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Journal articles
Advanced combustion and flow modeling: comprehensive model study improves recovery boiler operation, TAPPI JOURNAL, July 2000, Vol. 83(7)
Advanced combustion and flow modeling: comprehensive model study improves recovery boiler operation, TAPPI JOURNAL, July 2000, Vol. 83(7)
Journal articles
Adsorption of anionic dissolved and colloidal substances onto calcium carbonate fillers, TAPPI JOURNAL, July 2000, Vol. 83(7)
Adsorption of anionic dissolved and colloidal substances onto calcium carbonate fillers, TAPPI JOURNAL, July 2000, Vol. 83(7)
Journal articles
A laboratory method for biaxial straining of paper during drying, TAPPI JOURNAL, July 2000, Vol. 83(7)
A laboratory method for biaxial straining of paper during drying, TAPPI JOURNAL, July 2000, Vol. 83(7)
Journal articles
Impact of the cluster rule on the cost competitiveness of the u.s. papermaking industry in the global market, TAPPI JOURNAL, September 2000, Vol. 83(9)
Impact of the cluster rule on the cost competitiveness of the u.s. papermaking industry in the global market, TAPPI JOURNAL, September 2000, Vol. 83(9)
Journal articles
Improved ozone efficiency at reduced charges -- an electrochemical model and new experimental approach, TAPPI JOURNAL, September 2000, Vol. 83(9)
Improved ozone efficiency at reduced charges -- an electrochemical model and new experimental approach, TAPPI JOURNAL, September 2000, Vol. 83(9)
Journal articles
Pulping of aspen wood in acetic acid media: effect of operating conditions on yield and pulp properties, TAPPI JOURNAL, December 2000, Vol. 83(12)
Pulping of aspen wood in acetic acid media: effect of operating conditions on yield and pulp properties, TAPPI JOURNAL, December 2000, Vol. 83(12)
Journal articles
An image analysis method to quantify fibre separation in wood subjected to fatigue loading, TAPPI JOURNAL, December 2000, Vol. 83(12)
An image analysis method to quantify fibre separation in wood subjected to fatigue loading, TAPPI JOURNAL, December 2000, Vol. 83(12)
Journal articles
Controllable conversion of cellulose nanocrystals to cellulose microspheres: Insight on the effect of parameters during spray drying, TAPPI Journal February 2025
ABSTRACT: Cellulose microspheres, which have mainly been produced via the sol-gel method up until now, exhibit a promising potential for broad applications due to their regular microstructure and renewability. However, some issues with production of cellulose microspheres, such as the recycling of involved organic solvents and the removal of the residual solvents, should be solved. In this study, a cellulose nanocrystals (CNCs) suspension was used to produce cellulose microspheres via spray drying in order to avoid the use of organic solvents. The effects of CNCs particle size, CNCs concentration, and inlet temperature of spray drying on microstructure and particle size of cellulose microspheres were investigated. The results indicated that the optimal average particle size and concentration of CNCs used for obtaining cellulose microspheres were 106 nm and 0.1 wt%, respectively. Under the optimal conditions, cellulose microspheres with a regular spherical morphology and an average particle size of ca. 3 ìm were obtained. The sulfuric acid hydrolysis and spray drying process barely affected the crystalline structure of cellulose. However, the introduced sulfhydryl groups, which were confirmed by Fourier transform infrared spectroscopy results, degraded the thermostability of cellulose. Generally speaking, converting CNCs to cellulose microspheres via spray drying is beneficial for promoting the controllable and continuous production of cellulose microspheres.
Journal articles
Gap mechanics in pulp refiners, TAPPI Journal June 2025
ABSTRACT: Studies of pulp refining have shown that a single bar impact on pulp has only a 1%•5% probability of producing a successful refining effect. This study has explored the reason why. An analysis of refining kinetics suggested that small segments of a fiber length, about a fiber diameter in size, are treated during each impact. Measurements of localized swelling along fiber lengths caused by refining supported this finding. Based on these findings, it was postulated that force transmittal through fiber networks occurred primarily at fiber crossings. The small size of fiber diameters relative to fiber lengths accounts for the low probability of a successful refining event at each impact. This probability, and the probability of fibers being captured and impacted during passage through a refiner, account for the need for multiple bar crossings to refine pulps.
Journal articles
Predictive advisory solutions for chemistry management, control, and optimization, TAPPI Journal March 2025
ABSTRACT: Process runnability and end-product quality in paper and board making are often connected to chemistry. Typically, monitoring of the chemistry status is based on a few laboratory measurements and a limited number of online specific chemistry-related measurements. Therefore, mill personnel do not have real-time transparency of the chemistry related phenomena, which can cause production instability, including deposition, higher chemical consumption, quality issues in the end-product and runnability problems. Machine learning techniques have been used to establish soft sensor models and to detect abnormalities. Furthermore, these soft sensors prove to be most useful when combined with expert-driven interpretation. This study is aimed at utilizing a hybrid solution comprising chemistry and physics models and machine learning models for stabilizing chemistry-related processes in paper and board production. The principal idea is to combine chemistry/physics models and machine learning models in a fashion close to white box modeling. A cornerstone in the approach is to formulate explanations of the findings from the models; that is, to explain in plain text what the findings mean and how operational changes can mitigate the identified risks. The approach has been demonstrated for several different applications, including deposit control in the wet end, both raw water treatment and usage, and wastewater treatment. This approach provides mill personnel with knowledge of identified phenomena and recommendations on how to stabilize chemistry-related processes. Instead of using close to black box machine learning models, a hybrid solution including chemistry/physics models can enhance the performance of artificial intelligence (AI) deployed systems. A successful way of gaining the trust from mill personnel is by creating a plain text explanation of the findings from the hybrid models. The correlation between the likelihood of a phenomena and disturbance and the explanations are derived and validated by application and chemistry and physics experts.