Volume 21 Issue 4

Scientific breakthroughs are not just limited to empirical observation and analytical prowess but remain at the forefront of imagination. Speculation and storytelling, hallmarks of imagination, may be powerful means for realizing scientific possibilities long before they become technological realities. In the process of envisioning a breakthrough, imagination can embolden researchers to go beyond existing paradigms and promote creativity into reality. Visionary daydreaming can often be key to catalyze breakthrough discoveries.

Recent oil price volatility and geopolitical uncertainty highlight the need for more resilient energy production models. This study examines the bioeconomy as a strategic framework to address instability in global energy and material supply chains. Historical and recent oil crises demonstrate how fluctuations in fuel markets disrupt industrial competitiveness, particularly in energy-intensive sectors, while propagating impacts across downstream value chains. The bioeconomy offers an alternative pathway through the valorization of biobased resources. Current estimates place its contribution at approximately 3.5 to 4% of global gross domestic product (GDP), with significant growth projected by 2050. However, expansion remains constrained by challenges related to technological scale-up, regulatory fragmentation, investment risk, and limited standardization. Regional analysis reveals heterogeneous development patterns, with strong potential in resource-rich regions such as Latin America to promote localized value creation and reduce external dependencies. Key strategic priorities include strengthening regional value chains, advancing scalable biorefinery platforms, improving regulatory coherence, and expanding investment frameworks. These measures position the bioeconomy as a critical component for enhancing energy security, increasing industrial resilience, and supporting sustainable economic development in conditions of global uncertainty.

Biomass is a naturally renewable resource with wide distribution and huge annual output.  It is the most abundant  renewable organic resource in the world. Biorefinery can be defined as a processing system that converts biomass into a full range of energy products and chemical materials through a series of physical, chemical, and biological conversion treatments. It provides a practical technical route for reducing global dependence on fossil energy, mitigating the greenhouse effect, and promoting the green transformation of the global chemical and energy industry. To fully utilize the components of biomass, the biorefinery process generally comprises complex processing units and procedures, which results in low production efficiency and high investment. Process integration and coupling can effectively streamline its procedures and reduce the number of processing units. This can greatly enhance its production efficiency and reduce investment, thus improving its process economy.  In recent years, a variety of innovative integration and coupling strategies have been developed in the biorefinery process. However, current process integration and coupling still face multiple practical challenges. This editorial will provide a brief discussion on the use of process integration and coupling in the biorefinery process.

For many years, laboratory testing has been the cornerstone of quality evaluation in the paper and corrugated board industry, supporting both material control and packaging design. However, growing production complexity and the need for faster technological decisions expose the limitations of traditional, time-intensive testing methods. This editorial explores the potential of artificial intelligence as a tool that can complement, rather than replace, classical approaches. Machine learning models are capable of estimating key strength parameters such as ECT and BCT, identifying anomalies, and supporting material selection based on process and environmental data. Nevertheless, their effectiveness depends strongly on data quality, and they cannot substitute for standardized tests required for validation and certification. It is argued that the most effective path forward is a hybrid model, combining the reliability of laboratory testing with the speed and predictive power of AI, leading to more efficient and informed decision-making.

Historical woods are one of the most important natural resources in the world. Known wood species used in the past can be an elementary key for understanding traditional communities or old societies, registering cultural expressions, and making strategies for forest conservation. In addition, this knowledge can contribute to cultural agencies’ efforts in heritage preservation. On the other hand, the megabiodiversity found in tropical regions, such as Brazil, can pose an important challenge to successfully identifying wood species. In the rainforests of many regions, more than 450 wood species can be found, including trees and shrub components. Of this total, more than 100 species are used for cultural heritage. This number is incredibly higher than the usual number for cultural use in temperate regions. It is likely that many cultural species are still unknown. This paper introduces the concept of a collection specialized in cultural woods as a new frontier for the historical anatomy of tropical areas.