Materials Science Research Articles

How Can Materials Chemists Contribute to Food Supply Security in the Age of AI and Robotics?

AbstractGlobal factors are compromising the security of the food supply. Many of us in our community might be unsure about how to help with our seemingly inapplicable expertise. In this piece, I describe how materials chemistry and materials chemists will be essential in addressing this problem, but not only in the way we might think. There is a gigantic and largely unexplored opportunity for real societal impact if we accept a broader view of what academic materials chemistry can be.

The Importance of Offline Options for Online Learners

The popularity of MOOCs and MOOC platforms prompted some universities to develop their first online courses, while others experimented with the format of existing online offerings. Despite the body of research identifying cognitive, metacognitive, and practical benefits of printed materials, there has been a shift towards an approach that privileges online resources, reducing opportunities to access resources offline or in printed form. Online courses can be produced more quickly and cheaply than those providing both printed and digital options. They can also benefit learners in a society that values digital skills and literacies. This paper, informed by the principles of universal design for learning (CAST 2018), asks ‘What are the benefits to students of offering downloadable/printable versions of online study materials and supporting offline study?’. It takes a phenomenological approach, exploring the experience of 100 postgraduate learners on an online course delivered on the FutureLearn platform. Data was extracted from a large dataset that included all the students’ course discussion postings (N = 17,158). Data analysis identified the importance of the online/offline divide and showed that, as students’ contexts change, the benefits and accessibility of online, offline and print versions shifts. Printed and digital materials support different ways of learning and can have an affective impact. These findings point to ways in which learning design, skills training, and technical changes might be used to increase the affordances of digital materials for learners.

Generation and characterization of giant panda induced pluripotent stem cells

The giant panda ( Ailuropoda melanoleuca ) stands as a flagship and umbrella species, symbolizing global biodiversity. While traditional assisted reproductive technology faces constraints in safeguarding the genetic diversity of giant pandas, induced pluripotent stem cells (iPSCs) known for their capacity to differentiate into diverse cells types, including germ cells, present a transformative potential for conservation of endangered animals. In this study, primary fibroblast cells were isolated from the giant panda, and giant panda iPSCs (GPiPSCs) were generated using a non-integrating episomal vector reprogramming method. Characterization of these GPiPSCs revealed their state of primed pluripotency and demonstrated their potential for differentiation. Furthermore, we innovatively formulated a species-specific chemically defined FACL medium and unraveled the intricate signaling pathway networks responsible for maintaining the pluripotency and fostering cell proliferation of GPiPSCs. This study provides key insights into rare species iPSCs, offering materials for panda characteristics research and laying the groundwork for in vitro giant panda gamete generation, potentially aiding endangered species conservation.

Advancing Thermochromic Glass Durability: Reinforcing Thermosensitive Hydrogels with Enhanced Adhesion Techniques

The growing use of glass in architecture has driven research into reducing its energy consumption. Thermochromic (TC) glass technology shows promise for enhancing building energy efficiency by regulating solar heat dynamically. Although TC glass helps reduce heat radiation, additional solutions like Low-E or vacuum glass are needed to control heat convection and conduction. Low-E glass, while effective in lowering heat transfer, may increase surface temperature. Thermo-sensitive hydrogels, known for their light-scattering properties at high temperatures, have been explored to complement TC glass. However, their stability at elevated temperatures remains a challenge, especially for applications requiring durability under varying weather conditions. This study proposes enhancing the adhesion between hydrogel and glass by introducing silica–oxygen bonds. As a result, TC glass demonstrates stable performance over 100 cycles within temperature ranges from 85 °C to 30 °C in summer and 40 °C to −20 °C in winter. Furthermore, by incorporating ethylene glycol, the freezing point of TC glass is reduced to −26 °C, rendering it suitable for use in colder regions. The implementation of TC glass effectively addresses the dual requirements of summer shading and winter heating in areas with both cold winters and hot summers, significantly reducing building energy consumption. This study contributes substantially to developing advanced intelligent building materials, paving the way for more sustainable architectural designs.

Antimicrobial Biomaterials Based on Physical and Physicochemical Action

AbstractDeveloping effective antimicrobial biomaterials is a relevant and fast‐growing field in advanced healthcare materials. Several well‐known (e.g., traditional antibiotics, silver, copper etc.) and newer (e.g., nanostructured, chemical, biomimetic etc.) approaches have been researched and developed in recent years and valuable knowledge has been gained. However, biomaterials associated infections (BAIs) remain a largely unsolved problem and breakthroughs in this area are sparse. Hence, novel high risk and potential high gain approaches are needed to address the important challenge of BAIs. Antibiotic free antimicrobial biomaterials that are largely based on physical action are promising, since they reduce the risk of antibiotic resistance and tolerance. Here, selected examples are reviewed such antimicrobial biomaterials, namely switchable, protein‐based, carbon‐based and bioactive glass, considering microbiological aspects of BAIs. The review shows that antimicrobial biomaterials mainly based on physical action are powerful tools to control microbial growth at biomaterials interfaces. These biomaterials have major clinical and application potential for future antimicrobial healthcare materials without promoting microbial tolerance. It also shows that the antimicrobial action of these materials is based on different complex processes and mechanisms, often on the nanoscale. The review concludes with an outlook and highlights current important research questions in antimicrobial biomaterials.

Droplets can enhance microcapsule deformation in channel flow

The dynamics of soft microparticles enclosed in a droplet flowing in a channel is an unexplored fundamental problem that lies at the heart of numerous applications, including droplet-based microfluidics, tissue engineering and smart material synthesis. Here we show that enclosing a flexible capsule into a droplet can amplify the capsule’s deformation parameters in channel flow by up to two orders of magnitude. Previously unreported capsule equilibrium shapes in channel flow, including an oblate spheroid and a reversed bullet, have also been discovered. We propose two theoretical models to predict the equilibrium position of the capsule inside the droplet, and estimate the capsule deformation, respectively. The present study provides an effective but simple approach to enhance and control the deformation of soft particles in a flowing suspension, which may inspire widespread applications, from high-throughput single-cell mechanical phenotyping, enhanced cross-membrane drug delivery, to manufacturing shape-controlled non-spherical particles and artificial cells.

How is graphene influencing the electronic properties of NiO-TiO2 heterojunction?

Abstract We synthesized a new nanocomposite bearing nitrogen-doped graphene as a carbon additive to the nickel oxide nanoparticles-titanium dioxide nanotubes heterojunction. The main purpose was the comparison of its structural and electronic properties, hence potential applications, with its undoped, reduced graphene oxide homolog. The beneficial effect of graphene on TiO2 heterojunctions is an accepted fact in the materials science field, mainly in favor of the nitrogen-doped one. Our data show that both graphenes have little influence on the band offset values of the NiO-TiO2 heterojunction. Still, the presence of reduced, undoped graphene oxide allows an improved electron transfer process from titania, causing a better charge carriers’ separation. This correlates well with their observed photocatalytic activity under visible light exposure, for the degradation of four emerging contaminant pollutants (amoxicillin, acetaminophen, ibuprofen, and β-estradiol). In addition, the band alignment of the NiO-TiO2 heterojunction with graphenes, and the corrected thermodynamic potentials of the organic pollutants explain well the observed photocatalytic behavior.

Activating supercooled electrolytes

Abstract While materials science research in the rechargeable battery field is usually application-oriented, the general supercooled liquid theory from glass science can drive high-performance low-temperature aqueous batteries, facilitating cross-disciplinary collaborations and simultaneous research break- throughs.

How Can Materials Chemists Contribute to Food Supply Security in the Age of AI and Robotics?

How Can Materials Chemists Contribute to Food Supply Security in the Age of AI and Robotics?

Диагностика сформированности смыслового чтения при работе учеников средней школы с учебными математическими текстами

Learning is working with a variety of educational texts based on reading, understanding, evaluating and interpreting information. To identify the result of reading an educational mathematical text and the quality of understanding the meaning of the text space created by educational materials, it is necessary to diagnose reading, namely, the level of semantic reading. In the modern study of reading, the PISA international monitoring, the concept of reading literacy, its components and levels are defined. The success of understanding more complex educational mathematical texts will depend on the level of reader literacy. If the levels of reading literacy have evaluation criteria and diagnostic apparatus, then how to assess the level of semantic reading? The article examines the relationship between the levels of reading literacy and text comprehension, models for assessing the semantic complexity of the text and semantic reading skills, various level structures for diagnosing the understanding of a mathematical educational text. Based on the studied scientific material, the complexity of the educational mathematical text "Triangle" was assessed according to criteria such as the number of words, simple words, scientific terms and their complexity, the number of mentions of scientific terms in each paragraph. Diagnostic material has also been created to check the understanding of this text, each task of which is aimed at determining the understanding of each information block and assessing the degree of development of semantic reading.

Machine learning based predictive analysis of DNA cleavage induced by diverse nanomaterials

DNA cleavage by nanomaterials has the potential to be utilized as an innovative tool for gene editing. Numerous nanomaterials exhibiting DNA cleavage properties have been identified and cataloged. Yet, the exploitation of property data through data-driven machine-learning approaches remains unexplored. A database was developed, compiling thirty distinctive characteristics, encompassing physical and chemical properties, as well as experimental conditions of nanomaterials that have demonstrated DNA cleavage capability such as in articles published over the past two decades. The DNA cleavage effect and efficiency of nanomaterials were predicted using machine learning algorithms such as support vector machines, deep neural networks, and random forest, and a classification accuracy of 0.93 for the cleavage effect was achieved. Moreover, the potential of utilizing larger datasets to enhance the predictive capacity of models was discussed. The findings indicate the feasibility of predicting nanomaterial properties based on experimental data. Evaluating the performance and effectiveness of the machine learning models trained using the existing data can furnish valuable insights for future materials research endeavors, especially for the design of DNA cleavage with specific sites.

Ecological Innovations in Hotel Companies: A Case Study of Poland

Entrepreneurship is one of the key pillars of the modern market economy. The most important attributes of entrepreneurship include innovation. According to many economists, most of the economic growth of developed countries should now be linked to the application and implementation of innovation. Among many types of innovations, ecological innovations (eco-innovations) deserve special attention. Ecological innovations contribute to the reduction of operating costs, increase in competitive advantage and facilitate entry into new markets. At the same time, they have a positive impact on the natural environment. The examples of eco-innovations are also increasingly often found in hotel companies. The aim of the publication is to discuss the current examples of the most significant ecological innovations in hotel enterprises. The article considers the significant impact of ecological innovations on the activities of this type of enterprises. In order to achieve the objectives of the publication, the Polish hotel market was taken into account. The article presents the following research thesis: Environmental innovations are an increasingly important element influencing the operation of hotel enterprises in Poland. However, there is still little awareness of them among guests. The article was written on the basis of books studies, monographs, magazines and netographic information. Methodology of research carried out for the needs of the work. To identify and analyze ecological innovations in hotels in Poland, as well as for the purposes of achieving the goals of the work, two methods of collecting primary research material were used. The first one is based on the analysis of existing data, including the analysis of guest opinions on the booking portal and literary criticism. The second one consisted of a diagnostic survey in which a non-standardized interview was used as a research technique on a deliberately selected group of hotel owners and managers from all over Poland, who have decided to introduce ecological innovations on the premises of their facilities. Interviews were conducted in January-February 2024. The interview did not take into account objects that temporarily suspended their activity. The results of the research positively verify theses.

Application of photothermal beam deflection spectrometry for non-destructive evaluation of advanced materials: a state-of-the-art review

Abstract The progress made in lasers and data acquisition systems has paved the way for innovative non-destructive evaluation methods based on the photothermal phenomenon. Beam deflection spectrometry (BDS) is a photothermal spectroscopic technique that offers ultra-sensitivity, high signal-to-noise ratios, and reduced sample preparation requirements. These advantages provide precise assessment of advanced material (AM) properties. This review presents a comprehensive in-depth analysis, thus helping researchers to understand the potential and future perspectives of BDS along with the theory, instrumentation, and application supported by the literature data. The objective of this review is also to present the possibilities of BDS in the characterization of AMs, including organic, inorganic, and hybrid organic–inorganic materials in the form of thin films, coatings, composites, and nanomaterials.

Phrasebook in Text Typology: a Type of Textbook or an Independent Type of Text?

Introduction. A phrasebook as a type of text is aimed at providing the basics of communication in situations when the knowledge of a foreign language is absent. It can not be classified as a type of a dictionary, textbook or manual for the development of speaking skills. The article examines the problem of determining the status of a phrasebook in the typology of text types. The study is aimed at a diachronic analysis of the texts and structure of phrasebooks to identify features that unite a phrasebook with a textbook, as well as to determine the properties inherent only to a phrasebook, allowing it to be distinguished as an independent type of text. The lack of works that consider the problem of determining the status of a phrasebook determines the relevance of the study.Methodology and sources. The research material – the texts of German-Russian and Russian-German phrasebooks of the XVIII–XXI centuries, covering the time period from 1795 to 2011, which were created both for teaching the German or Russian language, and for practical use during travel. The general (educational and tourist) phrasebooks were chosen because of the fact that they reflect different aspects of interaction between representatives of language communities in predetermined situations.Results and discussion. The comparison has shown that a phrasebook is an independent type of text, at different stages of its historical development having more or less similar features with a textbook, dictionary and a manual for the development of oral speech skills, but differing significantly from them. In the course of its historical development, the cohesive connections between the linguistic units of the phrasebook weaken: from a book containing coherent and logical dialogues on various topics (XVIII–XIX centuries), the phrasebook turns into a manual with a set of thematically organized template phrases and lists of words (late XX–XXI centuries).Conclusion. The phrasebook, thus, is a type of text that is closely related to the era of creation, which is reflected not only in the theme and structure, but also in the strength of the cohesive connections of the linguistic units that make up the phrasebook.

Data-Driven Materials Research and Development for Functional Coatings.

Functional coatings, including organic and inorganic coatings, play a vital role in various industries by providing a protective layer and introducing unique functionalities. However, its design often involves time-consuming experimentation with multiple materials and processing parameters. To overcome these limitations, data-driven approaches are gaining traction in materials science. In this paper, recent advances in data-driven materials research and development (R&D) for functional coatings, highlighting the importance, data sources, working processes, and applications of this paradigm are summarized. It is begun by discussing the challenges of traditional methods, then introduce typical data-driven processes. It is demonstrated how data-driven approaches enable the identification of correlations between input parameters and coating performance, thus allowing for efficient prediction and design. Furthermore, carefully selected case studies are presented across diverse industries that exemplify the effectiveness of data-driven methods in accelerating the discovery of new functional coatings with tailored properties. Finally, the emerging research directions, involving integrating advanced techniques and data from different sources, are addressed. Overall, this review provides an overview of data-driven materials R&D for functional coatings, shedding light on its potential and future developments.

Beyond absorption maxima: the impact of wavelength-resolved photochemistry on materials science.

Reflecting on Giacomo Ciamician's revolutionary vision of harnessing sunlight to drive photochemical transformations, the field of materials science has evolved significantly, yet it has been constrained by the misconception that the highest reactivity in photochemical systems is achieved at the absorption maxima. Here, we explore this notion further with evidence from photochemical action plots, demonstrating that reactivity can indeed be maximal at wavelengths significantly separated from the absorption peak. By examining the implications of the disparity between absorptivity and photochemical reactivitiy, we explore its impact for the enhanced penetration depth of light in photoresists, the reduction of energy requirements for photochemical reactions, and its transformative potential for volumetric 3D printing. Ultimately, we argue for a renewed appreciation of light's capability to facilitate photochemical reactions across the entire volume of a material.

Microfluidics and Nanofluidics in Strong Light–Matter Coupling Systems

The combination of micro- or nanofluidics and strong light–matter coupling has gained much interest in the past decade, which has led to the development of advanced systems and devices with numerous potential applications in different fields, such as chemistry, biosensing, and material science. Strong light–matter coupling is achieved by placing a dipole (e.g., an atom or a molecule) into a confined electromagnetic field, with molecular transitions being in resonance with the field and the coupling strength exceeding the average dissipation rate. Despite intense research and encouraging results in this field, some challenges still need to be overcome, related to the fabrication of nano- and microscale optical cavities, stability, scaling up and production, sensitivity, signal-to-noise ratio, and real-time control and monitoring. The goal of this paper is to summarize recent developments in micro- and nanofluidic systems employing strong light–matter coupling. An overview of various methods and techniques used to achieve strong light–matter coupling in micro- or nanofluidic systems is presented, preceded by a brief outline of the fundamentals of strong light–matter coupling and optofluidics operating in the strong coupling regime. The potential applications of these integrated systems in sensing, optofluidics, and quantum technologies are explored. The challenges and prospects in this rapidly developing field are discussed.

Implementing innovation in project-based learning in electro-mechanical engineering education

This study investigates the implementation of project-based learning (PBL) in electro-mechanical engineering education, emphasizing the modeling and application of an innovation process to enhance student engagement, motivation, and employability. Initially, the innovation process was systematically modeled using Structured Analysis and Design Technique (SADT) to manage and organize skills, knowledge, and resources effectively. This model was subsequently applied in an educational experience focused on highly technical aspects such as energy conversion modeling, mechanical improvements, material science, and efficiency analysis. These aspects were primarily applied in the context of permanent magnet synchronous machines employed in electric vehicle (EV) axles. The SADT modeling allowed for a clear delineation of the innovation phases, ensuring a structured approach to project execution. Statistical analysis of the PBL approach indicated significant improvements in student performance, with a 25% increase in problem-solving skills and a 30% enhancement in critical thinking abilities. The case study demonstrated that industry-oriented projects significantly boost student satisfaction, particularly in problem definition and solution identification, leading to a more engaging and effective learning experience.

Liposomal Drug Delivery for Neurological Disorders: Advances and Challenges

Abstract: Liposomal drug delivery methods are becoming increasingly viable options for improving treatment outcomes for neurological illnesses. These systems provide a flexible framework for the formulation of medications intended for delivery to the brain, protecting the medication from enzymatic breakdown and enhancing its bioavailability. To maximize liposome-drug interactions and improve brain-targeted delivery efficiency, a variety of formulation strategies are used, such as surface modification and remote loading. By utilizing various pathways to cross the blood- -brain barrier (BBB), such as passive diffusion and receptor-mediated transcytosis, liposomes facilitate the effective transport of therapeutic drugs to the brain parenchyma. Liposomal formulations show potential for targeted drug delivery, reducing off-target effects, and improving treatment efficacy in neurological conditions like Parkinson's disease, Alzheimer's disease, stroke, multiple sclerosis, and brain cancers. For instance, in Parkinson's disease, liposomal delivery of neuroprotective agents can help maintain dopamine levels and protect dopaminergic neurons. In Alzheimer's disease, liposomes can be engineered to deliver drugs that reduce amyloid-beta plaques or tau tangles. For brain cancer, liposomal chemotherapy can target tumor cells more precisely while minimizing damage to surrounding healthy tissue. In stroke, liposomal delivery of neuroprotective agents can reduce the extent of brain damage, while in multiple sclerosis, liposomes can be used to deliver drugs that modulate the immune response. However, the clinical translation of liposomal drug delivery systems for brain diseases faces challenges related to scalability, stability, and immunogenicity, in addition to regulatory barriers. Scalability issues arise from the complex manufacturing processes required to produce liposomes consistently on a large scale. Stability concerns involve maintaining the integrity of liposomes during storage and after administration. Immunogenicity can be a problem if the liposomes trigger an unwanted immune response, potentially reducing their effectiveness or causing adverse effects. To overcome these obstacles, multidisciplinary cooperation is essential. Collaboration among materials scientists, pharmacologists, neurologists, and regulatory experts can drive the development of more robust liposomal formulations. Continuous research is needed to refine liposome designs, such as by optimizing lipid composition, surface charge, and size to improve stability and targeting capabilities. Advanced techniques like PEGylation (coating liposomes with polyethylene glycol) can help reduce immunogenicity and extend circulation time in the bloodstream. Despite these challenges, liposomal methods present intriguing prospects for transforming medication administration to the brain and offering effective treatments for neurological illnesses. The development of more sophisticated liposomal technologies, combined with a deeper understanding of their mechanisms of action, could lead to significant breakthroughs in the treatment of neurological disorders. For example, research into ligand- targeted liposomes, which use specific molecules to bind to receptors on the BBB, holds promise for enhancing delivery specificity and efficiency. To fully realize the therapeutic promise of these novel drug delivery systems, further advancements in liposomal technologies and a deeper understanding of their mechanisms are necessary. This includes not only technical improvements but also comprehensive preclinical and clinical studies to evaluate safety, efficacy, and long-term effects. As our knowledge expands and technology progresses, liposomal drug delivery could become a cornerstone of neurological disease treatment, providing new hope for patients with previously intractable conditions.

Studies of Phase Transformation Kinetics in the System of Nanocrystalline Iron/Ammonia/Hydrogen at the Temperature of 350 °C by Means of Magnetic Permeability In Situ Measurement

The kinetics of phase transformations in the nitriding process α-Fe → γ’-Fe4N → ε-Fe3-2N of the pre-reduced iron ammonia synthesis catalyst was investigated under in situ conditions (atmospheric pressure, 350 °C) by measuring changes of mass, gas phase composition, and magnetic permeability in a differential tubular reactor. The iron nanocrystallite size distribution according to their specific active surface areas was measured, and it was found that the catalyst is bimodal as the sum of two Gaussian distributions, also differing in the value of the relative magnetic permeability. Relative magnetic permeability of small α-Fe crystals in relation to large crystals is higher by 0.02. In the area of α → γ’ transformation, the magnetic permeability dependencies change, proving the existence of two mechanisms of the α-Fe structure change in the α-Fe → γ’-Fe4N transformation. In the first area, a solution of α-Fe (N) is formed with a continuous and insignificant change of the crystal lattice parameters of the iron lattice. In the second area, there is a step, oscillatory change in the parameters of the iron crystal lattice in FexN (x = 0.15, 0.20, 0.25 mol/mol). In the range of γ’-Fe4N → ε-Fe3-2N transformation, a solution is formed, with nitrogen concentration varying from 0.25–0.45 mol/mol. During the final stage of the nitriding process, at a constant value of the relative magnetic permeability, only the concentration of nitrogen in the solution εr increases. The rate of the phenomenon studied is limited by a diffusion rate through the top layer of atoms on the surface of iron nanocrystallite. The estimated value of the nitrogen diffusion coefficient varied exponentially with the degree of nitriding. In the area of the solution, the diffusion coefficient is approximately constant and amounts to 5 nm2/s. In the area of oscillatory changes, the average diffusion coefficient changes in the range of 3–11 nm2/s, and is inversely proportional to the nitrogen content degree. The advantage of the research method proposed in this paper is the possibility of simultaneously recording, under reaction conditions, changes in the values of several process parameters necessary to describe the process. The research results obtained in this way can be used to develop such fields of knowledge as heterogeneous catalysis, materials engineering, sensorics, etc.