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This study investigated how different learning tasks influence students' collaborative interactions in immersive Virtual Reality (iVR). A set of chemistry learning activities was designed with iVR, and 35 pairs of undergraduate students went through the activities. Videos of students' interactions were analysed to identify patterns in students' physical, conceptual, and social interactions. When students were manipulating conceptually familiar virtual objects (several water molecules), they perceived the tasks as a simple extension of prior knowledge and did not attempt to explore the 3D visualisation much. They did not move around to take different perspectives, and conceptual discussions were brief. Their prior power relations (leader-follower) carried over in iVR environments. In contrast, when conceptually unfamiliar chemical structures (protein enzyme) were displayed, students perceived the tasks as complex, demanding a new mode of learning. They spontaneously moved around to explore and appreciate the 3D visualisation of iVR. Walking to different positions to observe the virtual objects from multiple angles, students engaged in more collaborative, exploratory conceptual discussions. As the perceived complexity of learning tasks or virtual objects triggers different collaborative interactions amongst students, careful considerations need to be placed on the design of iVR tasks to encourage productive collaborative learning.

Magnetic molecular models help students explore molecular structures and interactions. In this study, we investigated how pairs of students used magnetic models to explore hydrogen bonding and the 6-fold symmetry of snowflakes. Fourteen first-year students enrolled in a chemistry unit participated in pairs. Students' interactions with the magnetic models and their peers were video recorded and later transcribed. Students' hand-drawn diagrams, verbal explanations, and gestures were used to evaluate students' conceptual understanding. Students showed distinctly different patterns of interaction depending on their prior knowledge of hydrogen bonding and how they socially interacted. Pairs with alternative prior understanding of hydrogen bonding relied on prompts while using magnetic models to feel the attraction and repulsion between two water molecules. They then constructed a tetrahedral structure and discussed its similarities with the branches of snowflakes. Pairs with a better understanding of hydrogen bonding interacted more with each other, used magnetic models to create ring structures, and explained their similarities with the 6-fold symmetry of snowflakes. Despite gaining a new understanding of hydrogen bonding, most student pairs' explanations did not extend to the massive 3D expansion of molecular structures to form a snowflake. Educators should consider the affordances of magnetic models and students' group dynamics when teaching molecular interactions to explain macroscopic-level phenomena.

In recent years, chemistry educators are increasingly adopting immersive virtual reality (IVR) technology to help learners visualise molecular interactions. However, educational studies on IVR mostly investigated its usability and user perceptions leaving out its impact on improving conceptual understanding. If they evaluated students' knowledge gains, they tended to use information recall tests to assess knowledge gains. Employing interviews and diagram-drawing tasks, this study explored how students' conceptual understanding of the nature of hydrogen bonds and the shape of snowflakes changed through a collaborative IVR experience on snowflakes. Participants were 68 undergraduate chemistry students. Videos of pre-/post-interviews and student-generated diagrams were analysed. The results indicated a marked improvement in students' conceptual understanding of the nature of hydrogen bonds among water molecules in snowflakes. After IVR, 57 students provided scientifically acceptable explanations of the nature of hydrogen bonds. Improvements in students' understanding were related to the intermolecular nature of hydrogen bonds, the role of lone pairs of electrons in forming hydrogen bonds, and molecular interactions in 3D space. This study suggests that collaborative IVR could be a powerful way for students to visualise molecular interactions, examine their alternative conceptions, and build more coherent understanding. Implications for the design and implementation of IVR activities for science learning are discussed.

This article reports the development of Chem'Sc@pe, an escape game activity for first- and second-year undergraduate students, covering various topics from an introductory organic chemistry course. The objective was to encourage them to review notions learned in class in a fun and collaborative environment. The set comprises a game board representing 6 rooms of a chemistry laboratory, 30 thematic cards with puzzles to solve (multiple-choice questions, exercise, calculation, and model handling), various tools such as molecular models, and an android-based application. Students in teams of three to four had 60 min to solve enigmas related to functional groups, organic nomenclature, hybridization, stereochemistry, as well as lab-based activities. Each correct answer provides players with a 4-digit code, which gives access through the application to further levels and eventually to the conclusion of the game. History cards offering a short biography of famous chemists were also included in the game to promote scientific culture. Chem'Sc@pe was tested in 2021 with 70 first year chemistry students at the University of Montpellier (France). Assessment of the gamification activity by the students returned excellent reviews, showing that they enjoyed playing the game, found it easy to play, and described it as a useful learning experience.

The main protease of SARS-CoV-2 is a promising drug target due to its functional role as a catalytic dyad in mediating proteolysis during the viral life cycle. In this study, experimentally proven 14 HIV protease peptides were screened against the main protease of SARS-CoV-2. Fourteen middle and high school "student researchers" were trained on relevant computational tools, provided with necessary biological and chemical background and scientific article writing. They performed the primary screening via molecular docking and the best performing complexes were subjected to molecular dynamics simulations. Molecular docking revealed that HIP82 and HIP1079 can bind with the catalytic residues, however after molecular dynamics simulation only HIP1079 retained its interaction with the catalytic sites. The student researchers were also trained to write scientific article and were involved with drafting of the manuscript. This project provided the student researchers an insight into multi-disciplinary research in biology and chemistry, inspired them about practical approaches of computational chemistry in solving a real-world problem like a global pandemic. This project also serves as an example to introduce scientific inquiry, research methodology, critical thinking, scientific writing, and communication for high school students.

Assessment of student learning within a degree program is an important but challenging endeavor. One goal of a programmatic assessment is to systematically collect evidence for chemistry majors' knowledge and understanding and to use the results to improve curriculum and instruction. Recently, the chemistry department at the United States Naval Academy developed a process to examine student learning in one particular thematic area of chemistry that was addressed in multiple courses throughout the entire curriculum, namely bonding. The assessment included the creation and implementation of an in-house-written, program-level assessment instrument administered to chemistry students at the end of the ACS-certified major. The exam, consisting of 13 free-response items, was collaboratively authored by a group of chemistry department faculty representing the 5 major subdisciplines recognized by the ACS Committee on Professional Training (analytical, biochemistry, inorganic, organic, and physical). Following administration of the instrument to 31 senior chemistry majors, analysis of student work revealed incomplete understanding and errors in process in several areas, including valence bond theory and ligand field theory. These results informed the design of further assessments conducted within the foundation-level lecture courses in the sophomore and junior years of the chemistry major and provided important information on possible areas of improvement within our curriculum.

COVID-19 has thrust educators into a period of uncertainty, complicating conventional ways of teaching and learning. We suspect that the pandemic has magnified the challenges that some high school teachers already experience, particularly when they are the sole chemistry teacher at their school. The pandemic has likely inhibited collegial interactions and access to professional development (PD). Our reflections from redesigning a face-to-face PD program to one that is remotely delivered provide recommendations that advance PD accessibility and interactivity to mitigate isolation and other longstanding challenges teachers may face. In this article, we discuss how the cognitive learning model informed emergent teaching practices that guided the transformation of the PD's implementation for 20 high school chemistry teachers. Our reflections on the PD's strengths, areas for improvement, and insights alongside participant feedback provide enduring guidelines for fellow teacher educators. Specifically, we forward the importance of conceptualizing theory-informed design principles first, and then modifying the delivery with appropriate tools and technologies. As PD facilitators, we also draw attention to the necessity for flexibility. Remaining open to adaptation during implementation is crucial to advance teacher learning and engagement. We hope our process for how and why our PD program was redesigned will inspire future teacher educators to explore new, postpandemic ways of maximizing high-quality PD experiences.

The COVID-19 pandemic has fundamentally changed many aspects of our world including the way we teach chemistry. Our emergence from the pandemic provides an opportunity for deep reflection and intentional action about what we teach, and why, as well as how we facilitate student learning. Focusing on foundational postsecondary chemistry courses, we suggest that we cannot simply return to "normal" practice but need to design and implement new ways of teaching and learning based on fundamentally reimagined learning outcomes for our courses that equip students for life after the rupture they have experienced. We recommend that new learning objectives should be guided both by an analysis of existing global challenges and the types of understandings and practices needed to confront them, and by research-based frameworks that provide insights into important areas of knowledge, skill, and attitude development. We identify a core set of competencies along three major dimensions (crosscutting reasoning, core understandings, and fundamental practices) that we believe should guide the design, implementation, and evaluation of chemistry curricula, teaching practices, and assessments in foundational courses for science and engineering majors. The proposed framework adopts systems thinking as the underpinning form of reasoning that students should develop to analyze and comprehend complex global systems and phenomena.

Multiple-choice (MC) exams are common in undergraduate general chemistry courses in the United States and are known for being difficult to construct. With their extensive use in the general chemistry classroom, it is important to ensure that these exams are valid measures of what chemistry students know and can do. One threat to MC exam validity is the presence of flaws, known as item writing flaws, that can falsely inflate or deflate a student's performance on an exam, independent of their chemistry knowledge. Such flaws can disadvantage (or falsely advantage) students in their exam performance. Additionally, these flaws can introduce unwanted noise into exam data. With the numerous possible flaws that can be made during MC exam creation, it can be difficult to recognize (and avoid) these flaws when creating MC general chemistry exams. In this study a rubric, known as the Item Writing Flaws Evaluation Instrument (IWFEI), has been created that can be used to identify item writing flaws in MC exams. The instrument was developed based on a review of the item writing literature and was tested for inter-rater reliability using general chemistry exam items. The instrument was found to have a high degree of inter-rater reliability with an overall percent agreement of 91.8% and a Krippendorff Alpha of 0.836. Using the IWFEI in an analysis of 1019 general chemistry MC exam items, it was found that 83% of items contained at least one item writing flaw with the most common flaw being the inclusion of implausible distractors. From the results of this study, an instrument has been developed that can be used in both research and teaching settings. As the IWFEI is used in these settings we envision an improvement in MC exam development practice and quality.

We investigated whether use of an adaptive-responsive online homework system (OHS) that tailors homework to students' prior knowledge and periodically reassesses students to promote learning through practice retrieval has inherent advantages over traditional-responsive online homework. A quasi-experimental cohort control post-test-only design with nonequivalent groups and propensity scores with nearest neighbor matching (n = 6,114 pairs) was used. The adaptive system was found to increase the odds of a higher final letter grade for average, below average, and failing students. However, despite the learning advantages, students self-reported less favorable attitudes toward adaptive-responsive (3.15 of 5) relative to traditional-responsive OHS (3.31). Specific to the adaptive OHS, the following were found: (i) student attitudes were moderately and positively correlated (r = 0.36, p < 0.01) to final letter grade, (ii) most students (95%) reported engaging in remediation of incorrect responses, (iii) a majority of students (69%) reported changes in study habits, and (iv) students recognized the benefit of using adaptive OHS by ranking its assignments and explanations or review materials as two of the top three most useful course aspects contributing to perceived learning. Instructors can use our findings to inform their choice of online homework system for formative assessment of chemistry learning by weighing the benefits, disadvantages, and learning pedagogies of traditional-responsive versus adaptive-responsive systems.

More science laboratories are being built because of larger enrollments in academics and schools. There is an increase in hands-on/process science effected by the renewed interest in and priority of science education. New science curricula like Biotechnology and Advanced college type program courses are being introduced with the use of exotic laboratory chemicals. The cost in dealing with chemicals in the science laboratories has been skyrocketing. All of these changes are putting pressure on the laboratory waste issue. This article offers information and specific recommendations on how schools can address hazardous waste generated by their science laboratories.

A multi-institution collaborative team of Australian chemistry education researchers, teaching a total of over 3000 first year chemistry students annually, has explored a tool for diagnosing students' prior conceptions as they enter tertiary chemistry courses. Five core topics were selected and clusters of diagnostic items were assembled linking related concepts in each topic together. An ordered multiple choice assessment strategy was adopted to enable provision of formative feedback to students through combination of the specific distractors that they chose. Concept items were either sourced from existing research instruments or developed by the project team. The outcome is a diagnostic tool consisting of five topic clusters of five concept items that has been delivered in large introductory chemistry classes at five Australian institutions. Statistical analysis of data has enabled exploration of the composition and validity of the instrument including a comparison between delivery of the complete 25 item instrument with subsets of five items, clustered by topic. This analysis revealed that most items retained their validity when delivered in small clusters. Tensions between the assembly, validation and delivery of diagnostic instruments for the purposes of acquiring robust psychometric research data versus their pragmatic use are considered in this study.

As carbon-based nanomaterials have such remarkable physical, chemical, and electrical capabilities, they have become a major focus of materials science study. A thorough examination of several carbon nanomaterial varieties, such as carbon nanotubes, graphene, fullerenes, and carbon nanodiamonds, is given in this review work. These materials all have distinctive qualities that qualify them for particular uses. This work starts by examining the synthesis processes of these nanomaterials, outlining the ways by which they are made and the variables affecting their ultimate characteristics. The specific features of each kind of carbon nanomaterial will then be briefly discussed in this study, along with their size, structure, and special physical and chemical properties. These materials have a wide range of possible uses in several fields. They are employed in the electronics industry to fabricate sensors, high-speed transistors, and other devices. Their high surface area and electrical conductivity make them useful in energy storage devices like supercapacitors and batteries. They are applied to environmental remediation and water purification in environmental science. They are employed in biomedicine for biosensing, bioimaging, and medication delivery. Notwithstanding the encouraging uses, the large-scale synthesis and functionalization of carbon nanomaterials present several difficulties. This review discusses the importance of carbon nanomaterials by studying their multifaceted properties and potential applications in industries. The novelty of this work lies in its detailed examination of the degradation and toxicity of these materials, which is essential for their safe integration into various technological and biomedical applications. By thoroughly analysing recent experimental results, this review aims to bridge the gap between fundamental research and practical applications.

This work presents a three-dimensional (3D) modeling exercise for undergraduate students in chemistry and health sciences disciplines, focusing on a protein-group linked to immune system regulation. Specifically, the exercise involves molecular modeling and structural analysis of tumor necrosis factor (TNF) proteins, both wild type and mutant. The structure of the tumor necrosis factor type 1 receptor (TNF-R1) is also briefly explored. TNF and TNF-R1 play major roles in maintaining human immune-system homeostasis. Upon binding with TNFR-1, the TNF can activate the nuclear factor kappa B (NF-?B), eventually resulting in apoptosis or cell death. These essential features of the clinically relevant TNF family is explored within the frame work of a readily adaptable tutorial.

Ice formation mechanisms in generating cells near stratiform cloud tops, where mixing and entrainment occurs in the presence of supercooled water droplets, remain poorly understood. Supercooled cloud droplet temperature and lifetime may impact heterogeneous ice nucleation through contact and immersion freezing; however, modeling studies normally assume the droplet temperature to be spatially uniform and equal to the ambient temperature. Here, we present a first-of-its-kind quantitative investigation of the temperature and lifetime of evaporating droplets, considering internal thermal gradients within the droplet, as well as thermal and vapor density gradients in the surrounding air. Our approach employs solving Navier–Stokes and continuity equations, coupled with heat and vapor transport, using an advanced numerical model. For typical ranges of cloud droplet sizes and environmental conditions, the droplet internal thermal gradients dissipate quickly (≤ 0.3 s) when droplets are introduced to new subsaturated environments. However, the magnitude of droplet cooling is much greater than estimated from past studies of droplet evaporation, especially for drier environments. For example, for an environment with 500 hPa pressure, and ambient temperature far from the droplet of −5 °C, the droplet temperature reduction can be as high as 24, 11, and 5 °C for initial ambient relative humidities of 10 %, 40 %, and 70 %, respectively. Droplet lifetimes are found to be tens of seconds longer compared to previous estimates, due to weaker evaporation rates because of lower droplet surface temperatures. Using these new end-of-lifetime droplet temperatures, the enhancement in the activation of ice-nucleating particles predicted by current ice nucleation parameterization schemes is discussed.

This paper describes an inexpensive experiment to determine the carbonyl stretching frequency of an organic keto compound in its ground state and first electronic excited state. The experiment is simple to execute, clarifies some of the fundamental concepts of spectroscopy, and is appropriate for a basic spectroscopy laboratory course. The experiment is complemented by an optional computational component.

Why is chemistry so difficult? A seminal paper by Johnstone (1982) offered an explanation for why science in general, and chemistry in particular, is so difficult to learn. He proposed that an expert in chemistry thinks at three levels; the macro (referred to as the observational level in this article), the sub-micro (referred to as the molecular level here), and representational (referred to as the symbolic level here). The observational level involves chemistry that is visible and tangible, incorporating what we can perceive with the senses. The molecular level of understanding consists of mental images that chemists use to imagine and explain observations in terms of atoms, ions and molecules. Observed phenomena and molecular-level processes are then represented in terms of mathematics and chemical notation at the symbolic level. In the early 1990s the VisChem project was funded to produce a suite of molecular animations, depicting the structures of substances and selected chemical and physical changes (Tasker et al., 1996), to address student misconceptions identified in the literature. For instance, only VisChem animations portray the vibrational movement in solid substances. This is important because this movement is correlated with temperature, and students need to understand this to interpret the significance of melting and boiling points in molecular-level terms. The need for a chemistry student to move seamlessly between Johnstone's three "thinking-levels" is a challenge, particularly for the novice. The author's work in the VisChem project indicates that animations and simulations can communicate many key features about the molecular level effectively, and these ideas can link the laboratory level to the symbolic level. However, the project has also shown that new misconceptions can be generated.

In the recent past, much nanotechnology research has been done in an effort to increase agricultural productivity. The Green Revolution led to the careless use of pesticides and artificial fertilizers, which reduced soil biodiversity and led to the development of disease and insect resistance. This article highlights the worldwide development and status of precision agriculture. Precision agriculture utilizes technologies and principles to manage spatial and temporal variability in agricultural production to improve crop performance and environmental quality. In precision agriculture (PA), information technology (IT) is used to make sure that crops and soil receive exactly what they require for optimal productivity and health. Precision farming includes the use of hardware i.e., a global positioning system (GPS) and geographic information system (GIS), different software of GIS, and traditional knowledge of agriculture management practices. The benefits of precision agriculture can be seen in both the economic and environmental aspects of agricultural production. Only nanoparticles or nanochips can transport materials to plants in a nanoparticle-mediated manner and create sophisticated biosensors for precision farming. Conventional fertilizers, insecticides, and herbicides can be nano encapsulated to provide exact doses to plants through a gradual, continuous release of nutrients and agrochemicals. The main topics included in this article are the variability of natural resources, variability management; administrative districts; the impact of precision farming technologies on farm profitability and the environment; innovations in sensors, controls, and remote sensing, information management; trends in global application and acceptance of precision farming technologies; potential and possibilities of technology along with challenges in agricultural modernization. Modern equipment and procedures based on nanotechnology have the ability to solve many of the issues in conventional agriculture and might transform this industry. There are many challenges in the implementation of smart agriculture equipment and approaches in the field as this technique uses both hardware and software. The cost of labour for managing IoT devices and the cost-of-service registration are included in the system operational cost. Additionally, there are operating costs related to the use of energy, maintenance, and communication between IoT devices, gateways, and cloud servers. In this review, nanotechnology is explored as a potential tool in precision agriculture, as well as the advantages of nanoparticles in agriculture, such as the use of fertilizers. By using precision agriculture, the food production chain can be monitored and quality and quantity can be managed effectively.

Over the past few decades, nanotechnology has gained momentum because of its potential to create a safer and healthier living environment using eco-friendly approaches. This study describes a safer, more dependable, and ecologically friendly technique of biologically synthesizing Cu/Fe/Ag trimetallic nanoparticles (NPs) using an aqueous leaf extract of Catharanthus roseus as the reducing and stabilizing agent. The synthesized trimetallic NPs were characterized by scanning electron microscope, Fourier transform infrared, dynamic light scattering, and ultraviolet–visible analysis and were evaluated for their potential applications, which included antioxidant properties and catalytic dye degradation. The result suggests that the antioxidant properties of Cu/Fe/Ag NPs are more significant than those of ascorbic acid, a known antioxidant, at lower doses (10 µg·ml−1) while a higher dose of 1,000 µg·ml−1 gives a 69.81% scavenging activity. The impact of Cu/Fe/Ag trimetallic NPs on the catalytic degradation of hazardous dyes such as phenol red (PR) and eosin yellow (EY) was also studied in this work. For PR and EY, the corresponding percentages of degradation were 76% and 48.6%, respectively.

Waste cooking oil has the potential to be a raw material for biodiesel. The use of heterogeneous catalysts and ultrasonicator will optimize the transesterification and environmentally friendly. Transesterification study of waste cooking oil with SrO-KF nano catalyst has been carried out. This researchs were: refinement of waste cooking oil, synthesis of SrO-KF nano-catalyst, and the transesterification. The catalyst applied ratio of 1:1, 1:2, and 1:3 of SrO:KF with concentrations of 2%, 3% and 4% by weight of oil respectively. The results of heterogeneous catalyst using XRD and SEM showed that SrF2, SrO and KF compounds had been formed. The optimum transesterification conditions were obtained on SrO-KF catalyst (1:2), concentration of 4% (w/w) with a yield of 84.4% (w/w). The methyl ester of waste cooking oil has density of 884 kg/m3, acid number of 0.48 mg/g, and viscosity of 4.2 cSt. Methyl esters of waste cooking oil were composed of 25.14% methyl palmitate and 33.65% methyl elaidate, 11.27% methyl linoleate, 10.14% methyl lauric and a mixture of methyl esters from waste cooking oil has the potential to be used as biodiesel.

The escalating issue of solid waste with a significant focus on plastic waste has prompted the exploration of alternative sustainable approaches for waste management. This paper discusses the pressing environmental challenges associated with solid waste, particularly plastics. It highlights the importance of implementing a systematic approach that aligns with the most effective environmental practices. With approximately 5.6 million tonnes of plastic waste produced annually in India alone, and only 12.3 % being recycled, there is a critical need for a sustainable plastic-waste management strategy. Traditional methods like landfilling, incineration, and recycling have some limitations, emphasizing the need for a sustainable approach. In this context, plastic biodegradation by microorganisms isolated from landfills presents a promising solution, efficiently breaking down plastics into carbon dioxide, water, and biomass in an eco-friendly manner. In recent years, substantial research efforts have been dedicated to identify microorganisms and enzymes with the ability to degrade plastics. This review thus, explores the limitations of conventional plastic waste management and delves into microbiological-based approaches, with the focus on recent advances and findings in this arena. The crucial prerequisite for sustainable and eco-friendly alternatives to combat plastic pollution is underscored. Therefore, this paper also explores the current challenges associated with the biodegradation of plastics and accentuates future prospects for the ongoing advancement of plastic biodegradation technologies.

Molybdenum oxide, belonging to the transition metal group, has garnered significant attention due to its diverse chemical properties, leading to extensive research in various fields. It manifests in multiple forms, including molybdenum oxides (MoO2 and MoO3), each showcasing distinct features. Their remarkable adaptability finds applications across different disciplines. This comprehensive review delves into the various oxidation states of molybdenum oxide, elucidating their unique features and applications across sectors such as solar cells, catalysts, gas sensors, electrochromic devices, batteries, and more. Additionally, the paper explores the utilization of molybdenum oxide in the petroleum and chemical industries, highlighting its multifaceted applications. This review examines its distinct features and underscores its potential as a material with significant promise for advancing technological innovation.

A prior study showed that students best make predictions about the outcome of opening a valve between two flasks containing a fluid or vacuum when they view both a demonstration video and a particulate animation, but the study showed no influence from the order in which these visualizations were used. The purpose of this current research was to study the effect of the order of visualization on students' particulate-level explanations. For this study, first-year general chemistry students in a south-central university in the United States were asked to choose, or type in their own explanations, for three experiments involving diffusion-effusion. Student ability to focus on particulate explanations was investigated after viewing either a macroscopic demonstration or an animated particle view. Students were directed to a Web site where they received one of two randomly assigned treatments. One group of students was shown the particulate animation first, followed by the macroscopic demonstration. For the other group, the order was reversed. Student explanations were assessed after each view. Finally, both groups were shown a side-by-side view of the animation and demonstration and their explanation was assessed one final time. Results showed that the order of visualizations did make a difference, with the macroscopic view followed by the particle view yielding significantly more particulate explanations. (Contains 7 tables and 8 figures.)

Untreated wastewater harbors dangerous pathogens, chemicals, and pollutants, posing grave public health threats. Nowadays, there is a rising demand for eco-friendly technologies for wastewater treatment. Recently, piezoelectric materials-based wastewater treatment technology has captured considerable interest among researchers because of its noninvasiveness and rapidity. Herein, a highly efficient piezoelectric composite material is designed with chitosan-incorporated bismuth ferrite (BFO) nanocrystals, to decompose pollutants and ablate bacteria in wastewater. On one hand, piezoelectric BFO has shown exclusive piezo-coefficient for ultrasound-mediated reactive oxygen species (ROS) production. On the other hand, chitosan depicts its biocompatible nature, which not only promotes cellular adhesion but also significantly elevates the ROS production capabilities of BFO under ultrasound. The synergistic effect of these two piezoelectric units in one composite entity shows an improved ROS production, eradicating ∼87.8% of Rhodamine B within 80 min under soft ultrasound treatment (rate constant, k ≈ 0.02866 min−1). After performing the scavenger experiment, it has been found that hydroxyl radicals are the dominating factor in this case. Further, the reusability of the composite piezocatalyst is confirmed through multiple cycles (five times) of the same experiment. The high polarizability of the composite material facilitates the generation of piezoelectric power through finger tapping (∼12.05 V), producing substantial instantaneous piezo-voltage. Moreover, the sample exhibits remarkable antibacterial activity, with nearly 99% bacterial eradication within 30 min. This indicates a significant advancement in utilizing biopolymeric composites incorporated with BFO for fabricating versatile devices with multidimensional applications.

An interdisciplinary team of science and education faculty at the University of Illinois at Chicago and several Chicago-area community colleges developed and implemented a series of four integrated, inquiry-based science courses for preservice elementary school teachers. All four courses are based on guiding principles taken from the rich literature on constructivist teaching and learning of science developed in recent decades. Further, their content and pedagogy align with national and state standards (National Academy of Sciences 1997; NRC 1996, 1997). This article describes each course and elaborates on a particular principle, sharing representative examples of how this principle is enacted in that course. (Contains 8 figures and 1 table.)

To illustrate the basic methodology involved in the quantum mechanics of molecules, a one-dimensional caricature of the hydrogen molecular ion (H[superscript +][subscript 2]) is presented, which is exactly solvable, in the Born-Oppenheimer approximation, in terms of elementary functions. The purpose of the exercise is to elucidate in a simple setting the standard approach to the electronic and vibrational states of molecules, a subject of interest to students of physics, chemistry and biology. (Contains 9 figures and 5 footnotes.)

Short circuiting an electrochemical cell is an unreported but persistent error in the electrochemistry textbooks. It is suggested that diagrams depicting a cell delivering usable current to a load be postponed, the theory of open-circuit galvanic cells is explained, the voltages from the tables of standard reduction potentials is calculated and the Nernst equation is discussed.

The relationship between aromaticity and stability in molecules on the basis of quantities such as hardness and electrophilicity is explored. The findings reveal that aromatic molecules are less energetic, harder, less polarizable, and less electrophilic as compared to antiaromatic molecules, as expected from the electronic structure principles.

It has become widely accepted that the computer is an indispensable tool in the study of science and technology. Thus, in recent years curricular programs such as Industrial Technology and associated scientific disciplines have been adopting and adapting the computer as a tool in new and innovative ways to support teaching, learning, and research. Industrial Technology is a management-oriented technical curriculum built upon studies from a variety of disciplines related to manufacturing technology. Included are a sound knowledge and understanding of material and production processes; principles of distribution; and concepts of industrial management and human relations. The importance of readily available technology and supporting software, which has flexibility in design and usage, has become an integral component of technology curriculums. The flexibility of these computer systems and their peripherals provides opportunities for interdisciplinary studies that extend well beyond the traditional technology curriculum into broader areas of science and mathematics. The facilities and curriculum described in this article support the ongoing collaborative work of students and faculty from the disciplines of computer science, chemistry, mathematics, physics, and industrial technology.

The BIO-MAÏDO (Bio-physicochemistry of tropical clouds at Maïdo: processes and impacts on secondary organic aerosols formation) campaign was conducted from 13 March to 4 April 2019 on the tropical island of Réunion. The main objective of the project was to improve understanding of cloud impacts on the formation of secondary organic aerosols (SOA) from biogenic volatile organic compound (BVOC) precursors in a tropical environment. Instruments were deployed at five sites: a receptor site, Maïdo Observatory (MO) at 2165 m a.s.l. and four sites along the slope of the Maïdo mountain. Observations include measurements of volatile organic compounds (VOCs) and characterization of the physical, chemical and biological (bacterial diversity and culture-based approaches) properties of aerosols and cloud water. Turbulent parameters of the boundary layer, radiative fluxes and emissions fluxes of BVOCs from the surrounding vegetation were measured to help interpret observed chemical concentrations in the different phases. Dynamical analyses showed two preferred trajectory routes for air masses arriving at MO during the daytime. Both trajectories correspond to return branches of the trade winds associated with upslope thermal breezes, where air masses likely encountered cloud processing. The highest mixing ratios of oxygenated VOCs (OVOCs) were measured above the site located in the endemic forest and the highest contribution of OVOCs to total VOCs at MO. Chemical compositions of particles during daytime showed higher concentrations of oxalic acid, a tracer of cloud processing and photochemical aging, and a more oxidized organic aerosol at MO than at other sites. Approximately 20 % of the dissolved organic compounds were analyzed. Additional analyses by ultra-high-resolution mass spectrometry will explore the complexity of the missing cloud organic matter.

Abstract In in-sensor image preprocessing, the sensed image undergoes low level processing like denoising at the sensor end, similar to the retina of human eye. Optoelectronic synapse devices are potential contenders for this purpose, and subsequent applications in artificial neural networks (ANNs). The optoelectronic synapses can offer image pre-processing functionalities at the pixel itself—termed as in-pixel computing. Denoising is an important problem in image preprocessing and several approaches have been used to denoise the input images. While most of those approaches require external circuitry, others are efficient only when the noisy pixels have significantly lower intensity compared to the actual pattern pixels. In this work, we present the innate ability of an optoelectronic synapse array to perform denoising at the pixel itself once it is trained to memorize an image. The synapses consist of phototransistors with bilayer MoS2 channel and p-Si/PtTe2 buried gate electrode. Our 7 × 7 array shows excellent robustness to noise due to the interplay between long-term potentiation and short-term potentiation. This bio-inspired strategy enables denoising of noise with higher intensity than the memorized pattern, without the use of any external circuitry. Specifically, due to the ability of these synapses to respond distinctively to wavelengths from 300 nm in ultraviolet to 2 µm in infrared, the pixel array also denoises mixed-color interferences. The “self-denoising” capability of such an artificial visual array has the capacity to eliminate the need for raw data transmission and thus, reduce subsequent image processing steps for supervised learning.

Natural biomass-derived carbon nanostructures have attracted research interest because of their unique surface and electrochemical properties. The present study embodied the carbonized micro-nano sheets derived from the low-cost natural source Kapok silk fiber. The material was obtained via a facile thermal pyrolysis process. Diffraction analysis showed a broad graphene structure-like peak, indicating the formation of graphene-like carbon nanosheets. Field emission scanning electron microscope (FESEM) and transmission electron microscopic (TEM) images confirmed the presence of fragmented carbon sheets, some of which were folded to form a tube-like structure. Raman study showed the presence of D and G band with the Id/Ig ratio of 0.96 which indicated the formation of few-layered carbon nanosheets. Furthermore, the electrochemical performance was evaluated for lithium-ion battery as well as supercapacitor. A specific capacity of 465 mAh.g-1 at 0.1 C rate for Li-ion battery and a specific capacitance of 473.61 F.g-1 for supercapacitor have been obtained with the capacitance retention of 95 %. This study provides insights into a strategy for the sustainable production and utilization of natural fiber-based carbon in energy storage systems.

The industrial revolution has improved living standards while destroying the natural world, and as a result, environmental pollution has become a serious concern for both developed and developing countries. Furthermore, photocatalysis is a chemical process that uses light energy to accelerate thermodynamically demanding operations, such as photosynthesis, which makes it a viable substitute for deep solar energy storage. Reduced exposure to chemicals and toxins released into the environment by industrial activity is another great benefit of this method. First and foremost, photocatalysis allows fossil fuels to be used for other purposes by substituting low-temperature pollution removal processes with high-temperature ones. Since they may exist in numerous valences and have excellent catalytic efficiency, various photocatalytic materials such as AgCl, P-doped g-C3N4, and Z-scheme photocatalysts coupled with Fe3O4/H2O2 have received interest as photocatalysts. One issue covered in the reviews is the Z-scheme strategy, which focuses on creating heterojunctions with appropriate band alignments to improve electron transport pathways and increase MnO2's photocatalytic activity. The review discusses the latest developments in photocatalysis, MnO2-based composites for photocatalytic capabilities, and the Z-scheme charge carrier mechanism. The electrical, photoelectric, and crystallographic properties of MnO2 are discussed in the review article, with a focus on the relevance of the Z-scheme electron transfer pathway in augmenting photocatalytic activity. Exploring several electron transport channels in MnO2-based composites, various characterization approaches offer insights into the Z-scheme mechanism. Moreover, we have reviewed various Photocatalysis, basic principles, processes, and materials.

The use of cerium oxide nanoparticles as a corrosion inhibitor for the CO2 corrosion of LDX 2101 duplex stainless steel has been evaluated using potentiodynamic polarization curves, linear polarization resistance and electrochemical impedance spectroscopy tests. Polarization curves have shown that CeO2 nanoparticles behaved as an efficient mixed type of inhibitor, with an efficiency that increases with its concentration reaching a maximum value when 600 ppm of nanoparticles were added. CeO2 nanoparticles were chemically adsorbed onto the steel surface according to a Langmuir type of adsorption isotherm. A passive layer was formed by the addition of CeO2 nanoparticles with lower passive current density and higher pitting potential values than those obtained without these nanoparticles. Corrosion current density decreased whereas the polarization resistance increased by two orders of magnitude in both cases with the addition of the nanoparticles. Similarly, the double layer capacitance was decreased due to the adsorption of the nanoparticles. Steel was susceptible to pitting type of corrosion, but its number and diameter decreased with the nanoparticles.

Continuous developments in detection technology are necessary because of the considerable threats that explosive materials represent to public safety and security. Optical sensors have emerged as powerful instruments for this purpose, offering non-invasive, real-time, and highly sensitive detection capabilities. This review paper provides a comprehensive analysis of the current state of research in optical sensors such as Laser-induced fluorescence, Raman spectroscopy, and photoluminescence based sensors intended to detect explosive compounds. This study delves into the basic concepts of optical sensing technologies, classifies different kinds of optical sensors according to their construction and functionality, and examines their wide range of uses in public safety, transportation security, and the military. The difficulties that optical sensors encounter—such as environmental influences or interferences and problems with specificity—are reviewed, along with the research that is now being done to solve these difficulties. The benefits and drawbacks of optical sensors are brought to light through a comparison with conventional detection techniques. Furthermore, new developments that will impact explosive materials identification in the future are identified in the article, including the fusion of machine learning and nanotechnology. By synthesizing existing knowledge and providing insights into the strengths, challenges, and future directions of optical sensors, this review aims to be a valuable resource for researchers, practitioners, and policymakers involved in enhancing explosive materials detection capabilities.