Chimia最新文献

Practicing research in high school is essential for preparing future university students, fostering critical thinking, and situating scientific knowledge within a broader context. However, such training remains rare in upper secondary education. Over the past 10 years, we have developed a research programme tailored for high school students, in which they create colorimetric sensors for analytes of societal importance using the simple strategy of indicator displacement assay (IDA). This initiative has led not only to publications, including in international journals, but also to awards and recognition at the Fall meeting of the Swiss Chemical Society (SCS), benefiting both our students and the broader scientific community. Each year, our students have presented their research at the SCS, gaining valuable experience in scientific communication. Moreover, the concept has extended beyond high school: the expertise gained in this program has directly contributed to initiating a PhD in the field of sensing. Taken together, these outcomes illustrate that such a visionary programme has great potential to be further developed and implemented in high schools. It therefore should be supported by institutions to promote excellence in science and chemistry. We hope that this article will inspire the scientific community to recognize and promote the importance of early research training in fostering excellence in science and chemistry.

The thesis of this study is that communicating research achievements is an important component of research and technology management in chemistry research. New chemical products and new synthetic and analytical chemical processes often have a broad and lasting socioeconomic and environmental impact. Besides differentiating chemistry from other basic sciences, this trait is reinforced by the sustainability challenge to make economic growth compatible with long-term well-being for all people and the environment. Following a succinct review of previous scholarly work on chemistry communication, we identify the key benefits provided to chemistry scholars by the effective communication of chemistry innovation to the public.

Artificial Intelligence (AI) is increasingly integrated into daily life and various other sectors, including medicine, agriculture, and education. While AI offers personalized learning, automated feedback, and reduced teacher workload, its formal use in schools remains limited. Nonetheless, many students already engage with AI tools such as ChatGPT to understand concepts and access information, raising questions about their perceptions and competencies. This study investigates students' prior experience with AI in school as well as their AI literacy. Further, it examines changes after a teaching unit using AI tools and compares AI supported learning to traditional instruction. Results indicate that hands-on exposure enhances students' self-efficacy, cognitive engagement and ethical awareness, though confidence in creating AI-driven solutions remains lower. Students valued both AI-supported and teacher-led learning, suggesting that students benefit most from hybrid approaches. Ethical considerations were prominent, emphasizing fairness and responsible use, yet technical understanding of AI design lagged behind. Overall, structured AI education can strengthen skills, ethical reflection, and problem solving, but successful integration requires balancing technological tools with teacher guidance, supporting higher-order skills, and promoting sustained engagement.

This article presents a comprehensive overview of modeling and simulation strategies for chemically reacting systems using the COMSOL Multiphysics®software, with a focus on applications in chemical engineering and chemistry education. Beginning with the historical development of the Chemical Reaction Engineering Module and its integration with the CFD Module, we describe how these tools implement the equations of change, reaction kinetics, and thermodynamics for both idealized and spatially resolved systems. The modeling strategy emphasizes a progression from space-independent models to fully coupled multiphysics simulations, illustrated with examples including selective catalytic reduction, heterogeneous catalysis with dual-porosity media, and reacting flow systems in pharmaceutical processes. The use of extra dimensions for intraparticle transport, as well as integration of fluid flow, heat transfer, and chemical reactions, demonstrates the software's capability to address multiscale and multiphysics problems. Finally, we discuss emerging approaches using surrogate models and deep neural networks to accelerate simulations and enable real-time interactivity in the classroom. These methods broaden the pedagogical scope, enabling students - from undergraduate students to graduate researchers - to explore complex reacting systems with greater accessibility, speed, and engagement.

Artificial intelligence (AI) and machine learning (ML) are developing fast and are increasingly adopted in both chemical industry and academic research. With the projected role such tools will play in the future, for every chemist, these developments call for a fundamental and sound education for future generations of scientists in these areas. In this perspective, we describe the development of the course Digital Chemistry at ETH Zurich, which addresses these topics. In particular, we outline our approach to teaching ML and its applications in chemistry. We especially emphasize that the skills of understanding, applying and critically assessing ML models will be fundamental for future chemists. We hope that this article will serve as inspiration for educators in this field and help to enhance the teaching in this area of future significance.

General-purpose AI already correctly solves most traditional assessment problems in first-year STEM education, and it continues to become more proficient with every release. This quiet superheating of familiar practices by increasing AI capabilities will yield a messy eruption unless instructors introduce deliberate 'nucleation sites' and shake up the curriculum. We argue that results of science education research are now more relevant than ever since they provide insights and strategies on how to optimize human learning. Finally, we emphasize the importance of community and wellbeing - through peer instruction, studios, and brief, structured oral checks with whiteboarding - to counter loneliness and fatalism. As most of these instructional methods involve open-ended tasks, which tend to be more resource-intensive in grading and feedback than traditional, solution-oriented closed-form answer practices, AI can play an important role in assisting and supporting human educators. Thus, we illustrate how ETH Zurich's Ethel system operationalizes these approaches through a course-grounded chatbot, formative feedback on handwritten work, on-demand practice, and grading assistance, while keeping learning human.

Since 1998, Thun High School has developed and implemented interdisciplinary, problem-based learning projects with the aim of preparing students for the successful completion of their Matura thesis. These projects have been integrated into the specialised subjects biology-chemistry course. To date, 11 large-scale projects and a number of smaller projects have been created. As well as teaching subject-specific content, these projects also develop interdisciplinary skills such as: self-organised learning; using scientific publication formats; conducting literature research; organised collaboration; and the preparation for the oral Matura examination. Each class completes at least three of these projects in the core biology-chemistry course. As teachers, we increasingly withdraw from instruction and guidance, thereby giving students more responsibility for the success of the project. This article presents the didactic concept using a concrete example and provides links to further information and insights into our various projects. Additionally, student feedback is presented, as well as the challenges and opportunities of interdisciplinary teaching.

Pharmaceutical industries play a crucial role in enhancing global health outcomes; however, like many other sectors, they also encounter significant environmental challenges. The extraction of raw materials and the manufacture of active pharmaceutical ingredients (APIs) result in considerable waste production, substantial resource consumption, and environmental pollution. Transitioning from traditional linear economic models to circular processes presents an opportunity for more sustainable pharmaceutical operations that benefit both communities and the environment. The circular economy framework - grounded in resource efficiency, waste minimization, and material regeneration - offers a path towards comprehensive sustainability in pharmaceutical practices. This is particularly relevant in the area of solvent usage, which accounts for over half the input mass and associated waste in most processes. This article examines the application of circular economy principles to solvent selection within process design, highlighting its significance as a central component of sustainable pharmaceutical development.

An integrated one pot protocol for the in situ generation of hazardous alkyl diazoacetates (from glycine ester hydrochloride) and their subsequent reaction with 3-alkenyl oxoindoles (generated via the in situ Wittig reaction from isatin derivatives) to afford diastereomeric mixtures of spirocyclopropyl oxoindoles in toluene at room temperature is presented. Spirocyclopropyl oxoindoles are interesting building blocks prevalent in many active pharmaceutical ingredients and in natural products. This protocol is devoid of any metal catalysts or bases.