Materials Science Research Articles

Xiaoyan Tang.

"The most important factor in the choice of my current research topic was the urgent need to develop eco-friendly alternatives to traditional polymers, aiming to reduce environmental impact and promote sustainability in materials science… My favorite time of day is my journey home after work, a peaceful moment to reflect and unwind from the day's activities, while eagerly anticipating seeing my son…" Find out more about Xiaoyan Tang in her Introducing… Profile.

Selective nitrogen insertion into aryl alkanes

Molecular structure-editing through nitrogen insertion offers more efficient and ingenious pathways for the synthesis of nitrogen-containing compounds, which could benefit the development of synthetic chemistry, pharmaceutical research, and materials science. Substituted amines, especially nitrogen-containing alkyl heterocyclic compounds, are widely found in nature products and drugs. Generally, accessing these compounds requires multiple steps, which could result in low efficiency. In this work, a molecular editing strategy is used to realize the synthesis of nitrogen-containing compounds using aryl alkanes as starting materials. Using derivatives of O-tosylhydroxylamine as the nitrogen source, this method enables precise nitrogen insertion into the Csp2-Csp3 bond of aryl alkanes. Notably, further synthetic applications demonstrate that this method could be used to prepare bioactive molecules with good efficiency and modify the molecular skeleton of drugs. Furthermore, a plausible reaction mechanism involving the transformation of carbocation and imine intermediates has been proposed based on the results of control experiments.

Solving Advanced Task-Specific Problems in Measurement Sciences with Generative AI.

The Generative Pre-Trained Transformer known as ChatGPT-4 has undergone extensive pretraining on a diverse data set, enabling it to generate coherent and contextually relevant text based on the input it receives. This capability allows it to perform tasks from answering questions and has attracted significant interest in material sciences, synthetic chemistry, and drug discovery. In this work, we posed four advanced task-specific problems to ChatGPT, which were recently published in leading journals for topics in analytical chemistry, spectroscopy, bioimage super-resolution, and electrochemistry. ChatGPT-4 successfully implemented the four ideas after assigning the "persona" to the AI and posing targeted questions. We show two cases where "unguided" ChatGPT could complete the assignments with minimal human direction. The construction of a microwave spectrum from a free induction curve and super-resolution of bioimages was accomplished using this approach. Two other specific tasks, correcting a complex baseline with morphological operations of set theory and estimating the diffusion current, required additional input, e.g., equations and specific directions from the user. In each case, the MATLAB code was eventually generated by ChatGPT-4 even when the original authors did not provide any code themselves. We show that a validation test must be implemented to detect and correct mistakes made by ChatGPT-4, followed by feedback correction. These approaches will pave the way for open and transparent science and eliminate the black boxes in measurement science when it comes to advanced data processing.

Rational Strategies to Improve the Efficiency of 2D Perovskite Solar Cells.

In the quest for durable photovoltaic devices, 2D halide perovskites have emerged as a focus of extensive research. However, the reduced dimension in structure is accompanied by inferior optical-electrical properties, such as widened band gap, enhanced exciton binding energy, and obstructed charge transport. As a result, the efficiency of 2D perovskite solar cells (PSCs) lags significantly behind their 3D counterparts. To overcome these constraints, extensive investigations into materials and processing techniques are pursued rigorously to augment the efficiency of 2D PSCs. Herein, The cutting-edge delve into developments in 2D PSCs, with a focus on chemical and material engineering, as well as their structure and photovoltaic properties. The review starts with an introduction of the crystal structure, followed by the key evaluation criteria of 2D PSCs. Then, the strategies around solution chemical engineering, processing technique, and interface optimization, to simultaneously boost efficiency and stability are systematically discussed. Finally, the challenges and perspectives associated with 2D perovskites to provide insights into potential improvements in photovoltaic performance will be outlined.

Synthesis of Nanoflowers using Garcinia gummi-gutta Leaf Extract via Green Route for Enhanced Antifungal and Anti-cancerous Activities

Due to its envisaged relevance in nanomedicine and materials research, the bio-engineering of nanoparticles (NPs) is becoming progressively more promising. Compared to physical and chemical processes, green synthesis produces NPs that are less hazardous to the environment. The usage of phytochemicals in Garcinia gummi-gutta (L.) leaf extract (GGL) in the bio-reduction of GGL-Ag NPs with potential antifungal and anti-cancerous activities was the main focus of the current study. UV-vis spectrophotometry at 442 nm verified the synthesized GGL-Ag NPs. The average diameters of the synthesized GGL-Ag NPs were determined by scanning electron microscopy (SEM and zeta-sizer studies to be 166.69 nm and 148.2 nm, respectively. Energy dispersive X-ray spectroscopy (EDS) and X-ray diffraction (XRD) examinations of the GGL-Ag NPs confirmed the crystalline nature and the elemental constitution of the NPs. Additionally, the synthesized GGL-Ag NPs' FTIR spectra demonstrated the presence of Phyto components acting as capping agents. Zeta potential measurements (-26.2± 4.13 mV) authenticated the stability of the synthesized GGL-Ag NPs. Antimicrobial activity testing of the GGL-Ag NPs demonstrated considerable suppression against Candida tropicalis and Candida albicans at a dose of 100 µg/ml and 60 µg/ml. Additionally, the synthesized GGL-Ag NPs have demonstrated considerable cytotoxic effects on the Hep-G2 cell line. The current study results show that GGL- Ag NPs may be produced at a low cost and with minimal environmental impact for nanobiotechnology and biomedicine usage.

Photo-Clickable Triazine-Trione Thermosets as Promising 3D Scaffolds for Tissue Engineering Applications.

There is an overwhelming demand for new scaffolding materials for tissue engineering (TE) purposes. Polymeric scaffolds have been explored as TE materials; however, their high glass transition state (Tg) limits their applicability. In this study, a novel materials platform for fabricating TE scaffolds is proposed based on solvent-free two-component heterocyclic triazine-trione (TATO) formulations, which cure at room temperature via thiol-ene/yne photochemistry. Three ester-containing thermosets, TATO-1, TATO-2, and TATO-3, are used for the fabrication of TE scaffolds including rigid discs, elastic films, microporous sponges, and 3D printed objects. After 14 days' incubation the materials covered a wide range of properties, from the soft TATO-2 having a compression modulus of 19.3MPa and a Tg of 30.4°C to the hard TATO-3 having a compression modulus of 411MPa and a Tg of 62.5°C. All materials exhibit micro- and nano-surface morphologies suited for bone tissue engineering, and in vitro studies found them all to be cytocompatible, supporting fast cell proliferation while minimizing cell apoptosis and necrosis. Moreover, bone marrow-derived mesenchymal stem cells on the surface of the materials are successfully differentiated into osteoblasts, adipocytes, and neuronal cells, underlining the broad potential for the biofabrication of TATO materials for TE clinical applications.

Design of Co-Cured Multi-Component Thermosets with Enhanced Heat Resistance, Toughness, and Processability via a Machine Learning Approach.

Designing heat-resistant thermosets with excellent comprehensive performance has been a long-standing challenge. Co-curing of various high-performance thermosets is an effective strategy, however, the traditional trial-and-error experiments have long research cycles for discovering new materials. Herein, a two-step machine learning (ML) assisted approach is proposed to design heat-resistant co-cured resins composed of polyimide (PI) and silicon-containing arylacetylene (PSA), that is, poly(silicon-alkyne imide) (PSI). First, two ML prediction models are established to evaluate the processability of PIs and their compatibility with PSA. Then, another two ML models are developed to predict the thermal decomposition temperature and flexural strength of the co-cured PSI resins. The optimal molecular structures and compositions of PSI resins are high-throughput screened. The screened PSI resins are experimentally verified to exhibit enhanced heat resistance, toughness, and processability. The research framework established in this work can be generalized to the rational design of other advanced multi-component polymeric materials.

A holistic platform for accelerating sorbent-based carbon capture.

Reducing carbon dioxide (CO2) emissions urgently requires the large-scale deployment of carbon-capture technologies. These technologies must separate CO2 from various sources and deliver it to different sinks1,2. The quest for optimal solutions for specific source-sink pairs is a complex, multi-objective challenge involving multiple stakeholders and depends on social, economic and regional contexts. Currently, research follows a sequential approach: chemists focus on materials design3 and engineers on optimizing processes4,5, which are then operated at a scale that impacts the economy and the environment. Assessing these impacts, such as the greenhouse gas emissions over the plant's lifetime, is typically one of the final steps6. Here we introduce the PrISMa (Process-Informed design of tailor-made Sorbent Materials) platform, which integrates materials, process design, techno-economics and life-cycle assessment. We compare more than 60 case studies capturing CO2 from various sources in 5 global regions using different technologies. The platform simultaneously informs various stakeholders about the cost-effectiveness of technologies, process configurations and locations, reveals the molecular characteristics of the top-performing sorbents, and provides insights on environmental impacts, co-benefits and trade-offs. By uniting stakeholders at an early research stage, PrISMa accelerates carbon-capture technology development during this critical period as we aim for a net-zero world.

Rapid detection of rare events from in situ X-ray diffraction data using machine learning

High-energy X-ray diffraction methods can non-destructively map the 3D microstructure and associated attributes of metallic polycrystalline engineering materials in their bulk form. These methods are often combined with external stimuli such as thermo-mechanical loading to take snapshots of the evolving microstructure and attributes over time. However, the extreme data volumes and the high costs of traditional data acquisition and reduction approaches pose a barrier to quickly extracting actionable insights and improving the temporal resolution of these snapshots. This article presents a fully automated technique capable of rapidly detecting the onset of plasticity in high-energy X-ray microscopy data. The technique is computationally faster by at least 50 times than the traditional approaches and works for data sets that are up to nine times sparser than a full data set. This new technique leverages self-supervised image representation learning and clustering to transform massive data sets into compact, semantic-rich representations of visually salient characteristics (e.g. peak shapes). These characteristics can rapidly indicate anomalous events, such as changes in diffraction peak shapes. It is anticipated that this technique will provide just-in-time actionable information to drive smarter experiments that effectively deploy multi-modal X-ray diffraction methods spanning many decades of length scales.

Biomimetic Materials Research, from Interest-driven to Society-serving: An interview with Shu-Hong Yu

Over the past two decades, Shu-Hong Yu's team has been focusing on the field of biomimetic materials, withmimetic targets include shells, pearls, wood, bone, fish scale, bamboo joint, lotus root silk and others.

Mikä aiheuttaa ilmastonmuutoksen?

This article discusses the transformation of climate change science from scientific knowledge to Finnish upper secondary school geography curricula and textbooks from 1985 to 2023. Scientific knowledge transforms into teachable knowledge through the transformation process at the societal, institutional, and classroom levels. In our analysis, we apply the idea of powerful knowledge and use three levels of geographical powerful knowledge, including geographical knowledge, critical and conceptual knowledge, and propensity to imagine alternative futures. The research material consists of five framework curricula from 1985 to 2019 and a total of thirteen upper secondary school geography textbooks that are based on the curricula. Our findings suggest that climate science knowledge has transformed slowly into societal curricula. However, in textbooks, scientific knowledge has transformed more rapidly. According to our results, the transformation may not necessarily occur linearly, first at the societal level and finally in classrooms.

Assessment of Forest Suitability of Soils in the Dry Steppe Zone of the Volgograd Region

Background: Assessing the forest suitability of soils is one of the key areas of agroforestry science. Research in this direction makes it possible to characterize areas where tree and shrub vegetation does not grow under natural conditions. The research carried out makes it possible to assess the possibilities of afforestation in the area of interest; they contribute to the perception of landscape diversity in the context of the reclamation efficiency of the created systems of protective forest plantings, their productivity and durability. Identification of soil suitability for forests is closely related to the assessment of soil quality and fertility. The study of forest suitability of soils has a pronounced regional aspect. This article presents materials from cartographic studies of the dry steppe zone of the Volgograd region of the Russian Federation. The study region is characterized by a wide variety of soil cover. Dark chestnut, chestnut soils and light chestnut soils are common in this zone. The processes of erosion, salinizationand deflation make a great contribution to the diversity of soil complexes. Methods: In this work, the cartographic research method is the main one. Achieving the research goal, creating a cartographic model of the forest vegetation properties of the study area, was carried out in three stages. At the first stage, the contours of the soil map at a scale of 1:400000 were classified into forest suitability groups. During the second stage, based on the functionality of the QGIS software package, new soil contours were created. At the third stage, area characteristics were taken, share parameters were calculated and an analysis of changes in soil cover was carried out in natural and economic areas. The research materials presented in this article were obtained during the implementation of the state task of the research work of the FSC of Agroecology RAS. The research period is from 2021-08 to 2023-11. Result: The result of the research is the creation of a cartographic model of the forest suitability of soils in the dry steppe zone of the Volgograd region. Based on measuring the areas of soil contours for each of the 17 administrative districts, the ratio of groups of forest suitability of soils was established. The revealed value of the share indicator for the study area as a whole is as follows: soils I, forest suitability groups occupy 10.4% of the territory; II -9.3%; III - 68.3%; IV - 12%. The data obtained are necessary for planning agroforestry work in the study area.

Benign and Selective Amination of Lignins towards Aromatic Biobased Building Blocks with Primary Amines.

Lignin is a widely available second-generation biopolymer and the main potential source of renewable aromatic building blocks. Lignin-based polyamines offer great potential in applications based on chemical and materials sciences. However, common aminations techniques for lignin usually involve toxic chemicals and generate hindered and low reactivity amines. In this study, we developed two new, simple, and benign 2-step methodologies for the elaboration of lignin-based polyamines from different technical lignins (kraft, soda and organosolv) with a selectivity towards reactive primary amines. These methods involve grafting amide groups onto lignin followed by a hydrolysis step. Non-toxic heterocyclic compounds N-acetyl-2-oxazolidinone and 2-methyl-2-oxazoline were used as amidation agents. Hydrolysis was performed in acetone-water mixtures. Reactions were studied on model compounds and optimized on lignins. Aminated lignins were fully characterized and primary amines were quantified using quantitative 19F NMR. Our methods generated aminated lignins with low apparent molar masses and high solubility in water and solvents. Nitrogen contents of the products ranged between 2.0 and 3.5 mmol/g with reactive primary amines counts up to 1.7 mmol/g. These soluble and reactive lignin-based polyamines offer great potential as a replacement for fossil-based polyamines in e.g., the synthesis of aromatic polymer materials or as potential chelating, antibacterial agents.

Soft matter physics of the ground beneath our feet.

The soft part of the Earth's surface - the ground beneath our feet - constitutes the basis for life and natural resources, yet a general physical understanding of the ground is still lacking. In this critical time of climate change, cross-pollination of scientific approaches is urgently needed to better understand the behavior of our planet's surface. The major topics in current research in this area cross different disciplines, spanning geosciences, and various aspects of engineering, material sciences, physics, chemistry, and biology. Among these, soft matter physics has emerged as a fundamental nexus connecting and underpinning many research questions. This perspective article is a multi-voice effort to bring together different views and approaches, questions and insights, from researchers that work in this emerging area, the soft matter physics of the ground beneath our feet. In particular, we identify four major challenges concerned with the dynamics in and of the ground: (I) modeling from the grain scale, (II) near-criticality, (III) bridging scales, and (IV) life. For each challenge, we present a selection of topics by individual authors, providing specific context, recent advances, and open questions. Through this, we seek to provide an overview of the opportunities for the broad Soft Matter community to contribute to the fundamental understanding of the physics of the ground, strive towards a common language, and encourage new collaborations across the broad spectrum of scientists interested in the matter of the Earth's surface.

Electron Leaks in Biophotovoltaics: A Multi‐Disciplinary Perspective

AbstractBiophotovoltaics (BPV), which exploits the natural oxygenic photosystem for energy production, provides a sustainable solution to produce carbon neutral or negative energy from sunlight to meet the growing global energy demand. BPV integrates oxygenic photoautotrophic microorganisms in an electrochemical cell, and harvests the water‐splitting derived photosynthetic electrons to an electrical circuit. Here e. g. electricity or H2, etc, can be produced, thus directly coupling sunlight and water to energy. Despite of the rapid development in the past decade, the system efficiency of BPV still needs magnitude‐level improvement for practical applications. In this perspective paper, we aim to address the electron transfer pipeline in BPV starting from the water splitting by the living whole‐cell catalysts to external electron sinks (i. e. mediator/anode) and eventually to the cathode, from multidisciplinary aspects. We calculated the electron leaks along the electron transfer pipeline to different metabolic electron sinks, and prospectively predicted an untapped potential for extracellular electron transfer rate. BPV could potentially reach an energy efficiency that is two orders of magnitude higher than its current status. An interdisciplinary research approach, that should combine systems and synthetic biology, bioprocess engineering and material science, among others, is proposed to broach the upper boundary of BPV technology.

Characteristic features of strong correlation: lessons from a 3-fermionone-dimensional harmonic trap

Abstract Many quantum phenomena responsible for key applications in material science and quantum
chemistry arise in the strongly correlated regime. This is at the same time, a costly regime for
computer simulations. In the limit of strong correlation analytic solutions exist, but as we move
away from this limit numerical simulation are needed, and accurate quantum solutions do not scale
well with the number of interacting particles. In this work we propose to use few-particle harmonic
traps in combination with twisted light as a quantum emulator to investigate the transition into a
strongly-correlated regime. Using both analytic derivations and numerical simulations we generalize
previous findings on 2 Coulomb interacting fermions trapped in a one-dimensional harmonic trap
to the case of 3 fermions. The 4 signatures of strong correlation we have identified in the one-
dimensional harmonic trap are: i) the ground state density is highly localized around N equilibrium
positions, where N is the number of particles, ii) the symmetric and antisymmetric ground state
wavefunctions become degenerate, iii) the von Neumann entropy grows, iv) the energy spectrum is
fully characterized by N normal modes or less. Our findings describe the low-energy behavior of
electrons in quantum wires and ions in Paul traps. Similar features have also been reported for cold
atoms in optical lattices.

Design and Fabrication of Nano‐Particles with Customized Properties using Self‐Assembly of Block‐Copolymers

AbstractFunctional nanoparticles (NPs) have gained significant attention as promising applications in various fields, including sensor, smart coating, drug delivery, and more. Here, a novel mechanism assisted by machine‐learning workflow is proposed to accurately predict phase diagram of NPs, which elegantly achieves tunability of shapes and internal structures of NPs using self‐assembly of block‐copolymers (BCP). Unlike most of previous studies, onion‐like and mesoporous NPs in neutral environment and hamburger‐like NPs in selective environment are obtained. Such novel phenomena are obtained only by tailoring the topology of a miktoarm star BCP chain architecture without the need for any further treatment. Moreover, it is demonstrated that the BCP chain architecture can be used as a new strategy for tuning the lamellar asymmetry of NPs. It is shown that the asymmetry between A and B lamellae in striped ellipsoidal and onion‐like particles increases as the volume fraction of the A‐block increases, beyond the level reached by linear BCPs. In addition, an extended region of onion‐like structure is found in the phase diagram of A‐selective environment, as well as the emergence of an inverse onion‐like structure in the B‐selective one. The findings provide a valuable insight into the design and fabrication of nanoscale materials with customized properties, opening up new possibilities for advanced applications in sensing, materials science, and beyond.

C─H Activation Enables the Construction of New Bis-Polyaryl Phenylpyridine Ruthenium Complexes: Conjugation and Rigidity Synergistic Effect for Advanced Electrochemiluminescence.

The access to bench-stable organometallic compounds unfolds new chemical space for medicinal and material sciences. In particular, stable organoruthenium compounds with constitutional and stereoisomeric forms for subtle regulation of electrochemiluminescence are intriguing and challenging. Here, coordination of polycyclic aromatic hydrocarbons on (2-phenylpyridine)2(CO)2Ru complex allows access to bis-polyaryl phenylpyridine (BPP) Ruthenium complex through C─H activation strategy and coupling reactions for installation of the functionalities with steric and electronic purposes. The photoluminescence and electrochemiluminescence of BPP Ru complexes are affected by the actual polycyclic aromatic hydrocarbons inherent properties. The anthracene derivatized BPP Ru complex (BPP-Ant) shows the best ECL performance and reveals an enormous ECL quantum efficiency of 1.6-fold higher than the golden standard Ru(bpy)3 2+. The unprecedentedly high efficiency is due to the best compromise between the structural conjugation and molecular rigidity from BPP-Ant providing a providential energy gap that facilitated the feasibility of electron transfer and favored the radiative energy release by experimentally and DFT calculations. Moreover, PL and spooling ECL spectroscopies are used to track and link multiple emission peaks of BPP-Ant at 445, 645, and 845nm to different emissive species. These discoveries will add a new member to the efficient ECL ruthenium complex family and bring more potentials.

Preparation and characterization of poly(butylene adipate‐co‐terephthalate) composites reinforced with acetylated cellulose nanocrystals and nanofibers for enhanced properties

AbstractNanocellulose‐reinforced composites hold great promise for outperforming the original polymer matrix by offering exceptional properties, including outstanding barrier characteristics achieved through the establishment of convoluted pathways for the diffusion of water vapor and gases, as well as superior mechanical and thermal properties. Nevertheless, a significant challenge when employing nanocelluloses as reinforcements in polymers arises from their limited compatibility with the polymer matrix, primarily attributed to the abundance of surface hydroxyl groups.To address this limitation, this study focuses on the acetylation modification of cellulose nanocrystals (CNC) and nanofibers (CNF) to enhance their compatibility with the polymer matrix. Poly(butylene adipate‐co‐terephthalate) (PBAT) nanocomposites were developed by incorporating 1 wt% of both untreated and acetylated cellulose. The process involved the molten state mixing of these components using a twin‐screw mini extruder, conducted at 160°C for 7 min. The efficacy of the acetylation process was verified through Fourier transform infrared spectroscopy (FTIR). Scanning electron microscopy (SEM) analysis confirmed the favorable interaction and dispersion of nanocelluloses within the polymer matrix. Importantly, introducing these fillers did not compromise thermal stability but notably enhanced the hydrophobic characteristics of the samples, as confirmed by contact angle measurements. Dynamic mechanical analyses further demonstrated the compatibility and effective interaction between the polymer and fillers. This research uniquely provides a comparative analysis of the effects of acetylated CNC and CNF within a PBAT matrix, unveiling distinct interactions and performance enhancements. Each type of nanocellulose exhibits its own characteristic ways of bonding and dispersing, leading to varying performance improvements for the material. This comparison elucidates the nuanced roles that these nanocelluloses play in reinforcing composites, offering insights into optimizing their contribution to polymer matrices. By demonstrating the differential impact of CNC and CNF post‐acetylation, our study contributes significantly to the field of polymer science, guiding future applications of nanocellulose‐reinforced materials in advanced engineering and sustainability efforts.

Ultra-stable, lightweight and superelastic waste flax-based aerogel for multifunctional applications

Multifunctional aerogels constructed from natural waste biomass have attracted great attention in the fields of green energy harvesting, flexible wearable sensing and natural environment restoration. However, the complex and polluted extraction of natural materials and the poor mechanical property have seriously hindered the development of natural material-based aerogels. Hence, a novel aerogel with capabilities of high-elasticity, stabilized constructions and weightlessness was prepared via waste flax staple fibers (simply physically disrupting) and multi-walled carbon tubes. Due to the assistance of cross-linking agent and carbon tubes, the aerogel was endowed with multiple properties including high photothermal conversion (97.2 %), superstability at the wide range of 0–29 KPa and outstanding compression resilience at different strains (up to 60 % and 100 cycles). Consequently, it is promising that the fabricated aerogel may be as a piezoresistive sensor to monitor different locations of the body for continuous detection of motor behavior. Further, the sample was also utilized as an evaporator with excellent water evaporation effect (1.93 kg·m−2·h−1) under 1 sun and to efficiently purify various types of wastewater for obtaining pure water. This multi-purpose aerogels prepared in this work display admirable potential for efficient environmental purification, advanced smart materials and green energy harvesting.