 95%. During these long hold times, several unusual behaviors were observed in the mass-vs-time curves. Deviations from expected sorption behavior were examined by fitting the data to an empirical sorption kinetics model and calculating the root mean square error (RMSE) between the observed and smoothed behavior. Samples that had a large RMSE relative to the median RMSE of the other datasets often had one of several types of errors: abrupt disturbances, diurnal oscillations, or long-term mass decline during an absorption step. In many cases, mass fluctuations were correlated with changes in the water reservoir temperature of the automated sorption balance. We discuss potential errors in sorption measurements on hygroscopic materials and suggest an acceptable level of RMSE for sorption data.