jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Clément Gédéon | Natalia Del Rio | Francesco Furlan | Andrea Taddeucci | Nicolas Vanthuyne | Vasilis G. Gregoriou | Matthew J. Fuchter | Giuliano Siligardi | Nicola Gasparini | Jeanne Crassous | Christos L. Chochos
Source: Advanced Materials (article, 2024-02-26)
Field: Chemistry — Organic Chemistry

Rational Design of New Conjugated Polymers with Main Chain Chirality for Efficient Optoelectronic Devices: Carbo[6]Helicene and Indacenodithiophene Copolymers as Model Compounds The unique properties of conjugated polymers (CPs) in various optoelectronic applications are mainly attributed to their different self-assembly processes and superstructures. Various methods are utilized to tune and control CP structure and properties with less attention paid to the use of chirality. CPs with main chain chirality are rare and their microscopic and macroscopic properties are still unknown. In this work, the first experimental results are provided along these lines by synthesizing a series of racemic and enantiopure CPs containing statistical and alternating carbo[6]helicene and indacenodithiophene moieties and evaluating their microscopic (optical, energy levels) and macroscopic properties (hole mobilities, photovoltaic performance). It is demonstrated that a small statistical insertion of either the racemic or enantiopure helicene into the polymer backbone finely tunes the microscopic and macroscopic properties as a function of the statistical content. The microscopic properties of the enantiopure versus the racemic polymers with the same helicene loading remain similar. On the contrary, the macroscopic properties, and more interestingly those between the two enantiomeric forms, are altered as a function of the statistical content. Once incorporated into a solar cell device, these chiral CPs display better performance in their enantiopure versus racemic forms. Helicene ; Materials science ; Conjugated system ; Chirality (physics) ; Copolymer ; Polymer ; Rational design ; Nanotechnology ; Optoelectronics ; Organic chemistry ; Molecule ; Composite material ; Chemistry Synthesis and Properties of Aromatic Compounds ; Organic Electronics and Photovoltaics ; Axial and Atropisomeric Chirality Synthesis
Authors: An Thuy Ngo | Yasushi Mori | Long Thanh Bui
Source: Environmental Technology & Innovation (article, 2024-04-30)
Field: Materials Science — Biomaterials

Effects of cellulose nanofibers on soil water retention and aggregate stability Innovative solutions that address global challenges such as water scarcity and soil erosion are critical for maintaining sustainable agriculture. Due to their water-absorbing and soil-binding properties, cellulose nanofibers (CNF) can be applied to soil to enhance soil water retention and aggregate stability. In this study, we analyzed the effects of the drying temperature, dosage, irrigation water quality, and soil type on the efficacy of CNFs. Our results revealed that CNF dried at 5°C is more effective at absorbing water than others, and adding 1% CNF enhanced soil water content up to 98%. The CNF samples absorbed water due to their hydrophilic molecular groups and morphological structure, as confirmed by Fourier-transform infrared spectroscopy and scanning electron microscopy. CNF addition increased the soil volumetric water content and prolonged water retention by 22 days in the paddy soil samples, highlighting its potential for drought-prone areas. Furthermore, irrigation water quality, such as pH and cation values, influenced the interactions between CNF and water molecules, suggesting adjustments to the water retention curve. In its hydrated state, CNF promotes colloid flocculation and binds to soil particles, thereby strengthening the bonds crucial for aggregate formation and stability. CNF enhanced macro-aggregate formation by up to 48% and 59% in the masa and paddy soil samples, respectively. Our study emphasizes the potential of CNF for water conservation, soil health, and overall agricultural sustainability. Water retention ; Cellulose ; Soil water ; Soil structure ; Irrigation ; Chemical engineering ; Environmental science ; Materials science ; Chemistry ; Soil science ; Agronomy ; Organic chemistry Advanced Cellulose Research Studies
Authors: Alex S. Anderton | Oliver J. Knowles | James A. Rossi‐Ashton | David J. Procter
Source: ACS Catalysis (article, 2024-01-31)
Field: Chemistry — Organic Chemistry

Flavin-Mediated Photocatalysis Provides a General Platform for Sulfide C–H Functionalization Functionalized sulfides are important in many areas of science, ranging from chemical biology through drug discovery to organic materials chemistry. Sulfides bearing pendant reactive groups in the α-position are particularly useful; however, methods for the selective valorization of simple sulfides or the late-stage functionalization of complex sulfides by the convenient addition of valuable functionality are underexplored. Here we exemplify a general reaction platform for sulfide functionalization by showcasing three modes of α-sulfur C-H functionalization; cyanation, alkenylation, and alkynylation. Using inexpensive and commercially available riboflavin tetraacetate and visible light, decoration of both feedstock and complex sulfides proceeds in a good yield and with high selectivity. Methionine-containing peptides can also be selectively functionalized and a tolerance screen using amino-acid dopants suggests that the platform is compatible with most amino-acid side chains and thus is a potential tool for bioconjugation. Flavin group ; Surface modification ; Photocatalysis ; Sulfide ; Catalysis ; Chemistry ; Combinatorial chemistry ; Photochemistry ; Organic chemistry ; Enzyme ; Physical chemistry Sulfur-Based Synthesis Techniques ; Synthesis and Catalytic Reactions ; Radical Photochemical Reactions
Authors: Umme Asma | Maria Letizia Bertotti | Simone Zamai | Marcellus Arnold | Riccardo Amorati | Matteo Scampicchio
Source: Antioxidants (article, 2024-02-09)
Field: Chemistry — Organic Chemistry

A Kinetic Approach to Oxygen Radical Absorbance Capacity (ORAC): Restoring Order to the Antioxidant Activity of Hydroxycinnamic Acids and Fruit Juices This study introduces a kinetic model that significantly improves the interpretation of the oxygen radical absorbance capacity (ORAC) assay. Our model accurately simulates and fits the bleaching kinetics of fluorescein in the presence of various antioxidants, achieving high correlation values (R<sup>2</sup> > 0.99) with the experimental data. The fit to the experimental data is achieved by optimizing two rate constants, <i>k</i><sub>5</sub> and <i>k</i><sub>6</sub>. The <i>k</i><sub>5</sub> value reflects the reactivity of antioxidants toward scavenging peroxyl radicals, whereas <i>k</i><sub>6</sub> measures the ability of antioxidants to regenerate oxidized fluorescein. These parameters (1) allow the detailed classification of cinnamic acids based on their structure-activity relationships, (2) provide insights into the interaction of alkoxyl radicals with fluorescein, and (3) account for the regeneration of fluorescein radicals by antioxidants. The application of the model to different antioxidants and fruit extracts reveals significant deviations from the results of traditional ORAC tests based on the area under the curve (AUC) approach. For example, lemon juice, rich in 'fast' antioxidants such as ascorbic acid, shows a high <i>k</i><sub>5</sub> value, in contrast to its low AUC values. This finding underscores the limitations of the AUC approach and highlights the advantages of our kinetic model in understanding antioxidative dynamics in food systems. This study presents a comprehensive, quantitative, mechanism-oriented approach to assessing antioxidant reactivity, demonstrating a significant improvement in ORAC assay applications. Oxygen radical absorbance capacity ; Chemistry ; Radical ; Antioxidant ; Ascorbic acid ; Absorbance ; Kinetics ; Reactivity (psychology) ; Antioxidant capacity ; Organic chemistry ; Chromatography ; Food science Free Radicals and Antioxidants ; Phytochemicals and Antioxidant Activities ; Antioxidant Activity and Oxidative Stress
Authors: Linfeng Bao | Jiahao Liu | Tingyong Mao | Zhao Linbo | Desheng Wang | Yunlong Zhai
Source: Frontiers in Plant Science (review, 2024-08-27)
Field: Materials Science — Materials Chemistry

Nanobiotechnology-mediated regulation of reactive oxygen species homeostasis under heat and drought stress in plants Global warming causes heat and drought stress in plants, which affects crop production. In addition to osmotic stress and protein inactivation, reactive oxygen species (ROS) overaccumulation under heat and drought stress is a secondary stress that further impairs plant performance. Chloroplasts, mitochondria, peroxisomes, and apoplasts are the main ROS generation sites in heat- and drought-stressed plants. In this review, we summarize ROS generation and scavenging in heat- and drought-stressed plants and highlight the potential applications of plant nanobiotechnology for enhancing plant tolerance to these stresses. Reactive oxygen species ; Heat stress ; Chloroplast ; Peroxisome ; Biology ; Drought tolerance ; Botany ; Cell biology ; Biochemistry ; Gene Nanoparticles: synthesis and applications ; Plant Stress Responses and Tolerance ; Advanced Nanomaterials in Catalysis
Authors: Binglong Zheng | Ying Lin | Haibo Yang | Hongmei Jing | Nan Hu | Yifei Wang | Fang‐Zhou Yao | Minquan Wang | Qibin Yuan
Source: Advanced Science (article, 2024-10-30)
Field: Materials Science — Materials Chemistry

A Broad‐High Temperature Ceramic Capacitor with Local Polymorphic Heterogeneous Structures Crafting high-performance dielectrics tailored for pulsed power capacitors, in response to the escalating demands of practical applications, presents a formidable challenge. Herein, this work introduces a novel lineup of lead-free ceramics with local polymorphic heterogeneous structures, defined by the formula (1-x)[0.92BaTiO<sub>3</sub>-0.08Sr(Mg<sub>1/2</sub>Ti<sub>3/4</sub>)O<sub>3</sub>]-x(Na<sub>0.5</sub>Bi<sub>0.5</sub>)TiO<sub>3</sub> (BT-SMT-xNBT). This innovative multi-scale synergistic strategy, spanning from the atomic to grain scale, yields materials with a giant recoverable energy density (W<sub>rec</sub>) of 10.1 J·cm<sup>-3</sup> and an impressive energy efficiency (η) of 95.0%. The integration of linear end elements SMT can significantly mitigate the polarization hysteresis while concurrently boosting the breakdown strength, thus enhancing overall energy efficiency. Furthermore, the inclusion of NBT with high polarization serves to amplify domain size, thereby reinforcing the electric field-induced polarization. This addition also stimulates the creation of polymorphic heterostructures, where tetragonal and rhombohedral nanodomains coexist, as validated by aberration-corrected transmission electron microscopy. Notably, the BT-SMT-0.2NBT ceramics have demonstrated outstanding high-temperature energy storage capabilities, with a W<sub>rec</sub> of 7.2 J·cm<sup>-3</sup> and an η of 92.2% at 150 °C, along with remarkable broad-temperature stability (ΔW<sub>rec</sub>, Δη ≤ 4.0%, ≈20-150 °C). These achievements in this work propel the field toward more practical and durable solutions of energy storage dielectrics. Materials science ; Capacitor ; Dielectric ; Ceramic ; Tetragonal crystal system ; Polarization (electrochemistry) ; Engineering physics ; Energy storage ; Optoelectronics ; Nanotechnology ; Voltage ; Composite material ; Electrical engineering ; Crystallography ; Power (physics) ; Physics ; Thermodynamics ; Chemistry ; Crystal structure Ferroelectric and Piezoelectric Materials ; Microwave Dielectric Ceramics Synthesis ; Dielectric properties of ceramics
Authors: Sumaia Jahan Mishu | Muhammad Asad Rahman | Nipa Dhar
Source: Heliyon (article, 2024-02-28)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Highly sensitive refractive index sensing with a dual-band optically transparent ITO-based perfect metamaterial absorber for biomedical applications In this paper, a dual-band optically transparent square-shaped perfect metamaterial absorber operating in the frequency range from 2 to 4 terahertz (THz) is proposed. The structure consists of an indium tin oxide (ITO)-based split ring resonator (SRR) structure with additional splits and rectangular inner strips to form the top layer over the lead glass substrate. Perfect absorption is attained in the frequencies of 2.089 and 3.892 THz with absorbances of 99.99% and 99.98% in TE polarization mode, respectively. Perfect absorption is also achieved in TM polarization mode at 2.23 THz. Broadband absorption is found in TM polarization mode with full width half maximum (FWHM) of 1.1742. The proposed structure has one polarization-insensitive band in TE polarization mode. Absorbance is greater than 80% and 90% in the successive absorption peaks even at 60° and 75° of incidence, respectively. The resonance frequency is sensitive to the refractive index of the medium. As a result, the proposed metamaterial structure may be implemented as a refractive index (RI) sensor with a high sensitivity of 1109 GHz/RIU and 1954 GHz/RIU in both absorption bands for a refractive index range of 1.34 to 1.40. It's interesting to note that the refractive index of most biological samples ranges from 1.3 to 1.39. The figure of merit (FOM) of the proposed sensor can reach as high as 10 and 14 for the 1st and 2nd frequency bands. As a result, the proposed sensor has a high sensitivity and can be employed in medical applications. Potential applications of the proposed absorber include imaging, biomedical sensing, etc. Metamaterial ; Multi-band device ; Refractive index ; Optoelectronics ; Materials science ; Optics ; Metamaterial absorber ; Dual (grammatical number) ; High-refractive-index polymer ; Tunable metamaterials ; Physics ; Computer science ; Telecommunications Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Plasmonic and Surface Plasmon Research
Authors: Zhuozhi Lai | Yuqing Ai | Weipeng Xian | Qing Guo | Qingwei Meng | Shijie Yin | Sai Wang | Li Zhang | Yubing Xiong | Banglin Chen | Qi Sun
Source: Advanced Functional Materials (article, 2024-08-09)
Field: Materials Science — Materials Chemistry

Covalent–Organic‐Framework Membrane with Aligned Dipole Moieties for Biomimetic Regulable Ion Transport Abstract Biological ion channels are renowned for their exceptional ion transport selectivity and adaptability to environmental changes, posing a significant challenge for synthetic mimicry. Herein, an innovative covalent–organic‐framework membrane featuring aligned benzothiadiazole units within its oriented 1D nanochannels is reported. These densely arrayed dipolar benzothiadiazole units enhance selective ion adsorption and facilitate membrane charge regulation. Consequently, the membrane can dynamically adjust its permselectivity toward ions, transitioning seamlessly between cation‐selective, ambipolar, and anion‐selective states. This versatility affects both the type of ions transported and the transport efficiency, supporting reversible and controlled membrane operation, as illustrated by the capacity to regulate the magnitude and direction of osmotic power. When interacting with multivalent anions, highly negatively charged channels of the membrane exhibit outstanding cation permselectivity and conductivity. Specifically, upon exposure to PO 4 3− ions, the membrane achieves a remarkable osmotic power of 155 W m −2 and an energy conversion efficiency of 46.1% under salinity gradients of 0.5 and 0.01 m NaCl. Notably, introducing multivalent cations can reverse the polarity of the membrane. This work underscores the potential of exploiting ion‐dipolar interactions for the development of adaptive, ion‐selective membranes with promising applications in electrochemical sensing, energy conversion, and more. Materials science ; Covalent bond ; Membrane ; Nanotechnology ; Dipole ; Ion ; Chemical physics ; Organic chemistry ; Chemistry ; Biochemistry Covalent Organic Framework Applications ; Metal-Organic Frameworks: Synthesis and Applications ; Fuel Cells and Related Materials
Authors: Mojan Omidvar | Hangfeng Zhang | Achintha Ihalage | Theo Saunders | Henry Giddens | Derek Michael Forrester | Sajad Haq | Yang Hao
Source: Nature Communications (article, 2024-08-02)
Field: Materials Science — Materials Chemistry

Accelerated discovery of perovskite solid solutions through automated materials synthesis and characterization Accelerating perovskite solid solution discovery and sustainable synthesis is crucial for addressing challenges in wireless communication and biosensors. However, the vast array of chemical compositions and their dependence on factors such as crystal structure, and sintering temperature require time-consuming manual processes. To overcome these constraints, we introduce an automated materials discovery approach encompassing machine learning (ML) assisted material screening, robotic synthesis, and high-throughput characterization. Our proposed platform for rapid sintering and dielectric analysis streamlines the characterization of perovskites and the discovery of disordered materials. The setup has been successfully validated, demonstrating processing materials within minutes, in stark contrast to conventional procedures that can take hours or days. Following setup validation with established samples, we showcase synthesizing single-phase solid solutions within the barium family, such as (Ba<sub>x</sub>Sr<sub>1-x</sub>)CeO<sub>3</sub>, identified through ML-guided chemistry. Characterization (materials science) ; Perovskite (structure) ; Materials science ; Sintering ; Nanotechnology ; Computer science ; Throughput ; Dielectric ; Wireless ; Chemical engineering ; Optoelectronics ; Telecommunications ; Engineering ; Metallurgy Machine Learning in Materials Science ; Electronic and Structural Properties of Oxides ; X-ray Diffraction in Crystallography
Authors: Karen Ghazaryan | Shreni Agrawal | Gohar Margaryan | Anna Harutyunyan | Priyadarshani Rajput | Hasmik Movsesyan | Vishnu D. Rajput | Rupesh Kumar Singh | Tatiana Minkina | Mohamed S. Elshikh | Mona S. Alwahibi | Αθανάσιος Αλεξίου | Marios Papadakis | João Ricardo Sousa | Abhishek Singh
Source: Discover Sustainability (article, 2024-12-02)
Field: Materials Science — Materials Chemistry

Soil pollution: an agricultural and environmental problem with nanotechnological remediation opportunities and challenges Abstract Nanotechnology has emerged as a promising frontier in the realm of environmental remediation, offering unprecedented precision and efficacy in addressing soil contamination and land degradation. This review paper has performed comprehensive survey of nanotechnological approaches for soil remediation and land restoration, encompassing a diverse array of nanomaterial (NM)-based strategies tailored to mitigate the impacts of various contaminants on terrestrial ecosystems. Furthermore, this review critically examines the ecological implications, regulatory considerations, and ethical dimensions associated with the deployment of engineered nanoparticles (NPs) in environmental remediation efforts. By providing a holistic understanding of the opportunities and challenges inherent in the integration of nanotechnology with soil remediation practices, this review aims to inform policymakers, researchers, and practitioners alike, fostering informed decision-making and catalyzing sustainable approaches towards land stewardship and environmental conservation. Environmental remediation ; Pollution ; Environmental science ; Soil remediation ; Agriculture ; Environmental planning ; Environmental pollution ; Environmental protection ; Soil contamination ; Environmental resource management ; Soil science ; Soil water ; Geography ; Contamination ; Ecology Nanoparticles: synthesis and applications ; Environmental remediation with nanomaterials ; Electrokinetic Soil Remediation Techniques
Authors: Sergei V. Kalinin | Yongtao Liu | Arpan Biswas | Gerd Duscher | Utkarsh Pratiush | Kevin M. Roccapriore | Maxim Ziatdinov | Rama K. Vasudevan
Source: Microscopy Today (article, 2024-01-01)
Field: Materials Science — Materials Chemistry

Human-in-the-Loop: The Future of Machine Learning in Automated Electron Microscopy Abstract Machine learning (ML) methods are progressively gaining acceptance in the electron microscopy community for de-noising, semantic segmentation, and dimensionality reduction of data post-acquisition. The introduction of the application programming interfaces (APIs) by major instrument manufacturers now allows the deployment of ML workflows in microscopes, not only for data analytics but also for real-time decision-making and feedback for microscope operation. However, the number of use cases for real-time ML remains remarkably small. Here, we discuss some considerations in designing ML-based active experiments and pose that the likely strategy for the next several years will be human-in-the-loop automated experiments (hAE). In this paradigm, the ML learning agent directly controls beam position and image and spectroscopy acquisition functions, and a human operator monitors experiment progression in real and feature space of the system and tunes the policies of the ML agent to steer the experiment toward specific objectives. Electron microscope ; Loop (graph theory) ; Materials science ; Microscopy ; Nanotechnology ; Computer science ; Artificial intelligence ; Physics ; Optics ; Mathematics ; Combinatorics Machine Learning in Materials Science ; Electron and X-Ray Spectroscopy Techniques ; Advanced Electron Microscopy Techniques and Applications
Authors: Martin Müller | Marie Stiefel | Björn-Ivo Bachmann | Dominik Britz | Frank Mücklich
Source: Metals (article, 2024-05-07)
Field: Materials Science — Materials Chemistry

Overview: Machine Learning for Segmentation and Classification of Complex Steel Microstructures The foundation of materials science and engineering is the establishment of process–microstructure–property links, which in turn form the basis for materials and process development and optimization. At the heart of this is the characterization and quantification of the material’s microstructure. To date, microstructure quantification has traditionally involved a human deciding what to measure and included labor-intensive manual evaluation. Recent advancements in artificial intelligence (AI) and machine learning (ML) offer exciting new approaches to microstructural quantification, especially classification and semantic segmentation. This promises many benefits, most notably objective, reproducible, and automated analysis, but also quantification of complex microstructures that has not been possible with prior approaches. This review provides an overview of ML applications for microstructure analysis, using complex steel microstructures as examples. Special emphasis is placed on the quantity, quality, and variance of training data, as well as where the ground truth needed for ML comes from, which is usually not sufficiently discussed in the literature. In this context, correlative microscopy plays a key role, as it enables a comprehensive and scale-bridging characterization of complex microstructures, which is necessary to provide an objective and well-founded ground truth and ultimately to implement ML-based approaches. Computer science ; Artificial intelligence ; Context (archaeology) ; Characterization (materials science) ; Microstructure ; Process (computing) ; Ground truth ; Machine learning ; Segmentation ; Materials science ; Nanotechnology ; Geology Machine Learning in Materials Science ; Hydrogen embrittlement and corrosion behaviors in metals ; Corrosion Behavior and Inhibition