Search Results (82)

Large Language Models (LLMs) now occupy a prominent role in science, engineering, and higher education. Their capacity to generate step-wise solutions, conceptual explanations, and problem-solving pathways creates new opportunities—but also new risks—for Chemical Engineering learners. Despite widespread informal use, few empirical studies have evaluated LLM performance using a systematically designed dataset mapped directly to Bloom’s Taxonomy. This study evaluates the competency of ChatGPT in solving Chemical Engineering problems mapped to Bloom’s Taxonomy. A diverse dataset of undergraduate-level problems spanning six cognitive domains was used to assess the model’s reasoning across ascending levels of cognitive complexity. Each response was evaluated for accuracy and categorized into five error types. Although ChatGPT demonstrated considerable potential across a range of topics, the analysis also revealed important challenges and limitations that inform best practices for integrating LLMs into Chemical Engineering education. Results show significant differences in ChatGPT performance across Bloom levels, revealing three distinct tiers of capability. Strong performance was observed at lower cognitive levels (Remember–Apply), while substantial degradation occurred at Analyze, Evaluate, and specially Create. The findings provide a nuanced, empirically grounded understanding of current LLM capability limits, with practical recommendations for educators integrating LLMs into engineering curricula. Full article

A sense of belonging in science, technology, engineering, and mathematics (STEM) education is often conceptualized primarily through social dimensions, overlooking its disciplinary and epistemological contexts. In chemistry, understanding belonging requires examining how disciplinary culture, values, and norms shape who feels included and who is excluded. This perspective article explores belonging in chemistry (a STEM discipline) as a multidimensional construct, emphasizing the intersections of social, cultural, and epistemic dimensions that influence students’ participation and identity development in chemistry. Through a critical synthesis of literature informed by dominant group theory and decolonization frameworks, this work interrogates how Eurocentric definitions of merit and excellence perpetuate exclusionary practices and constrain the belonging of nondominant groups. The analysis identifies key opportunities in chemistry to support the participation of all and offers asset-based considerations for transforming departmental and instructional practices. We conclude that advancing belonging in chemistry requires reexamining disciplinary norms and adopting new approaches that validate multiple ways of knowing and contributing to the chemical sciences. Full article

The integration of complex system concepts and sustainability in chemical engineering education is often limited to elective or separate courses rather than their integration into the core curriculum. This pedagogical gap can lead to graduates who lack a holistic understanding of the intricate interplay between industrial processes and the Earth’s ecological limits, and the feedback loops required to address complex global challenges. This paper presents a transformative approach to close this gap by embedding the Planetary Boundaries framework and system thinking across core chemical engineering courses, such as Material and Energy Balances, Reaction Engineering, and Process Design, and extending this integration to capstone projects. The framework treats the curriculum itself as an interconnected learning system in which key systems concepts are revisited and deepened through contextualized examples and digital modeling tools, including process simulators and life-cycle assessment. We map each boundary to illustrative process examples and learning activities and discuss practical implementation issues such as curriculum crowding, educator readiness, and data availability. This approach aligns with outcome-based education goals by making system thinking and absolute sustainability explicit learning outcomes, preparing future chemical engineers to design processes that respect planetary limits while balancing technical performance, economic feasibility, and societal needs. Full article

The development of highly efficient and stable non-noble metal catalysts for volatile organic compound (VOCs) abatement remains a pressing challenge. Mn-based perovskites exhibit superior thermal stability as redox catalysts but suffer from limited activity in light alkane combustion. This study systematically investigates the performance of SmMnO₃ (SMO) perovskite catalysts for propane oxidation through selective etching of Sm species. By precisely controlling the etching process, the removal of surface Sm exposes more active sites and significantly increases the specific surface area from 22.05 m²·g⁻¹ for pristine SMO to 66.15 m²·g⁻¹. SEM and N₂ adsorption–desorption analysis revealed that prolonged etching induces surface roughening and pore channel expansion. XPS and XANES measurements confirmed that an increased Mn⁴⁺/Mn³⁺ ratio enhances reactant adsorption and accessibility to active sites. The etched catalysts exhibited markedly improved activity for propane oxidation, achieving a ~50 °C reduction in light-off temperature compared to the raw SMO. This performance enhancement is attributed to the synergistic effects of enhanced oxygen mobility, elevated Mn⁴⁺ content, and abundant oxygen vacancies. Further characterization via Raman spectroscopy and H₂-TPR revealed weakened Jahn–Teller distortion and lower reduction temperatures, reflecting optimized Mn–O interactions and superior redox properties. Among the samples, SMO-20 demonstrated exceptional stability. Moreover, the SMO-20/cordierite monolithic catalyst maintained outstanding catalytic performance over 1000 h of operation. This work offers a facile and effective approach to engineer perovskite catalysts and provides new insights into structure–activity relationships in VOC oxidation. Full article

The search for sustainable alternatives to synthetic composites has become increasingly relevant in aerospace engineering education and student rocketry. Fiberglass is widely used for rocket fuselages due to its favorable balance of performance and cost, but it is energy-intensive, non-biodegradable, and environmentally burdensome. This study provides the first demonstration of natural fiber composites applied to student rocket fuselages, evaluating bamboo and jute as sustainable alternatives to fiberglass. Fiberglass, bamboo, and jute laminates were fabricated following the procedures of the RocketWolf team at CEFET/RJ. The fuselages were characterized by parachute ejection tests, surface roughness analysis, and flight simulations using OpenRocket software. Additional data such as laminate mass, wall thickness, fiber–resin ratio, and cost analysis were incorporated to provide a comprehensive assessment. Results revealed contrasting behaviors: untreated bamboo composites showed poor resin impregnation, brittle behavior, and lack of structural stability, confirming their unsuitability without chemical treatment. Jute composites, in contrast, achieved adequate impregnation, cylindrical geometry, and superior surface roughness (Ra = 37 µm) compared to fiberglass with paint (62 µm) or envelopes (52 µm). Both fiberglass and jute fuselages successfully passed parachute ejection tests, while simulations indicated apogees close to 1 km, fulfilling competition requirements. The jute fuselage also presented slightly improved stability margins. Economically, jute was ~492% cheaper than fiberglass in fiber-only comparison but absorbed more resin; nevertheless, real purchase prices favored jute. These findings confirm that jute composites are a technically feasible, cost-effective, and sustainable substitute for fiberglass in student rocket fuselages. Beyond technical validation, this work demonstrates the educational and environmental benefits of integrating natural fibers into academic rocketry, bridging sustainability, performance, and innovation. Full article

Marine Aspergillus fungi, adapted to extreme marine environments (e.g., sediments, corals, mangroves), are prolific producers of structurally diverse secondary metabolites with significant bioactivities. This review comprehensively analyzes 340 novel natural products reported from 81 marine-derived Aspergillus strains over the past three years, classifying them into six major categories: alkaloids (31.2%), polyketides (29.4%), terpenoids, lignans, cyclopeptides, and others. Bioactivity assessments reveal broad therapeutic potential, including antitumor, antimicrobial, anti-inflammatory, and antiviral effects. Notably, marine sediments constitute the primary source (25.9% of strains), followed by sponges and corals. The predominance of alkaloids and polyketides underscores their pharmacological relevance. These findings highlight marine Aspergillus as a critical resource for drug discovery, offering promising scaffolds for developing treatments against human diseases and agricultural pathogens. Full article

This study examines the perceived utility of generative artificial intelligence (GenAI), particularly ChatGPT, in the development of final degree projects across diverse academic disciplines. Drawing on a mixed-methods design, the research involved eleven final-year undergraduate students who participated in structured sessions integrating GenAI tools into distinct project phases. Quantitative and qualitative data revealed heterogeneous perceptions of GenAI’s utility, with theoretical framework development rated most favorably and visual presentation tasks least useful. Disciplinary variations were pronounced; students from Chemical Engineering and Psychology reported higher engagement, while those in Philosophy and Computer Science expressed greater skepticism. To ensure methodological rigor, AI-driven linguistic analysis of oral discourse confirmed participant homogeneity in academic maturity, supporting the attribution of perceptual differences to disciplinary and task-specific variables rather than individual disparities. The findings underscore the need for context-sensitive integration of GenAI in higher education, balancing its potential as a cognitive amplifier with critical evaluation of its limitations. Full article

Aluminum is the most used non–ferrous metal. It can be recycled saving several natural resources, but generates large amounts of residues with a complex composition—still containing a valuable amount of aluminum, although also including contaminant compounds. The laboratory-scale valorization of an industrial aluminum residue is here used as a powerful didactic resource in Inorganic and Analytical Chemistry and related fields such as Chemistry, Chemical Engineering, Environmental Engineering, Materials Engineering, and related university degrees, since concepts like acid-base properties (particularly amphoterism), redox reactions, speciation diagrams, or solubility–precipitation concepts are applied. The students are encouraged to look for information on the topic, to teamwork, and to elaborate a well-written laboratory report. At the same time, this laboratory work introduces them to advanced laboratory techniques and to incorporate concepts of Circular Economy and various Sustainable Development Goals, educating the students with respect to the environment. Although focused on University studies, this manuscript also contains excellent ideas for secondary teachers to motivate STEM vocations, particularly for Chemistry and Chemical and Environmental Engineering, and is also ideal for being included in the preparation of future Secondary School teachers. Full article

This study presents the design and fabrication of silicone–urethane hybrid foam (SUF) to improve fire safety in transportation seating. Tin(II) 2-ethylhexanoate (Sn(OCT)₂) was used to catalyze reactions between bifunctional isocyanates, polyols, and vinyl-terminated PDMS, enabling simultaneous curing and foaming. Sn(OCT)₂ effectively facilitated both the foaming and gelation processes of silicone and urethane chemistries. The resulting SUF demonstrated a 44.55% reduction in peak heat release rate (PHRR) compared to UF, due to the PDMS network’s synergistic flame-retardant and barrier effects. Additionally, the crosslinked PDMS structure maintained strong mechanical integrity. This study offers a simple and effective approach for producing SUF with enhanced fire safety. Full article

This review provides a comprehensive overview of the evolution and application of artificial intelligence (AI) and large language models (LLMs) in engineering, with a specific focus on chemical engineering. The review traces the historical development of LLMs, from early rule-based systems and statistical models like N-grams to the transformative introduction of neural networks and transformer architecture. It examines the pivotal role of models like BERT and the GPT series in advancing natural language processing and enabling sophisticated applications across various engineering disciplines. For example, GPT-3 (175B parameters) demonstrates up to 87.7% accuracy in structured information extraction, while GPT-4 introduces multimodal reasoning with estimated token limits exceeding 32k. The review synthesizes recent research on the use of LLMs in software, mechanical, civil, and electrical engineering, highlighting their impact on automation, design, and decision-making. A significant portion is dedicated to the burgeoning applications of LLMs in chemical engineering, including their use as educational tools, process simulation and modelling, reaction optimization, and molecular design. The review delves into specific case studies on distillation column and reactor design, showcasing how LLMs can assist in generating initial parameters and optimizing processes while also underscoring the necessity of validating their outputs against traditional methods. Finally, the review addresses the challenges and future considerations of integrating LLMs into engineering workflows, emphasizing the need for domain-specific adaptations, ethical guidelines, and robust validation frameworks. Full article

Respirable crystalline silica is a well-established occupational hazard in construction work. Despite increased awareness, consistent exposure control remains a challenge, particularly in dynamic and resource-constrained environments. Respirable crystalline silica exposure in construction environments challenges the achievement of the United Nations Sustainable Development Goals (SDGs), particularly SDG 3 (Good Health and Well-Being) and SDG 8 (Decent Work and Economic Growth). Respirable crystalline silica particles cause severe health complications, including silicosis, lung cancer, cardiovascular diseases, and autoimmune disorders, representing a significant barrier to achieving SDG 3.9’s target of reducing deaths and illnesses from hazardous chemical exposures by 2030. This systematic review evaluates two decades of advancements (2004–2024) in respirable crystalline silica identification, characterisation, and mitigation within construction, synthesising evidence from 143 studies to assess progress toward sustainable occupational health management. This review documents a paradigmatic shift from traditional exposure assessment toward sophisticated monitoring approaches incorporating real-time detection systems, virtual reality–Computational Fluid Dynamics simulations, and wearable sensor technologies. Engineering controls, including local exhaust ventilation, wet suppression methods, and modified tool designs, have achieved exposure reductions exceeding 90%, directly supporting SDG 8.8’s commitment to safe working environments for all workers, including migrants and those in precarious employment. However, substantial barriers persist, including prohibitive costs, inadequate infrastructure, and regional regulatory disparities that particularly disadvantage lower-resourced countries, contradicting the Sustainable Development Goals’ principles of leaving no one behind. The findings advocate holistic approaches integrating technological innovation with context-specific regulations, enhanced international cooperation, and culturally adapted worker education to achieve equitable occupational health protection supporting multiple Sustainable Development Goals’ objectives by 2030 and also highlighting potential areas for future research. Full article

This study presents the outcomes of the Erasmus+ European project Higher Education Classroom of the Future (HECOF), with a particular focus on chemical engineering education. In the digital era, the integration and advancement of artificial intelligence (AI) in higher education, especially in engineering, are increasingly important. The main goal of the HECOF project is to establish a system of new higher education teaching practices and national reforms in education. This system has been developed and tested through an innovative personalized and adaptive method of teaching that exploited digital data from students’ learning activity in immersive environments, with the aid of computational analysis techniques from data science. The unit operations—extraction process course—a fundamental component of the chemical engineering curriculum, was selected as the case study for the development of the HECOF learning system. A group of undergraduate students evaluated the system’s usability and educational efficiency. The findings showed that the HECOF system contributed positively to students’ learning—although the extent of improvement varied among individuals—and was associated with a high level of satisfaction, suggesting that HECOF was effective in delivering a positive and engaging learning experience. Full article

New teaching methods are essential to prepare 21st-century engineers for sustainable challenges. This study used project-based learning to evaluate the energy potential of water channels in fish farms in Loreto, Peru. Chemical engineering students applied theory to practice, enhancing skills like field data collection and technical assessment. The results show a practical potential of 18.37 kW and a theoretical potential of 84.19 kW, enough to power 37–244 households. This approach not only highlights renewable energy opportunities but also demonstrates the effectiveness of connecting theory and practice in real-world contexts. Despite simplified calculations, this project significantly impacts engineering education in Latin America, serving as an example of successful learning and inspiring innovative teaching techniques. All of the students (100%) agreed that the project helped in terms of practical skill and problem-solving capability development, teaching motivation, and relevance training for professional life. Full article

This study examines the Chemical Engineering and Technology major at Nanjing Forestry University as a case study to explore a sustainable improvement and development model for the major, grounded in the principles of Outcome-Based Education (OBE) and the Plan-Do-Check-Act (PDCA) framework. In the context of new engineering education and integrating the core concepts of engineering professional education accreditation, this research merges the OBE concept with the PDCA model to promote the sustainable enhancement of the Chemical Engineering and Technology major. The objective is to assess the effectiveness of this professional construction model based on the OBE and PDCA framework in fostering the sustainable development of students. The findings indicate that by establishing a cultivation system aligned with the new economy, restructuring the interdisciplinary curriculum, and implementing a diversified evaluation system, it is feasible to nurture high-quality technical engineering talents equipped with social responsibility, teamwork skills, innovative thinking, and an awareness of sustainable development. This study demonstrates that this professional construction mechanism and model significantly contribute to developing sustainable education, enhancing engineering practice and innovative awareness, and cultivating applied innovative talents among students. Furthermore, this study not only offers new insights for specialty construction but also serves as a practical reference for improving teaching quality and meeting societal demands. Full article

The objective of this study is to compare rice husk-derived silica (biosilica) synthesized via an environmentally friendly method with conventional silica (Zeosil 175) for reinforcing the mechanical properties of silicone rubber. The silanol group content of Zeosil 175 (9.45 OH/nm²) is higher than that of biosilica (7.07 OH/nm²), whereas the specific surface area of biosilica (159.52 m²/g) exceeds that of Zeosil 175 (144.90 m²/g). Silicone rubber specimens containing two types of silica nanoparticles were prepared at loading levels of 5, 10, 15, 20, 25, and 30 parts per hundred rubber to evaluate their mechanical properties and characteristics. Results indicate that silicone rubber filled with biosilica shows comparable tensile strength to Zeosil 175 at low filler contents, which can be attributed to its higher specific surface area. However, at higher loading levels, the mechanical properties are somewhat diminished due to the Payne effect and filler agglomeration resulting from the larger particle size of biosilica. These experimental findings offer insights into the potential utilization of rice husk-derived biosilica as an alternative to conventional silica in enhancing the properties of silicone rubber alongside the findings of the mechanical analysis. Full article