jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Dongliang Zhang | Dongsheng Jia | Zhou Fang | Hua Min | Xiaoyi Xu | Ying Li
Source: Molecules (article, 2023-09-11)
Field: Materials Science — Materials Chemistry

The Detection of Anthrax Biomarker DPA by Ratiometric Fluorescence Probe of Carbon Quantum Dots and Europium Hybrid Material Based on Poly(ionic)- Liquid Bacillus anthracis has gained international attention as a deadly bacterium and a potentially deadly biological warfare agent. Dipicolinic acid (DPA) is the main component of the protective layer of anthracis spores, and is also an anthrax biomarker. Therefore, it is of great significance to explore an efficient and sensitive DPA detection method. Herein, a novel ratio hybrid probe (CQDs-PIL-Eu<sup>3+</sup>) was prepared by a simple one-step hydrothermal method using carbon quantum dots (CQDs) as an internal reference fluorescence and a covalent bond between CQDs and Eu<sup>3+</sup> by using a polyionic liquid (PIL) as a bridge molecule. The ratiometric fluorescence probe was found to have the characteristics of sensitive fluorescence visual sensing in detecting DPA. The structure and the sensing properties of CQDs-PIL-Eu<sup>3+</sup> were investigated in detail. In particular, the fluorescence intensity ratio of Eu<sup>3+</sup> to CQDs (I<sub>616</sub>/I<sub>440</sub>) was linear with the concentration of DPA in the range of 0-50 μM, so the detection limit of the probe was as low as 32 nm, which was far lower than the DPA dose released by the number of anthrax spores in human body (60 μM) and, thus, can achieve sensitive detection. Therefore, the ratiometric fluorescence probe in this work has the characteristics of strong anti-interference, visual sensing, and high sensitivity, which provides a very promising scheme for the realization of anthrax biomarker DPA detection. Dipicolinic acid ; Fluorescence ; Bacillus anthracis ; Detection limit ; Europium ; Chemistry ; Molecule ; Ionic bonding ; Quantum dot ; Quantum yield ; Nanotechnology ; Materials science ; Chromatography ; Spore ; Organic chemistry ; Ion ; Microbiology ; Bacteria ; Optics Carbon and Quantum Dots Applications ; Luminescence and Fluorescent Materials ; Advanced biosensing and bioanalysis techniques
Authors: Mochamad Asrofi | Rizki Setyobudi | R.A. Ilyas | M. L. Sanyang | Adewale O. Adegbenjo | Izwandy Idris | Senthil Muthu Kumar Thiagamani | Midhun Dominic | Victor Feizal Knight | Mohd Nor Faiz Norrrahim | L. Rajeshkumar | M. R. M. Asyraf
Source: REVIEWS ON ADVANCED MATERIALS SCIENCE (article, 2023-01-01)
Field: Materials Science — Polymers and Plastics

Influence of ultrasonication time on the various properties of alkaline-treated mango seed waste filler reinforced PVA biocomposite Abstract The usage of biodegradable materials is gaining mounting applications owing to the environmental problems created by petroleum-based synthetic materials. Agro-waste materials are finding more scope as reinforcement materials in polymer composites, mainly because of their cost-effectiveness and availability. The main aim of this research work is to utilize agro-waste material in the form of mango seed waste (MSW) as a reinforcing material with polyvinyl alcohol (PVA) to form biocomposite. The biocomposites were fabricated using the solution casting technique. The research work focuses on the influence of varying ultrasonication periods (0–20 min at 5-min intervals, i.e. , 0, 5, 10, 15, and 20 min) on the properties of PVA/MSW biocomposites. The fabricated biocomposites were subjected to tensile test, fracture morphology, moisture absorption (MA), Fourier transform infrared spectroscopy, and thermogravimetric analysis. The results revealed that the material with the highest tensile strength was 3.95 MPa obtained with the 20-min ultrasonication sample. This value is 49% higher than that obtained in the sample without ultrasonication. The scanning electron microscopy analysis shows that the 20-min ultrasonication sample indicated a good distribution of MSW fillers in the PVA contrasted with the rest of the samples. The thermal stability of the samples treated with ultrasonication was found to be significantly higher than that of the untreated samples, whereas the MA value decreased with increasing ultrasonication time. It can be observed from the results that biocomposites can be a potential alternative to the synthetic materials used in packaging applications. Biocomposite ; Materials science ; Sonication ; Thermogravimetric analysis ; Ultimate tensile strength ; Composite material ; Fourier transform infrared spectroscopy ; Filler (materials) ; Polymer ; Thermal stability ; Chemical engineering ; Composite number Natural Fiber Reinforced Composites ; Nanocomposite Films for Food Packaging ; biodegradable polymer synthesis and properties
Authors: Andreas Prahs | Lukas Schöller | Felix Schwab | Daniel Schneider | Thomas Böhlke | Britta Nestler
Source: Computational Mechanics (article, 2023-10-04)
Field: Materials Science — Materials Chemistry

A multiphase-field approach to small strain crystal plasticity accounting for balance equations on singular surfaces Abstract An implementation of the crystal plasticity theory in the context of the multiphase-field method provides a numerically efficient tracking of evolving grain boundaries, modeled as diffuse interfaces. In literature, several approaches exist for the implementation of the plastic material behavior within the diffuse interface, based on interpolation, homogenization, or the mechanical jump conditions. Among these, only the jump condition approach exhibits an intrinsic relationship to the sharp interface (SI) theory. Therefore, in the work at hand, the implementation of the crystal plasticity theory within the jump condition approach, referred to as phase-specific plastic fields approach (PSPFA), is discussed in detail. The PSPFA is compared to the interpolation approach, referred to as common plastic fields approach (CPFA), using three-dimensional benchmark simulations of a bicrystal set-up. The comparison reveals that the PSPFA and SI coincide convincingly regarding the accumulated plastic slip and the Mises stress. In contrast, a significant deviation of CPFA and SI is observed both quantitatively and qualitatively, not only within the diffuse interface region, but throughout the complete simulation domain. A variation of the interface width illustrates that this observation can be transferred to the normal components of the total strain, even for smaller interface widths. Consequently, a quantitative estimate of the plastic material behavior, which is crucial for the prediction of the dynamic behavior of grain boundaries, is only provided by the PSPFA. The application of the crystal plasticity in the context of PSPFA to more complex microstructures is illustrated with respect to a periodic honeycomb-structure and an octotuple. Plasticity ; Homogenization (climate) ; Materials science ; Jump ; Interpolation (computer graphics) ; von Mises yield criterion ; Mechanics ; Mathematical analysis ; Mathematics ; Finite element method ; Physics ; Thermodynamics ; Classical mechanics ; Composite material Microstructure and mechanical properties ; Aluminum Alloy Microstructure Properties ; Metallurgy and Material Forming
Authors: Patience Mapule Thabede | Fanyana M. Mtunzi | Pardon Nyamukamba
Source: Applied Sciences (article, 2023-04-20)
Field: Chemistry — Spectroscopy

Sorption Behaviour of Ibuprofen Using Activated Carbon Derived from Rose Geranium (Pelargonium graveolens L.) Leaves This research assessed the adsorption of a pharmaceutical compound, ibuprofen, using rose geranium (Pelargonium graveolens L.) leaves to prepare low-cost activated carbon through orthophosphoric acid (H3PO4) activation. The activated carbon from rose geranium leaves (AC-RGL) was characterized by TGA, SEM and FTIR. The results were compared with those from natural rose geranium leaves (Raw-RGL). The influence of chemical parameters for the uptake of ibuprofen on both adsorbents was evaluated through adsorption experiments. The results were subjected to adsorption models, kinetics models and thermodynamic studies to determine the distribution of ibuprofen in the solid and liquid phases. The results for both Raw-RGL and AC-RGL best fitted the Freundlich model, and the kinetic studies were shown to be pseudo-first order. The thermodynamic evaluation suggested exothermic and spontaneous process sorption for ibuprofen on both adsorbents. The maximum sorption capacities for AC-RGL and Raw-RGL were 113.76 and 74.12 mg/g, respectively. This work confirms that low-cost rose geranium leaves can be used as a potential adsorbent for the sorption of ibuprofen in solution. Geranium ; Sorption ; Adsorption ; Activated carbon ; Chemistry ; Nuclear chemistry ; Chromatography ; Raw material ; Organic chemistry ; Botany ; Biology ; Cultivar Analytical Chemistry and Chromatography ; Advanced Chemical Sensor Technologies ; Analytical Methods in Pharmaceuticals
Authors: Laela Hayu Nurani | Citra Ariani Edityaningrum | Irnawati Irnawati | Anggita Rosiana Putri | Anjar Windarsih | Any Guntarti | Abdul Rohman
Source: Indonesian Journal of Chemistry (review, 2023-03-27)
Field: Chemistry — Analytical Chemistry

Chemometrics-Assisted UV-Vis Spectrophotometry for Quality Control of Pharmaceuticals: A Review Spectroscopic method in the UV-Vis region is considered the most molecular spectrometric method for content determination of a single component. However, a lot of pharmaceutical dosage forms comprise two or more components which lead to peak overlapping. Moreover, in the chemical stability test, active pharmaceutical ingredient (API) was also found along with the degradation products, impurities, and adulterant compounds. UV-Vis spectroscopy is one of the methods of choice for the determination or quantification of a single component in pharmaceutical preparations. The pharmaceutical products typically contain two or more APIs having chromophoric agents capable of absorbing UV-Vis beams and the absorbance values are summative from the absorption of each UV-Vis active compound according to the additive nature of Lambert-Beer law. The main problem for the simultaneous determination of API along with impurities and the degradation products in pharmaceutical preparations is the presence of overlapping peaks of UV-Vis spectra. The chemometrics-assisted spectroscopy is one of the analytical efforts to solve these problems. This review highlighted the application of chemometrics in combination with UV-Vis spectroscopy for the assay of API, impurities, adulteration issues and degradation products present in pharmaceutical dosage forms. Chemometrics ; Chemistry ; Ultraviolet visible spectroscopy ; Active ingredient ; Absorbance ; Dosage form ; Spectrophotometry ; Adulterant ; Impurity ; Chromatography ; Spectroscopy ; Forced degradation ; Degradation (telecommunications) ; Analytical Chemistry (journal) ; Organic chemistry ; High-performance liquid chromatography Spectroscopy and Chemometric Analyses ; Analytical Methods in Pharmaceuticals ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Bikram Adhikari | Michael A. Stager | Melissa D. Krebs
Source: Journal of Biomedical Materials Research Part A (review, 2023-02-13)
Field: Materials Science — Biomaterials

<scp>Cell‐instructive</scp> biomaterials in tissue engineering and regenerative medicine The field of biomaterials aims to improve regenerative outcomes or scientific understanding for a wide range of tissue types and ailments. Biomaterials can be fabricated from natural or synthetic sources and display a plethora of mechanical, electrical, and geometrical properties dependent on their desired application. To date, most biomaterial systems designed for eventual translation to the clinic rely on soluble signaling moieties, such as growth factors, to elicit a specific cellular response. However, these soluble factors are often limited by high cost, convoluted synthesis, low stability, and difficulty in regulation, making the translation of these biomaterials systems to clinical or commercial applications a long and arduous process. In response to this, significant effort has been dedicated to researching cell-directive biomaterials which can signal for specific cell behavior in the absence of soluble factors. Cells of all tissue types have been shown to be innately in tune with their microenvironment, which is a biological phenomenon that can be exploited by researchers to design materials that direct cell behavior based on their intrinsic characteristics. This review will focus on recent developments in biomaterials that direct cell behavior using biomaterial properties such as charge, peptide presentation, and micro- or nano-geometry. These next generation biomaterials could offer significant strides in the development of clinically relevant medical devices which improve our understanding of the cellular microenvironment and enhance patient care in a variety of ailments. Biomaterial ; Regenerative medicine ; Nanotechnology ; Tissue engineering ; Materials science ; Biomedical engineering ; Biochemical engineering ; Cell biology ; Engineering ; Stem cell ; Biology Supramolecular Self-Assembly in Materials ; 3D Printing in Biomedical Research ; Silk-based biomaterials and applications
Authors: Hannah M. Hartge | Eckhard Flöter | Thomas A. Vilgis
Source: Physics of Fluids (article, 2023-06-01)
Field: Materials Science — Materials Chemistry

Crystallization in highly supersaturated, agitated sucrose solutions Supersaturated sucrose solutions that have been sufficiently cooled without nucleation represent a metastable system in which agitation promotes fast crystallization. Applications of this physically interesting process can be found, for example, in the production of fondants in confectionery. This work considers supersaturated sucrose–water solutions under agitation, different temperatures, and concentrations as simplified fondant model systems. Although simple in composition, such solutions undergo complex kinetic and thermodynamic processes during crystallization under agitation. Main attention is paid to the torque during constant kneading of the samples at controlled temperature, accompanied by light microscopic examination of a characteristic sample. All torque curves show a characteristic minimum followed by a sharp peak during crystallization, which are attributed to an interplay of changes in concentration of the continuous liquid phase, formation of big conglomerates, and breaking of largest particles during continued growth. When comparing the crystallization times with classical nucleation theory, it is found that the variations are related to temperature and supersaturation in the same way as given by induction time models of thermodynamics and statistical physics. Supersaturation ; Crystallization ; Nucleation ; Thermodynamics ; Metastability ; Physics ; Work (physics) Crystallization and Solubility Studies ; Freezing and Crystallization Processes ; Microencapsulation and Drying Processes
Authors: Hong Liu | Huazhang Guo | Yibin Fang | Liang Wang | Peng Li
Source: Molecules (article, 2023-02-02)
Field: Materials Science — Materials Chemistry

Rational Design of Nitrogen-Doped Carbon Dots for Inhibiting β-Amyloid Aggregation The fibrillization and abnormal aggregation of <i>β</i>-amyloid (A<i>β</i>) peptides are commonly recognized risk factors for Alzheimer's disease (AD) brain, and require an effective strategy to inhibit the A<i>β</i> deposition and treat AD. Herein, we designed and synthesized nitrogen-doped carbon dots (N-CDs) as an A<i>β</i>-targeted probe, which exhibits the capacity of inhibiting the 1-42 A<i>β</i> (A<i>β</i><sub>1-42</sub>) self-assembly in vitro. The N-CDs exhibited orange emission with an emission wavelength of 570 nm, which demonstrates their excellent optical properties with excitation-independent behavior. Meanwhile, the N-CDs have spherical morphologies with an average size of 2.2 nm, whose surface enriches the amino, carboxyl, and hydroxyl groups. These preparties are conducive to improving their biological water solubility and provide a large number of chemical bonds for further interaction with proteins. Contrary to this, the kinetic process, size evolutions, and morphologies changes of A<i>β</i><sub>1-42</sub> were inhibited in the presence of N-CDs in the determination of a thioflavin T assay, dynamic light scattering, transmission electron microscope, etc. Finally, the safety application of N-CDs on A<i>β</i><sub>1-42</sub>-induced cytotoxicity was further demonstrated via in vitro cytotoxicity experiments. This work demonstrates the effective outcome of suppressing A<i>β</i> aggregation, which provides a new view into the high-efficiency and low-cytotoxicity strategy in AD theranostics. Rational design ; Amyloid (mycology) ; Chemistry ; Nanotechnology ; Amyloid β ; Carbon fibers ; Nitrogen ; Biophysics ; Biochemistry ; Materials science ; Biology ; Organic chemistry ; Medicine ; Inorganic chemistry ; Internal medicine ; Composite material ; Disease Carbon and Quantum Dots Applications ; Alzheimer's disease research and treatments ; Graphene and Nanomaterials Applications
Authors: Yisen Liu | Songbin Zhou | Zhiyong Wan | Zefan Qiu | Lulu Zhao | Kunkun Pang | Chang Li | Zexuan Yin
Source: Foods (article, 2023-07-11)
Field: Chemistry — Analytical Chemistry

A Self-Supervised Anomaly Detector of Fruits Based on Hyperspectral Imaging Hyperspectral imaging combined with chemometric approaches is proven to be a powerful tool for the quality evaluation and control of fruits. In fruit defect-detection scenarios, developing an unsupervised anomaly detection framework is vital, as defect sample preparation is labor-intensive and time-consuming, especially for exploring potential defects. In this paper, a spectral–spatial, information-based, self-supervised anomaly detection (SSAD) approach is proposed. During training, an auxiliary classifier is proposed to identify the projection axes of principal component (PC) images that were transformed from the hyperspectral data cubes. In test time, the fully connected layer of the learned classifier was used as a ‘spectral–spatial’ feature extractor, and the feature similarity metric was adopted as the score function for the downstream anomaly evaluation task. The proposed network was evaluated with two fruit data sets: a strawberry data set with bruised, infected, chilling-injured, and contaminated test samples and a blueberry data set with bruised, infected, chilling-injured, and wrinkled samples as anomalies. The results show that the SSAD yielded the best anomaly detection performance (AUC = 0.923 on average) over the baseline methods, and the visualization results further confirmed its advantage in extracting effective ‘spectral–spatial’ latent representation. Moreover, the robustness of SSAD is verified with the data pollution experiment; it performed significantly better than the baselines when a portion of anomalous samples was involved in the training process. Hyperspectral imaging ; Pattern recognition (psychology) ; Artificial intelligence ; Anomaly detection ; Principal component analysis ; Computer science ; Classifier (UML) ; Robustness (evolution) ; Extractor ; Visualization ; Engineering ; Chemistry Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Identification and Quantification in Food
Authors: Julia Marconato Sudki | Gustavo Roberto Fonseca de Oliveira | André Dantas de Medeiros | Thiago Mastrangelo | Valter Arthur | Edvaldo Aparecido Amaral da Silva | Clíssia Barboza da Silva
Source: Frontiers in Plant Science (article, 2023-02-22)
Field: Chemistry — Analytical Chemistry

Fungal identification in peanuts seeds through multispectral images: Technological advances to enhance sanitary quality The sanitary quality of seed is essential in agriculture. This is because pathogenic fungi compromise seed physiological quality and prevent the formation of plants in the field, which causes losses to farmers. Multispectral images technologies coupled with machine learning algorithms can optimize the identification of healthy peanut seeds, greatly improving the sanitary quality. The objective was to verify whether multispectral images technologies and artificial intelligence tools are effective for discriminating pathogenic fungi in tropical peanut seeds. For this purpose, dry peanut seeds infected by fungi (<i>A. flavus</i>, <i>A. niger</i>, <i>Penicillium</i> sp., and <i>Rhizopus</i> sp.) were used to acquire images at different wavelengths (365 to 970 nm). Multispectral markers of peanut seed health quality were found. The incubation period of 216 h was the one that most contributed to discriminating healthy seeds from those containing fungi through multispectral images. Texture (Percent Run), color (CIELab <i>L</i>*) and reflectance (490 nm) were highly effective in discriminating the sanitary quality of peanut seeds. Machine learning algorithms (LDA, MLP, RF, and SVM) demonstrated high accuracy in autonomous detection of seed health status (90 to 100%). Thus, multispectral images coupled with machine learning algorithms are effective for screening peanut seeds with superior sanitary quality. Multispectral image ; Artificial intelligence ; Identification (biology) ; Quality (philosophy) ; Support vector machine ; Reflectivity ; Computer science ; Environmental science ; Biotechnology ; Biology ; Botany ; Physics Spectroscopy and Chemometric Analyses ; Nuts composition and effects ; Plant Pathogens and Fungal Diseases
Authors: Ioannis Navrozidis | Xanthoula Eirini Pantazi | Anastasia L. Lagopodi | Dionysis Bochtis | Thomas Alexandridis
Source: Remote Sensing (article, 2023-12-11)
Field: Chemistry — Analytical Chemistry

Application of Machine Learning for Disease Detection Tasks in Olive Trees Using Hyperspectral Data Timely and accurate detection of diseases plays a significant role in attaining optimal growing conditions of olive crops. This study evaluated the use of two machine learning algorithms, Random Forest (RF) and XGBoost (XGB), in conjunction with the feature selection methods Recursive Feature Elimination (RFE) and Mutual Information (MI), for detecting stress in olive trees using hyperspectral data. The research was conducted in Halkidiki, Northern Greece, and focused on identifying stress caused by biotic and abiotic factors through the analysis of hyperspectral images. Both the RF and XGB algorithms demonstrated high efficacy in stress classification, achieving roc-auc scores of 0.977 and 0.955, respectively. The study also highlighted the effectiveness of RFE and MI in optimizing the classification process, with RF and XGB requiring a reduced number of hyperspectral features for an optimal performance of 1.00 on both occasions. Key wavelengths indicative of stress were identified in the visible to near-infrared spectrum, suggesting their strong correlation with olive tree stress. These findings contribute to precision agriculture by demonstrating the viability of using machine learning for stress detection in olive trees, and underscores the importance of feature selection in improving classifier performance. Hyperspectral imaging ; Random forest ; Feature selection ; Computer science ; Artificial intelligence ; Pattern recognition (psychology) ; Machine learning ; Feature (linguistics) ; Classifier (UML) Spectroscopy and Chemometric Analyses ; Date Palm Research Studies ; Remote Sensing in Agriculture