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Editorial: TAPPI Journal 2024 Best Research Paper focuses on realistic potential for using nonwood residues in sustainable packaging, TAPPI Journal April 2025

ABSTRACT: Each year, the TAPPI Journal Editorial Board honors outstanding content by nominating and voting for the Best Research Paper published the previous year based on scientific merit, innovation, creativity, and clarity. TAPPI and the TAPPI Journal Editorial Board would like to congratulate the authors of the 2024 TAPPI Journal Best Research Paper: Antonio Suarez, Ashok Ghosh, Fritz Paulsen, and Peter W. Hart of Smurfit Westrock (formerly WestRock). The winning paper, “Life cycle carbon analysis of packaging products containing nonwood residues: A case study on linerboard and corrugating medium,” was published in the March 2024 issue.

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.

Improved barrier performance with microfibrillated cellulose, TAPPI Journal March 2025

ABSTRACT: In this work, the impact of microfibrillated cellulose (MFC) on the properties of water-based barrier coatings intended for food packaging have been explored. Commercially available MFC was used for improving the rheology and water retention of three different commercially available dispersion coatings (acrylic, styrene acrylic, and polylactic acid). Coatings were applied by rod to paper, and barrier properties were tested by measuring air permeability and water barrier properties. Results clearly showed that addition of MFC to water-based dispersion coatings improved the barrier performance of the final coatings.

Application of AI-based approach to control the papermaking process, TAPPI Journal March 2025

ABSTRACT: This paper explores AI’s role in revolutionizing the pulp and paper industry, and specifically in predicting wet tensile strength (WTS) for specialty-grade papers. Leveraging eLIXA technology, a 90-day study achieved a 15% reduction in chemical dosage and an 80% decrease in wet tensile standard deviation. The real-time dosage prediction led to optimizing the wet strength resin (WSR) consumption and improved process reliability. The self-learning models exhibited adaptability to changing variables, ensuring their robustness. Overall, this study highlights AI’s transformative impact on efficiency, cost savings, and product quality within the dynamic landscape of papermaking. The approach used for wet strength optimization has been used to optimize other aspects of pulp and paper production.

Multifunctional starch-based barrier materials, TAPPI Journal August 2021

ABSTRACT: Natural and renewable polymer-based barrier materials play an inevitable role in a sustainable economy. Most commercially available barrier materials are either based on multiple layers of synthetic polymers or petroleum-based chemicals. Tremendous amounts of research are being done in academia and industry to replace these synthetic barrier materials with natural and environmentally friendly materials. The current work summarizes the application of starch-based materials for various barrier applications, such as water vapor, oxygen, liquid water, oil, and grease. Also, exotic starch-based barrier materials for the application of sound, ultraviolet, and thermal barrier applications are reviewed. The potential of starch-based materials to offer antimicrobial and antiviral properties is discussed. Finally, commercially available starch-based barrier materials have been summarized.

Tetraethyl orthosilicate-containing dispersion coating — water vapor and liquid water barrier properties, TAPPI Journal September 2021

ABSTRACT: An aqueous styrene-butadiene latex dispersion coating containing in-situ processed tetraethyl orthosilicate (TEOS) applied on paperboard demonstrated improved water barrier performance. Coatings containing TEOS equivalent to 0.8% silicon dioxide (SiO2; dry basis) exhibited water vapor performance of < 25 g/m2/day (23°C, 50% relative humidity [RH]) and liquid water barrier performance Cobb 1800 s of < 6 g/m2, when applied as a single-layer 18 g/m2 coating. Cobb 1800 s barrier performance was still good (< 11 g/m2) at coat weights of 7–10 g/m2. The use of filler materials such as kaolin improved the vapor barrier properties of the coating, but this was not critical to the liquid water barrier properties.

An analytical approach to assess the interrelation of surface properties and softness of tissue paper, TAPPI Journal February 2023

Recycling performance of softwood and hardwood unbleached kraft pulps for packaging papers, TAPPI Journal February 2023

Setting priorities in CNF particle size measurement: What is needed vs. what is feasible, TAPPI Journal February 2023

Assessing lignin content in Nordic hardwood and softwood species using models based on near-infrared (NIR) spectral data and partial least squares regression (PLSR), TAPPI Journal September 2025

ABSTRACT: Continuous kraft cooking digesters face challenges affecting product quality, making it valuable to improve control through advanced techniques like near-infrared (NIR) spectroscopy, model predictive control, and machine learning models. The primary goal of this study was to use NIR spectra to predict the amount of lignin in hardwood and softwood samples. This study investigated the correlation of NIR derivative spectra with the amounts of lignin relative to other constituents, namely cellulose, hemicellulose, and water, in wood chip samples of varying chip sizes and shapes from six Nordic wood species. It employed partial least squares regression (PLSR) on the NIR data to construct a model that predicted the lignin fraction and the relative fraction of acid-soluble lignin. When trained on a group of five wood species, the model achieved a satisfactory predictive ability, striking a balance between a wide range of lignin content and a consistent chemical environment. The accuracy increased further when the model was restricted only to spruce and pine, reflecting the benefits of a more homogenous dataset. Additionally, the optimal number of latent variables was identified as two, indicating that three distinct chemical components — cellulose, lignin and water — can be effectively differentiated using NIR.