jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Shiqian Wang | Ziye Zhang | Xinyao Zhao | Xinqing Xiao
Source: Discover Food (article, 2024-12-19)
Field: Chemistry — Analytical Chemistry

Electrical impedance spectroscopy for non-destructive meat freshness assessment The quality of meat is inherently linked to the time of its departure from the processing facility, the conditions of transportation, and the methods of storage, all of which directly affect the meat's integrity. Rapid, non-destructive, and precise evaluation of meat quality has thus emerged as a significant area of interest in recent years. Electrical impedance spectroscopy (EIS), recognized for its high reproducibility, user-friendly nature, non-polluting properties, measurement stability, and controllable error rates, stands out as a cutting-edge, non-destructive technique for quality assessment in today's landscape of equipment, applications, and data analysis methodologies. This paper provides a comprehensive review of the utilization of EIS-based non-destructive sensors for gauging the internal quality of meat, detailing the modalities of measurement and predictive modeling techniques. A critical discourse on the merits and demerits of various biosensors is presented, alongside an examination of the practical applicability of the EIS measurement approach. The paper encapsulates the commonly employed methods for the selection and processing of electrical impedance sensor data, including preprocessing, feature selection, calibration, and validation. Ultimately, the paper posits that the evolution from costly electrochemical devices traditionally used for impedance data collection to more economical, impedance-based devices for estimating meat freshness represents an avenue ripe for future exploration. Dielectric spectroscopy ; Electrical impedance ; Spectroscopy ; Materials science ; Environmental science ; Analytical Chemistry (journal) ; Electrical engineering ; Engineering ; Chemistry ; Environmental chemistry ; Physics Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Fault Detection and Control Systems
Authors: Olfa Ouled Ltaief | Ilham Ben Amor | Hadia Hemmami | Wiem Hamza | Soumeia Zeghoud | Asma Ben Amor | Mourad Benzina | Ali Alnazza Alhamad
Source: Annals of Medicine and Surgery (review, 2024-06-15)
Field: Materials Science — Biomaterials

Recent developments in cancer diagnosis and treatment using nanotechnology The article provides an insightful overview of the pivotal role of nanotechnology in revolutionizing cancer diagnosis and treatment. It discusses the critical importance of nanoparticles in enhancing the accuracy of cancer detection through improved imaging contrast agents and the synthesis of various nanomaterials designed for oncology applications. The review broadly classifies nanoparticles used in therapeutics, including metallic, magnetic, polymeric, and many other types, with an emphasis on their functions in drug delivery systems for targeted cancer therapy. It details targeting mechanisms, including passive and intentional targeting, to maximize treatment efficacy while minimizing side effects. Furthermore, the article addresses the clinical applications of nanomaterials in cancer treatment, highlights prospects, and addresses the challenges of integrating nanotechnology into cancer treatment. Medicine ; Nanotechnology ; Cancer therapy ; Cancer ; Applications of nanotechnology ; Cancer treatment ; Drug delivery ; Medical physics ; Internal medicine ; Materials science Nanoparticle-Based Drug Delivery ; Nanoplatforms for cancer theranostics ; Graphene and Nanomaterials Applications
Authors: Anshuman Goswami | Siddarth H. Krishna | Rajamani Gounder | William F. Schneider
Source: ACS Catalysis (article, 2024-05-14)
Field: Materials Science — Materials Chemistry

Kinetic Monte Carlo Analysis Reveals Non-mean-field Active Site Dynamics in Cu–Zeolite-Catalyzed NO<sub><i>x</i></sub> Reduction Copper-exchanged chabazite (Cu-CHA) zeolites are the preferred catalysts for the selective catalytic reduction of NO <sub><i>x</i></sub> with NH<sub>3</sub>. The low temperature (473 K) SCR mechanism proceeds through a redox cycle between mobile and ammonia-solvated Cu(I) and Cu(II) complexes, as demonstrated by multiple experimental and computational investigations. The oxidation step requires two Cu(I) to migrate into the same <i>cha</i> cage to activate O<sub>2</sub> and form a binuclear Cu(II)-di-oxo complex. Prior steady state and transient kinetic experiments find that the apparent rate constants for oxidation (per Cu ion) are sensitive to catalyst composition and follow nonmean-field kinetics. We develop a nonmean-field kinetic model for NO <sub><i>x</i></sub> SCR that incorporates a composition-dependent Cu(I) volumetric footprint centered at anionic [AlO<sub>4</sub>]<sup>-</sup> tetrahedral sites on the CHA lattice. We use Bayesian optimization to parameterize a kinetic Monte Carlo model against available experimental composition-dependent SCR rates and <i>in situ</i> Cu(II) fractions. We find that both rates and Cu(II) fractions of a majority of catalyst compositions can be captured by single oxidation and reduction rate constants combined with a composition-dependent Cu(I) cation footprint, highlighting the contributions of both Cu and Al densities to steady-state SCR performance of Cu-CHA. The work illustrates a pathway for extracting robust molecular insights from the kinetics of a dynamic catalytic system. Catalysis ; Monte Carlo method ; Zeolite ; Reduction (mathematics) ; Active site ; Kinetic Monte Carlo ; Kinetic energy ; Chemistry ; Materials science ; Physical chemistry ; Physics ; Mathematics ; Organic chemistry ; Statistics Catalytic Processes in Materials Science ; Catalysis and Oxidation Reactions ; Gas Sensing Nanomaterials and Sensors
Authors: Jack L. Eatson | Susann Bauernfeind | Benjamin Midtvedt | Antonio Ciarlo | Johannes Menath | Giuseppe Pesce | Andrew B. Schofield | Giovanni Volpe | Paul S. Clegg | Nicolas Vogel | D. Martin A. Buzza | Marcel Rey
Source: Journal of Colloid and Interface Science (article, 2024-12-21)
Field: Materials Science — Materials Chemistry

Self-assembly of defined core–shell ellipsoidal particles at liquid interfaces Pure ellipsoidal particles without a shell consistently form side-to-side "chain-like" assemblies, regardless of aspect ratio. In contrast, core-shell ellipsoidal particles exhibit a transition from tip-to-tip "flower-like" arrangements to side-to-side structures as aspect ratio increases. The critical aspect ratio for this transition shifts with increasing shell thickness. Our results highlight how we can engineer the self-assembly of anisotropic particles at liquid interfaces by tuning their physicochemical properties such as aspect ratio and shell thickness, allowing the deterministic realization of distinct structural configurations. Shell (structure) ; Ellipsoid ; Core (optical fiber) ; Materials science ; Nanotechnology ; Self-assembly ; Chemical physics ; Chemical engineering ; Chemistry ; Physics ; Composite material ; Engineering Pickering emulsions and particle stabilization ; Nanomaterials and Printing Technologies ; Surfactants and Colloidal Systems
Authors: Kwang Jun Lee | Alexander C. Trowbridge | Graham D. Bruce | George Dwapanyin | Kylie R. Dunning | Kishan Dholakia | Erik P. Schartner
Source: Current Research in Food Science (article, 2024-01-01)
Field: Chemistry — Analytical Chemistry

Learning algorithms for identification of whisky using portable Raman spectroscopy Reliable identification of high-value products such as whisky is vital due to rising issues of brand substitution and quality control in the industry. We have developed a novel framework that can perform whisky analysis directly from raw spectral data with no human intervention by integrating machine learning models with a portable Raman device. We demonstrate that machine learning models can achieve over 99% accuracy in brand or product identification across twenty-eight commercial samples. To demonstrate the flexibility of this approach, we utilized the same algorithms to quantify ethanol concentrations, as well as measuring methanol levels in spiked whisky samples. To demonstrate the potential use of these algorithms in a real-world environment we tested our algorithms on spectral measurements performed through the original whisky bottle. Through the bottle measurements are facilitated by a beam geometry hitherto not applied to whisky brand identification in conjunction with machine learning. Removing the need for decanting greatly enhances the practicality and commercial potential of this technique, enabling its use in detecting counterfeit or adulterated spirits and other high-value liquids. The techniques established in this paper aim to function as a rapid and non-destructive initial screening mechanism for detecting falsified and tampered spirits, complementing more comprehensive and stringent analytical methods. Computer science ; Identification (biology) ; Algorithm ; Machine learning ; Counterfeit ; Flexibility (engineering) ; Artificial intelligence ; Bottle ; Biochemical engineering ; Engineering ; Mathematics ; Mechanical engineering Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Advanced Chemical Sensor Technologies
Authors: Nazym Zhylkybayeva | Konstantin Paliienko | Anna Topchylo | Alexander N. Zaderko | Alain Géloën | Тatiana Borisova | Liudmyla M. Grishchenko | Ruslan Mariychuk | V. A. Skryshevsky | Gauhar Mussabek | Vladimir Lysenko
Source: Scientific Reports (article, 2024-11-13)
Field: Materials Science — Materials Chemistry

Size dependent properties of Gd3+-free versus Gd3+-doped carbon dots for bioimaging application Gd<sup>3+</sup>- free carbon dots (CDs) were synthesized by one-step solvothermal method using urea, citric acid and 3-(trifluoromethyl)aniline as precursors. Additionally, Gd<sup>3+</sup>-doped CDs were prepared by incorporating gadolinium chloride (Gd<sup>3+</sup> ions) into the synthesis. Size selection of the purified CDs was achieved through filter membranes ranging from 3 kDa to 100 kDa. The chemical composition and optical properties of the obtained samples were characterized by Energy dispersive X-ray (EDX), Fourier-transform infrared spectroscopy (FTIR), Dynamic Light Scattering (DLS), proton relaxation time measurements, Ultraviolet-visible (UV-vis) and fluorescence spectroscopies. A comparative analysis revealed a strong size-dependent behavior in the optical properties of both Gd<sup>3+</sup>-doped and Gd<sup>3+</sup>-free CDs. Furthermore, in vitro tests confirmed the non-cytotoxicity of Gd<sup>3+</sup>-doped CDs, indicating their potential applicability in biomedicine for magnetic resonance imaging (MRI) and red fluorescence-based cell and tissue imaging. Doping ; Carbon fibers ; Nanotechnology ; Materials science ; Chemistry ; Chemical engineering ; Optoelectronics ; Composite material ; Composite number Carbon and Quantum Dots Applications ; Nanocluster Synthesis and Applications ; Advanced biosensing and bioanalysis techniques
Authors: Junwei Yang | Kangjie Zheng | Siyu Long | Zaiqing Nie | Ming Zhang | Xinyu Dai | Wei‐Ying Ma | Hao Zhou
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2024-04-15)
Field: Materials Science — Materials Chemistry

Mol-AE: Auto-Encoder Based Molecular Representation Learning With 3D Cloze Test Objective Abstract 3D molecular representation learning has gained tremendous interest and achieved promising performance in various downstream tasks. A series of recent approaches follow a prevalent framework: an encoder-only model coupled with a coordinate denoising objective. However, through a series of analytical experiments, we prove that the encoderonly model with coordinate denoising objective exhibits inconsistency between pre-training and downstream objectives, as well as issues with disrupted atomic identifiers. To address these two issues, we propose M ol -AE for molecular representation learning, an auto-encoder model using positional encoding as atomic identifiers. We also propose a new training objective named 3D Cloze Test to make the model learn better atom spatial relationships from real molecular substructures. Empirical results demonstrate that M ol -AE achieves a large margin performance gain compared to the current state-of-the-art 3D molecular modeling approach. The source codes of M ol -AE are publicly available at https://github.com/yjwtheonly/MolAE . Autoencoder ; Representation (politics) ; Encoder ; Test (biology) ; Cloze test ; Computer science ; Natural language processing ; Artificial intelligence ; Deep learning ; Linguistics ; Reading (process) ; Biology ; Botany ; Philosophy Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Machine Learning in Bioinformatics
Authors: Najmeh Sanjarani | Mashaallah Rahmani
Source: Heliyon (article, 2024-10-01)
Field: Chemistry — Analytical Chemistry

Exploration of supramolecular solvent-based microextraction for crystal violet detecting in water samples This approach highlights the advantages of supramolecular solvents in a new microextraction model. The distinct properties and behavior of this supramolecular solvent provide enhanced extraction capabilities for detecting crystal violet (CV) in water samples. The methodical experimentation was executed to optimize the critical process parameters, providing maximum efficiency of crystal violet extraction at optimal conditions with pH set at 2.7, 186 μL of extraction solvent, extraction time of 3.5 min, and a salt amount of 3.1 % w/v, yielding the best results. Analytical data from extraction experiments under these optimal conditions demonstrated a high extraction percentage. The extraction model exhibited a linear response within the range of 10-800 ng mL<sup>-1</sup> of crystal violet, with a detection limit of 2 ng mL<sup>-1</sup>. This model enables the measurement of CV in water samples with recovery rates exceeding 97 %, offering a straightforward and accessible approach for analysis. Crystal violet ; Supramolecular chemistry ; Solid-phase microextraction ; Solvent ; Chromatography ; Chemistry ; Materials science ; Nanotechnology ; Organic chemistry ; Gas chromatography–mass spectrometry ; Crystal structure ; Mass spectrometry ; Medicine Analytical chemistry methods development ; Dye analysis and toxicity ; Analytical Chemistry and Chromatography
Authors: Sina Hossein Zadeh | Cem Cakirhan | Danial Khatamsaz | John Broucek | Timothy D. Brown | Xiaoning Qian | İbrahim Karaman | Raymundo Arróyave
Source: Materials & Design (preprint, 2024-06-20)
Field: Materials Science — Materials Chemistry

Data-driven study of composition-dependent phase compatibility in NiTi shape memory alloys The martensitic transformation in NiTi-based Shape Memory Alloys (SMAs) provides a basis for shape memory effect and superelasticity, thereby enabling applications requiring solid-state actuation and large recoverable shape changes upon mechanical load cycling. In order to tailor the transformation to a particular application, the compositional dependence of properties in NiTi-based SMAs, such as martensitic transformation temperatures and hysteresis, has been exploited. However, the compositional design space is large and complex, and experimental studies are expensive. In this work, we develop an interpretable piecewise linear regression model that predicts the λ2 parameter, a measure of compatibility between austenite and martensite phases, and an (indirect) factor that is well-correlated with martensitic transformation hysteresis, based on the chemical features derived from the alloy composition. The model is capable of predicting, for the first time, the type of martensitic transformation for a given alloy chemistry. The proposed model is validated by experimental data from the literature as well as in-house measurements. The results show that the model can effectively distinguish between B19 and B19′ regions for any given composition in NiTi-based SMAs and accurately estimate the λ2 parameter. Shape-memory alloy ; Nickel titanium ; Diffusionless transformation ; Martensite ; Pseudoelasticity ; Austenite ; Materials science ; Hysteresis ; Transformation (genetics) ; Thermodynamics ; Metallurgy ; Physics ; Condensed matter physics ; Chemistry ; Microstructure Shape Memory Alloy Transformations
Authors: Lingyun Zhang | Zeyu Zhao | Lingling Tao | Yixiao Wang | Chi Zhang | Jianing Yang | Yongqiang Jiang | Huiqi Duan | Xiaoguang Zhao | Shaolong Chen | Zilun Wang
Source: Micromachines (review, 2024-12-10)
Field: Materials Science — Electronic, Optical and Magnetic Materials

A Review of Cascaded Metasurfaces for Advanced Integrated Devices This paper reviews the field of cascaded metasurfaces, which are advanced optical devices formed by stacking or serially arranging multiple metasurface layers. These structures leverage near-field and far-field electromagnetic (EM) coupling mechanisms to enhance functionalities beyond single-layer metasurfaces. This review comprehensively discusses the physical principles, design methodologies, and applications of cascaded metasurfaces, focusing on both static and dynamic configurations. Near-field-coupled structures create new resonant modes through strong EM interactions, allowing for efficient control of light properties like phase, polarization, and wave propagation. Far-field coupling, achieved through greater interlayer spacing, enables traditional optical methods for design, expanding applications to aberration correction, spectrometers, and retroreflectors. Dynamic configurations include tunable devices that adjust their optical characteristics through mechanical motion, making them valuable for applications in beam steering, varifocal lenses, and holography. This paper concludes with insights into the potential of cascaded metasurfaces to create multifunctional, compact optical systems, setting the stage for future innovations in miniaturized and integrated optical devices. Holography ; Retroreflector ; Polarization (electrochemistry) ; Stacking ; Computer science ; Electronic engineering ; Optics ; Materials science ; Optoelectronics ; Engineering ; Physics ; Laser Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Antenna Design and Analysis
Authors: Xiaofeng Zhang | Miao Liu | Weiqi Qiu | Wei Zhang
Source: Molecules (article, 2024-03-11)
Field: Chemistry — Organic Chemistry

2-Azidobenzaldehyde-Based [4+2] Annulation for the Synthesis of Quinoline Derivatives Quinoline is a privileged heterocyclic ring which can be found in many drug molecules and bioactive compounds. The development of synthetic methods for making quinoline derivatives continuously attracts the interest of organic and medicinal chemists. This paper highlights 2-azidobenzaldehyde-based [4+2] annulation for the synthesis of quinoline derivatives including fused and spiro-quinolines, quinoline-4-ols, 4-aminoquinolines, and related compounds. Quinoline ; Annulation ; Ring (chemistry) ; Chemistry ; Combinatorial chemistry ; Aminoquinolines ; Molecule ; Organic chemistry ; Catalysis Cyclopropane Reaction Mechanisms ; Catalytic C–H Functionalization Methods ; Synthesis and Catalytic Reactions
Authors: Owen P. Missen | Stuart J. Mills | Thebny Thaíse Moro | Edgar E. Villalobos-Portillo | Hiram Castillo‐Michel | Thomas E. Lockwood | Raquel González de Vega | David Clases
Source: Environmental Chemistry (article, 2024-03-14)
Field: Materials Science — Polymers and Plastics

Natural cobalt–manganese oxide nanoparticles: speciation, detection and implications for cobalt cycling Environmental context Cobalt is a technologically critical element due to its uses in the green energy transition, but its cycling is poorly constrained in surface environments. We determined the form of cobalt in naturally enriched soils and found that it is commonly associated with manganese as mixed oxide nanoparticles. These findings demonstrate that the behaviour of critical elements such as cobalt in the environment is in part governed at the nanoscale. Rationale Cobalt (Co) faces increasing demand for use in batteries and alloys, but its environmental behaviour in terrestrial surface environments is poorly constrained. This study analyses cobalt regolith mineralogy and nanoparticulate phase transitions to address this knowledge gap. Methodology We studied Co-enriched environments across six localities and four distinct deposit types in arid and semi-arid Australian regolith environments to analyse its environmental behaviour. We used a combination of single particle inductively coupled plasma–mass spectrometry (SP ICP-MS) and synchrotron X-ray techniques (fluorescence microscopy, X-ray flouresence microscopy and X-ray absorption spectroscopy). Results We discovered the presence of Co oxide-based nanoparticles in soils surrounding cobalt-rich rocks at all of our studied locations, to our knowledge the first detection of terrestrial Co oxide-based nanoparticles. The extractable concentration of Co in the nanoparticles varied from 0.7 ng of nanoparticulate Co per gram of soil (ng Co g–1), up to 1390 ng Co g–1, the latter soil containing 1 × 109 extractable Co-based nanoparticles per gram of soil. Discussion Nanoparticulate cobalt was typically closely associated with manganese (Mn) in the form of natural Co–Mn oxide phases, with only two of the studied locations not showing a close Co–Mn association. We discuss the environmental drivers that may facilitate formation of Co–Mn oxide nanoparticles. Our study suggests that Co may be more mobile in surface environments than previously thought, with Co–Mn oxide nanoparticles found around all four analysed types of Co-rich outcrops. Cobalt ; Manganese ; Nanoparticle ; Genetic algorithm ; Manganese oxide ; Chemistry ; Cycling ; Environmental chemistry ; Cobalt oxide ; Materials science ; Inorganic chemistry ; Nanotechnology ; Biology ; Organic chemistry Transition Metal Oxide Nanomaterials
Authors: Tong Zhang | Sanyuan Ma | Ziyang Zhang | Yongkang Guo | Daiying Yang | Wei Lü
Source: International Journal of Molecular Sciences (article, 2024-06-29)
Field: Materials Science — Biomaterials

Overview and Evolution of Insect Fibroin Heavy Chain (FibH) The <i>FibH</i> gene, crucial for silk spinning in insects, encodes a protein that significantly influences silk fiber mechanics. Due to its large size and repetitive sequences, limited known sequences of insect FibH impede comprehensive understanding. Here, we analyzed 114 complete <i>FibH</i> gene sequences from Lepidoptera (71 moths, 24 butterflies) and 13 Trichoptera, revealing single-copy <i>FibH</i> in most species, with 2-3 copies in Hesperinae and Heteropterinae (subfamily of skippers). All <i>FibH</i> genes are structured with two exons and one intron (39-45 bp), with the second exon being notably longer. Moths exhibit higher GC content in <i>FibH</i> compared to butterflies and Trichoptera. The FibH composition varies among species, with moths and butterflies favoring Ala, Gly, Ser, Pro, Gln, and Asn, while Trichoptera FibH is enriched in Gly, Ser, and Arg, and has less Ala. Unique to Trichoptera FibH are Tyr, Val, Arg, and Trp, whereas Lepidoptera FibH is marked by polyAla (polyalanine), polySer (polyserine), and the hexapeptide GAGSGA. A phylogenetic analysis suggests that Lepidoptera FibH evolved from Trichoptera, with skipper FibH evolving from Papilionoidea. This study substantially expands the FibH repertoire, providing a foundation for the development of artificial silk. Fibroin ; Insect ; Chain (unit) ; Evolutionary biology ; Biology ; Zoology ; Ecology ; Materials science ; Physics ; SILK ; Composite material Silk-based biomaterials and applications ; Insect and Arachnid Ecology and Behavior ; Invertebrate Immune Response Mechanisms