In the current undergraduate chemistry curriculum,the content on non-covalent interactions is mostly limited to van der Waals forces and hydrogen bonds.However,over the past two decades,other non-covalent interactions based on elements such as halogens,chalcogens,pnictogens,borons,and carbons have been extensively studied and have demonstrated significant application value in fields such as drug design,biochemistry,polymer chemistry,and organic catalysis.Therefore,it is particularly important to update the undergraduate teaching system by incorporating these topics to enhance the curriculum content and address students’ knowledge gaps.

Based on the actual situation of organic chemistry teaching at our university,this study conducts an in-depth analysis of the characteristics of students learning situation.By constructing knowledge graphs and developing an AI teaching assistant,it integrates artificial intelligence technology with the BOPPPS teaching mode and implements intelligent reform of the evaluation system.The results demonstrate that these reforms effectively enhance the structured construction of students knowledge systems,significantly improve the effectiveness of classroom learning and achieve the comprehensive improvement in“teaching-learning-assessment”.Additionally,the integration of ideological and political education elements fosters students sense of social responsibility.This research provides a feasible solution for the modernization of organic chemistry teaching and offers new insights for educational reform.

This study investigates the implementation of the O-PIRTAS flipped classroom mode in structural chemistry education,focusing on its pedagogical application through a case study of the instructional design on “background of quantum mechanics emergence”.Taking the teaching process of “Heisenberg’s uncertainty principle” as an example,we analyze the necessity of adopting flipped classrooms in structural chemistry and delineate critical tasks for instructors during preparatory and implementation phases.A novel O-PIRTAS-based flipped classroom framework is proposed,integrating thematic micro-videos to enhance conceptual understanding.This framework integrates curriculum-based ideological and political education,achieving synergistic integration of knowledge delivery and value cultivation.

This study innovatively proposes a“virtual-pretreatment and real-post detection”segmented teaching mode.This mode is specifically designed to address the issues of high risk,high cost,and low efficiency associated with microwave digestion pre-processing in the instrumental analysis experiment of“determination of multiple trace elements in food by inductively coupled plasma optical emission spectrometry(ICP-OES)”.Built upon a self-developed virtual platform for microwave digestion,the mode integrates virtual pretreatment with physical detection,thereby establishing a four-dimensional pedagogical framework comprising“learning,operation,assessment,and evaluation”and a three-dimensional assessment system encompassing“virtual experiment,physical operation and outcome output”.Teaching practice demonstrates that,compared with traditional experimental teaching mode,this mode optimizes teaching resources through the integration of virtual and real components.It not only mitigates instructional risks and curtails costs but also enhances students’ safety awareness,experimental skills and digital literacy,thereby markedly improving teaching quality and learning effectiveness.It thus provides valuable implications for the digital transformation of high-risk pretreatment experiments and carries substantial demonstrative significance for advancing experimental teaching reform.

This study takes the classic teaching project“total hardness determination of water”as the starting point and innovatively constructs a dynamic data processing platform based on ASP(Application Service Provider) service architecture and Access database.The platform achieves intelligent processing of experimental data,full process traceability management,and multi-dimensional error analysis through three core functions:online computing module,real-time data collaboration,and visualization analysis system.Teaching practice has shown that this technical solution not only improves the data processing efficiency of traditional EDTA titration method by more than 60%,but also enhances the ability to trace and analyze abnormal data,providing a replicable technical paradigm for the digital transformation of analytical chemistry experimental teaching.

Based on the three-dimensional integration concept of“interdisciplinary approach,digital empowerment,and value cultivation”,a comprehensive experiment using covalent organic framework(COF) materials as the carrier was designed.The experiment encompasses exploring bottom-up synthesis routes for COF materials,characterization using modern analytical techniques,and fluorescence detection applications for heavy metal ions,thereby constructing a complete research framework from material synthesis and structural analysis to functional validation,effectively bridging core foundational courses in the discipline.By implementing this experiment,students can gain hands-on experience in authentic research settings,mastering cutting-edge knowledge of COF materials,experimental operations,digital simulations,and data processing methods.This approach strengthens their awareness of knowledge transfer and enhances their ability to solve complex problems.

In contemporary chemistry,automated flow chemistry techniques are undergoing rapid development for the synthesis of active pharmaceutical ingredients(APIs).Consequently,it is imperative to integrate the training of innovative talent,ensuring that students are exposed to and proficient in the most advanced automated chemical synthesis techniques.In this paper,we introduce a peptide synthesis device for undergraduate laboratory teaching.This device integrates flow chemistry and automated synthesis technology for the synthesis of the peptide drug Argireline.This device enables students to synthesize multidisciplinary knowledge and gain a deeper understanding of the principles of flow chemistry technology.The innovative integration of flow chemistry concepts and automatic programming technology into the teaching framework realizes the in-depth intersection of chemical engineering and information science,and systematically cultivates the core qualities of modern academic talents.

This study focuses on the intelligent analysis of gas chromatography data and its deep integration with teaching scenarios.Based on the AI-powered educational innovation platform(NK-GeniOS),we have developed an AI-based gas chromatography analysis teaching assistant system specifically for halogenated alkane preparation experiments.By integrating multimodal AI tools through Python scripting,a dual-channel interactive intelligent engine was created,enabling batch recognition,component analysis,and experimental evaluation of gas chromatography data.The student interface allows autonomous data uploading,acquisition of experimental improvement suggestions,and generation of personalized reports via a visual interface,while the teacher interface facilitates rapid identification of class-wide experimental trends,common issues,and anomalies for targeted instruction.In the teaching process,a task-driven learning model was adopted and implemented through collaborative interest groups.Technical approaches and problem-solving strategies were shared among peers via slide presentations and problem-solving discussions,fostering in-depth exchanges.This process embodies the hierarchical empowerment educational philosophy,enabling all students to engage in research experiences at varying levels,while pioneering new pathways for cultivating innovative talents in the AI era.

The popularization of chemistry experiments,due to their vivid,interesting,and interactive nature,serves as an important vehicle for science communication.This article selects the experiment of cultivating rhombic dodecahedron CuSO₄·5H₂O crystals to explore crystal chemistry knowledge and build molecular structure models.Through online and offline science exhibitions that combine theory with practical operation,students’ understanding of chemical principles is deepened.At the same time,related science-themed creative products are designed for display based on the synthesized CuSO₄·5H₂O crystals,including ornaments,postcards,and anime keychains,thereby achieving a combination of chemical products and artistry.This approach aims to stimulate the interest of teenagers and the general public in recognizing and exploring the field of chemistry.

In the context of the development of new quality productive forces,improving the ability of pre-service teachers in science popularization is an important way to promote the popularization of scientific and technological achievements and serve the national innovation-driven development strategy.To address the demand for science pupularization talent within this new productive forces framework,this study constructs a structural framework for science pupularization competences among pre-service teachers.Addressing current practical challenges in cultivating these competences,it proposes systematic solutions including establishing dedicated science pupularization curricula modules and implementing science pupularization enhancements within subject-specific curricula.These measures aim to effectively elevate pre-service teachers’ science pupularization competences,thereby meeting the evolving demands for educational talent within the new productive forces development paradigm.

Using“Tofu-Making”as the central activity,the teaching process comprises three tasks to deliver instruction on colloids.The Tyndall effect is observed and analyzed to identify colloidal properties through“Soy Milk Colloid-Discovering Colloids”.Diverse coagulation methods are then employed to demonstrate particle aggregation and electrophoresis,revealing colloidal structure and exploring different coagulation principles in“Coagulation Technique-Precipitating Colloids”.Finally,the applications of colloidal coagulation principles are expanded while drawing life analogies from tofu craftsmanship in“Savoring Tofu-Triple Reflections”.This process achieves dual objectives:internalizing colloidal knowledge and solving real-world problems.A competency cultivation mode integrating“Cultural Heritage-Scientific Inquiry-Value Guidance”is established,seamlessly combining task-driven learning,experimental exploration,and ideological education.It elevates students’ core chemical literacy and cultural confidence.The project-based context and task design significantly enhance learning engagement,facilitate knowledge transfer,and deepen appreciation for Chinese traditional culture.It offers a replicable pathway for project-based chemistry instruction,preserving excellent traditional culture and synergizing it with ideological and political education in the curriculum.

Internship teaching in materials science is a core component in cultivating engineering-oriented professionals and a crucial stage for students’ transition toward professional engineering roles.Traditional internship instruction is often limited by safety regulations and production complexity,resulting in low student engagement and the dilemma of “visible but untouchable” skill development.Taking polymer materials internships as a case study,this paper explores the construction of an AI-enabled internship assistant that integrates enterprise production data,operating standards,and other resources to provide scenario-based and precise guidance.By incorporating virtual simulation experiments,an immersive training environment is created.An intelligent Q&A system is also developed to support real-time interaction for complex tasks such as process parameter adjustment and anomaly handling.Teaching evaluations show an 8.15% improvement in theoretical scores and a 17.23% enhancement in practical abilities,marking a shift from passive observation to active practice.This research offers a replicable model for the digital-intelligent transformation of engineering education.

The drug metabolism in vivo is a key and difficult point in the teaching of medicinal chemistry.The procedure and method of prediction for the main metabolites and excreted original compound of drug were given by our team,and“prediction+verification”methods were applied in the teaching exploration of the drug metabolism in vivo.At first,the procedure and method of prediction were taught through several examples by lecture-based learning,while the accuracy of the prediction was verified.And then the task-driven teaching method was performed,a group of students must predict the main metabolites(excreted original compound)of a drug and verify them.The result of practice showed,the teaching effect of the methods reached an ideal level and accorded with the construction standard of golden course.

This experiment is designed in response to the growing volume of express deliveries in universities and is set against the background of low-carbon development.It focuses on the carbon footprint accounting of express packaging,aiming to deepen students’ understanding of the“dual carbon”goals.By calculating the carbon emissions throughout the full life cycle of express packaging and combining steps such as optimization scheme design,sample classification,sample collection,and data analysis,the carbon emissions of express packaging in universities can be quantified.The results show that the raw material production stage of express packaging emits 163 tons of CO₂ equivalent(t CO₂e) annually,accounting for 72% of the total emissions,recycling and reuse of materials are the most effective carbon reduction measures.Additionally,fossil fuel consumption during transportation is another significant contributor to the carbon footprint of express packaging,which can be mitigated by replacing conventional vehicles with those powered by clean energy.Through this experiment,students can not only master the methods of carbon footprint accounting but also gain an in-depth understanding of how different packaging materials,transportation processes,and waste disposal methods affect carbon emissions.The experiment enhances students’ awareness of low-carbon and environmental protection concepts,improves their comprehensive experimental skills,and inspires their interest in green development,while subtly strengthening their sense of environmental responsibility.

With the advent of the era of intelligent education and the rapid development of artificial intelligence technologies,traditional classroom teaching modes are facing both challenges and opportunities for transformation.This paper takes the postgraduate course Functional Materials and Energy Catalysis at Tianjin University as an example to illustrate ongoing teaching reforms under this context.The course introduces case-based teaching methods,constructing a multidimensional case-based education matrix and applying a case library in classroom practice.This approach has proven effective in value guidance,classroom engagement,and student assessment,and has been well received by students.Building on these achievements,the paper also proposes plans for future improvements,thereby forming a practical,effective,and easily replicable teaching mode that can serve as a valuable reference for postgraduate education in related disciplines of new energy and advanced materials at other universities.

To meet the needs of scientific research,topical cases are combined into the quantum chemistry course for postgraduate students with investigations and practical explorations.Corresponding course discussion sessions are designed around topics such as spectroscopic characterization,reaction mechanisms,surface adsorption and machine screening.According to outcome-based education,course learning,practical applications,and simulated research progress are integrated to improve the comprehensive quality of graduate students and theoretical depth for scientific research.

The rapid development of artificial intelligence(AI) has brought unprecedented opportunities to chemistry education,while also raising a range of concerns.This study critically examines the capability of GPT-4 to score scientific essays in an undergraduate electrochemistry course.Using a multidimensional rubric,we compared GPT-4 evaluations with those from a human instructor across grammar,citation,logical structure,scientific accuracy,and critical thinking.Results revealed significant discrepancies:GPT aligned moderately in grammar but performed poorly in content-driven dimensions,with weak correlations across dimensions and the total score.The GPT model also showed score compression and ranking misclassifications,potentially disadvantaging technically strong students.These findings underscore the risks of relying on GPT as a sole grader for scientific writing.We recommend a hybrid framework combining GPT’s efficiency in objective aspects with human judgment in evaluating scientific reasoning and depth,ensuring fairness and academic integrity.

Fine and ultrafine denier polypropylene fibers are high-tech achievements developed independently by China in the 1980s and 1990s,reaching an internationally leading level.From 1987 to 1997,China successfully achieved industrial production of fine and ultrafine denier polypropylene filaments and completed the transformation of scientific and technological achievements through three stages:advanced research,technological development and industrial trials,and industrialization.This process not only served as a model for China’s industry-university-research cooperative development projects but also reflected the transformation of China’s scientific and technological activities and operational mechanisms against the backdrop of scientific and technological transformation.During this period,the Institute of Chemistry,Chinese Academy of Sciences provided solid support for the research and development,industrial production,and commercialization of fine and ultrafine denier polypropylene fibers through research on the spinning process,development of specialized materials,spinning technology development,and the establishment of technology companies.This paper focuses on the work of the Institute of Chemistry,systematically examines its participation in the entire process of research and development and industrialization of fine and ultrafine denier polypropylene fibers,analyzes the organizational models and characteristics of China’s high-tech industry-university-research cooperative innovation against the backdrop of scientific and technological transformation in the 1980s and 1990s,discusses the role and key functions of the Chinese Academy of Sciences in this process,and extracts lessons learned from the operational experience in science and technology to provide a historical reference for scientific and technological development in the new era.