jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Joana F. Soeiro | Filipa L. Sousa | Maria V. Monteiro | Vítor M. Gaspar | Nuno J. O. Silva | João F. Mano
Source: Nanoscale Horizons (article, 2024-01-01)
Field: Materials Science — Biomaterials

Advances in screening hyperthermic nanomedicines in 3D tumor models Hyperthermic nanomedicines are particularly relevant for tackling human cancer, providing a valuable alternative to conventional therapeutics. The early-stage preclinical performance evaluation of such anti-cancer treatments is conventionally performed in flat 2D cell cultures that do not mimic the volumetric heat transfer occurring in human tumors. Recently, improvements in bioengineered 3D <i>in vitro</i> models have unlocked the opportunity to recapitulate major tumor microenvironment hallmarks and generate highly informative readouts that can contribute to accelerating the discovery and validation of efficient hyperthermic treatments. Leveraging on this, herein we aim to showcase the potential of engineered physiomimetic 3D tumor models for evaluating the preclinical efficacy of hyperthermic nanomedicines, featuring the main advantages and design considerations under diverse testing scenarios. The most recent applications of 3D tumor models for screening photo- and/or magnetic nanomedicines will be discussed, either as standalone systems or in combinatorial approaches with other anti-cancer therapeutics. We envision that breakthroughs toward developing multi-functional 3D platforms for hyperthermia onset and follow-up will contribute to a more expedited discovery of top-performing hyperthermic therapies in a preclinical setting before their <i>in vivo</i> screening. Cancer ; Tumor microenvironment ; Medicine ; Computer science ; Tumor cells ; Cancer research Nanoparticle-Based Drug Delivery ; Nanoplatforms for cancer theranostics ; Extracellular vesicles in disease
Authors: Xi Pan | Zhiming Yu | Zhong Yang
Source: Forests (article, 2024-03-19)
Field: Chemistry — Organic Chemistry

A Multi-Scale Convolutional Neural Network Combined with a Portable Near-Infrared Spectrometer for the Rapid, Non-Destructive Identification of Wood Species The swift and non-destructive classification of wood species holds crucial significance for the utilization and trade of wood resources. Portable near-infrared (NIR) spectrometers have the potential for rapid and non-destructive wood species identification, and while several studies have explored related methodologies, further research on their practical application is needed. To address this research gap, this study proposes a multi-scale convolutional neural network (CNN) combined with a portable NIR spectrometer (wavelengths range: 908 to 1676 nm) for wood species identification. To enhance the capability of directly extracting robust features from NIR spectral data collected by a portable spectrometer, the Gramian angular field (GAF) method is introduced to transform 1-dimensional (1D) NIR spectral data into 2-dimensional (2D) data matrices. Furthermore, a multi-scale CNN model is utilized for direct feature extraction. The representation by 2D matrices, instead of 1D NIR spectral data, aligns with 2D convolutional operations and enables a more robust extraction of discriminative features. In the experimental phase, eight wood species were identified using the proposed method, alongside commonly used multivariate data analysis and machine learning (ML) methods. The StratifiedGroupKFold dataset partitioning approach and five-fold cross-validation were used. Additionally, nine spectral preprocessing methods were compared, and principal component analysis (PCA) was used for feature extraction in the ML method. Evaluation metrics, such as accuracy, precision, and recall, were adopted to assess the performance of the methods. The proposed multi-scale CNN model, in combination with 2D GAF matrices of the 1D spectral data, yielded the most accurate results with a mean accuracy of 97.34% in the five-fold validation. These findings present a new approach for the construction of a rapid, non-destructive, and automatic wood species identification method using a portable NIR spectrometer. Convolutional neural network ; Identification (biology) ; Spectrometer ; Scale (ratio) ; Environmental science ; Infrared ; Species identification ; Remote sensing ; Computer science ; Materials science ; Artificial intelligence ; Physics ; Botany ; Biology ; Astronomy ; Geology ; Optics ; Cartography ; Geography Wood and Agarwood Research ; Industrial Vision Systems and Defect Detection ; Spectroscopy and Chemometric Analyses
Authors: Vincent Albrecht | Johannes B. Mueller‐Reif | Thierry M. Nordmann | Andreas Mund | Lisa Schweizer | Philipp E. Geyer | Lili Niu | Juanjuan Wang | Frederik Post | Marc Oeller | Andreas Metousis | Annelaura Bach Nielsen | Michael F. Steger | Nicolai J. Wewer Albrechtsen | Matthias Mann
Source: Molecular & Cellular Proteomics (article, 2024-11-09)
Field: Chemistry — Spectroscopy

Bridging the Gap From Proteomics Technology to Clinical Application: Highlights From the 68th Benzon Foundation Symposium The 68th Benzon Foundation Symposium brought together leading experts to explore the integration of mass spectrometry-based proteomics and artificial intelligence to revolutionize personalized medicine. This report highlights key discussions on recent technological advances in mass spectrometry-based proteomics, including improvements in sensitivity, throughput, and data analysis. Particular emphasis was placed on plasma proteomics and its potential for biomarker discovery across various diseases. The symposium addressed critical challenges in translating proteomic discoveries to clinical practice, including standardization, regulatory considerations, and the need for robust "business cases" to motivate adoption. Promising applications were presented in areas such as cancer diagnostics, neurodegenerative diseases, and cardiovascular health. The integration of proteomics with other omics technologies and imaging methods was explored, showcasing the power of multimodal approaches in understanding complex biological systems. Artificial intelligence emerged as a crucial tool for the acquisition of large-scale proteomic datasets, extracting meaningful insights, and enhancing clinical decision-making. By fostering dialog between academic researchers, industry leaders in proteomics technology, and clinicians, the symposium illuminated potential pathways for proteomics to transform personalized medicine, advancing the cause of more precise diagnostics and targeted therapies. Bridging (networking) ; Foundation (evidence) ; Proteomics ; Data science ; Engineering ethics ; Computational biology ; Computer science ; Nanotechnology ; Library science ; Medicine ; Engineering ; Chemistry ; Materials science ; Biology ; Biochemistry ; Geography ; Archaeology Advanced Proteomics Techniques and Applications ; Advanced Biosensing Techniques and Applications ; Molecular Biology Techniques and Applications
Authors: Xiaotong Liu | Udit Pant | Natasha Logan | Qiqi He | Brett Greer | Christopher T. Elliott | Cuong Cao
Source: Food Chemistry (article, 2024-06-03)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Non-linear responses via agglomeration and aggregation of gold nanoparticles for surface-enhanced Raman spectroscopy (SERS) coupled with chemometric analysis for chlorpyrifos detection This study investigates the behaviour of gold nanoparticles (AuNPs) when exposed to chlorpyrifos, an agricultural pesticide, and its application in detecting the pesticide via surface-enhanced Raman spectroscopy (SERS). Under synergistic addition of NaCl, AuNPs undergo agglomeration at lower chlorpyrifos concentrations but aggregation at higher concentrations, resulting in a distinctive nonlinear SERS response. A linear relationship is obtained between 0.001 and 1 ppm with detection limit (LOD) of 0.009 ppm, while an inverse response is observed at higher concentrations (1-1000 ppm) with a LOD of 1 ppm. Combining the colorimetric response of AuNP solutions, their absorbance spectra, and principal component analysis can improve detection reliability. The assay, coupled with a simple recovery method using acetonitrile swabbing, achieves high reproducibility in detecting chlorpyrifos in cucumber, even at concentrations as low as 0.11 ppm. This approach can be tailored for various chlorpyrifos concentrations not only in cucumbers but also in different food matrices. Surface-enhanced Raman spectroscopy ; Raman spectroscopy ; Colloidal gold ; Economies of agglomeration ; Nanoparticle ; Chemistry ; Analytical Chemistry (journal) ; Materials science ; Nanotechnology ; Chromatography ; Chemical engineering ; Raman scattering ; Optics Gold and Silver Nanoparticles Synthesis and Applications ; Spectroscopy Techniques in Biomedical and Chemical Research ; Melamine detection and toxicity
Authors: Mekhrdod Subhoni | A.M. Srivastava | Bibo Lou | Dilshod Nematov | Amondulloi Burhonzoda | Tomoyuki Yamamoto | Chong‐Geng Ma | M.G. Brik
Source: Inorganic Chemistry (article, 2024-10-21)
Field: Materials Science — Materials Chemistry

Thermal Quenching Mechanism of Mn<sup>4+</sup> in Na<sub>2</sub>SiF<sub>6</sub>, NaKSiF<sub>6</sub>, and K<sub>2</sub>SiF<sub>6</sub> Phosphors: Insights from the First-Principles Analysis This study aims to identify the key factors governing the thermal quenching of Mn<sup>4+</sup> ion luminescence in fluoride-based phosphor materials used as red emitters in modern-day phosphor-converted LED devices. Here, we employ first-principles calculations for Mn<sup>4+</sup>-doped Na<sub>2</sub>SiF<sub>6</sub>, NaKSiF<sub>6</sub>, and K<sub>2</sub>SiF<sub>6</sub> hosts to explore how host properties and local coordination environments influence thermal quenching behavior. The ΔSCF method was used to model the geometric structures of the Mn<sup>4+4</sup>A<sub>2</sub> (ground) and <sup>2</sup>E, <sup>4</sup>T<sub>2</sub> (excited) states and the energies of the optical transitions between these states. Our results reveal that thermal quenching in Na<sub>2</sub>SiF<sub>6</sub> and K<sub>2</sub>SiF<sub>6</sub> phosphors occurs through thermally activated <sup>2</sup>E → <sup>4</sup>T<sub>2</sub> → <sup>4</sup>A<sub>2</sub> crossover. In contrast, thermal quenching in NaKSiF<sub>6</sub> is due to other nonradiative decay pathways. Investigations of the mechanical stability of these fluorides show that NaKSiF<sub>6</sub> is mechanically unstable. We suggest that this property of the host limits the luminescence efficiency of the embedded Mn<sup>4+</sup> ions. We also determined the reason for the difference in the intensity of the <sup>2</sup>E → <sup>4</sup>A<sub>2</sub> emission transition (ZPL) in the systems. These findings advance our fundamental understanding of the thermal quenching mechanism of Mn<sup>4+</sup> ion luminescence in fluorides, and the results can aid future discoveries of technologically useful phosphors through high-throughput design methodologies. Chemistry ; Phosphor ; Quenching (fluorescence) ; Analytical Chemistry (journal) ; Fluorescence ; Nuclear physics ; Physics Luminescence Properties of Advanced Materials ; Inorganic Fluorides and Related Compounds ; Inorganic Chemistry and Materials
Authors: Nader Ekramirad | Lauren E. Doyle | Julia R. Loeb | Dipak K. Santra | Akinbode A. Adedeji
Source: Foods (article, 2024-04-26)
Field: Chemistry — Analytical Chemistry

Hyperspectral Imaging and Machine Learning as a Nondestructive Method for Proso Millet Seed Detection and Classification Millet is a small-seeded cereal crop with big potential. There are many different cultivars of proso millet (<i>Panicum miliaceum</i> L.) with different characteristics, bringing forth the issue of sorting which are important for growers, processors, and consumers. Current methods of grain cultivar detection and classification are subjective, destructive, and time-consuming. Therefore, there is a need to develop nondestructive methods for sorting the cultivars of proso millet. In this study, the feasibility of using near-infrared (NIR) hyperspectral imaging (900-1700 nm) to discriminate between different cultivars of proso millet seeds was evaluated. A total of 5000 proso millet seeds were randomly obtained and investigated from the ten most popular cultivars in the United States, namely Cerise, Cope, Earlybird, Huntsman, Minco, Plateau, Rise, Snowbird, Sunrise, and Sunup. To reduce the large dimensionality of the hyperspectral imaging, principal component analysis (PCA) was applied, and the first two principal components were used as spectral features for building the classification models because they had the largest variance. The classification performance showed prediction accuracy rates as high as 99% for classifying the different cultivars of proso millet using a Gradient tree boosting ensemble machine learning algorithm. Moreover, the classification was successfully performed using only 15 and 5 selected spectral features (wavelengths), with an accuracy of 98.14% and 97.6%, respectively. The overall results indicate that NIR hyperspectral imaging could be used as a rapid and nondestructive method for the classification of proso millet seeds. Hyperspectral imaging ; Artificial intelligence ; Computer science ; Pattern recognition (psychology) ; Machine learning ; Remote sensing ; Geography Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Leaf Properties and Growth Measurement
Authors: Guruswamy Kumaraswamy | Senthilkumar Thambiannan | A. Arputharaj | Kirti Jalgaonkar | Ajinath Dukare | R. Pandiselvam | Niraj Kumar Jha
Source: Heliyon (article, 2024-10-24)
Field: Materials Science — Polymers and Plastics

Coir fibre-reinforced concrete for enhanced compressive strength and sustainability in construction applications This research explores the potential of coir fibre as a sustainable and effective reinforcement material to enhance the compressive strength (CS) of concrete. The influence of the fibre volume fraction (FVF) and fibre length (FL) on the CS of the coir fibre reinforced concrete was studied using the response surface method (RSM). The selected range for the FVF was from 4 % to 12 %, and the FL varied from 0.4 cm to 1.2 cm, as per the experimental design. The research determined that the coir fibre with an FVF of 4 % and an FL of 10 mm yielded the maximum CS for the reinforced concrete cubes, measuring 34 N/mm<sup>2</sup>. Furthermore, an increase in fibre content was observed to lead to a decrease in the workability of coir fibre-reinforced concrete. Furthermore, Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD) analyses of the control and coir fibres extracted from the concrete cubes after a period of 1 year indicated no significant changes in the functional properties, thermal properties and crystallinity of the fibres. Compressive strength ; Coir ; Sustainability ; Materials science ; Composite material ; Pervious concrete ; Mechanical strength ; Geotechnical engineering ; Civil engineering ; Engineering ; Cement Natural Fiber Reinforced Composites ; Advanced Cellulose Research Studies ; Innovative concrete reinforcement materials
Authors: Natalia Cano | Oscar E. Médina | Iván Mozo | Santiago Céspedes | Camilo A. Franco | Farid B. Cortés
Source: Energy (article, 2024-06-07)
Field: Chemistry — Analytical Chemistry

Viability of the steam-based extraction of extra-heavy crude oil using nanoparticles: Exergy and life-cycle assessment Steam injection ; Nanofluid ; Exergy ; Extraction (chemistry) ; Environmental science ; Fraction (chemistry) ; Life-cycle assessment ; Enhanced oil recovery ; Mass fraction ; Waste management ; Pulp and paper industry ; Process engineering ; Chemistry ; Materials science ; Nanoparticle ; Engineering ; Nanotechnology ; Chromatography ; Production (economics) Petroleum Processing and Analysis ; Global Energy and Sustainability Research ; Enhanced Oil Recovery Techniques
Authors: Taewon Choi | Chulsoo Choi | Junseo Bang | Youngjin Kim | Hyunwoo Son | Changhyun Kim | Junhyeok Jang | Yoonchan Jeong | Byoungho Lee
Source: Nano Letters (article, 2024-08-27)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Multiwavelength Achromatic Deflector in the Visible Using a Single-Layer Freeform Metasurface Deflectors are essential for modulating beam direction in optical systems but often face form factor issues or chromatic aberration with conventional optical elements, such as prisms, mirrors, and diffractive/holographic optical elements. Despite recent efforts to address such issues using metasurfaces, their practicality remains limited due to operation wavelengths in the near-infrared or the fabrication difficulties inherent in the multilayer scheme. Here, we propose a novel single-layer metasurface achieving multiwavelength chromatic aberration-free deflection across the visible spectrum by employing the robust freeform design strategy to simplify the fabrication process. By properly selecting diffraction orders for red, green, and blue wavelengths to achieve identical wavelength-diffraction-order products, the metasurface deflects light at a consistent angle of 41.3° with a high efficiency. The coupled Bloch mode analysis explains the physical properties, and experimental fabrication and characterization confirm its effectiveness. This approach holds potential for various applications such as AR/VR, digital cameras, and high-quality optical systems. Achromatic lens ; Chromatic aberration ; Optics ; Fabrication ; Holography ; Diffraction ; Wavelength ; Materials science ; Chromatic scale ; Optoelectronics ; Optical engineering ; Diffraction efficiency ; Infrared ; Physics ; Computer science Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Photonic Crystals and Applications
Authors: Shi Sun | Yue Gou | Tie Jun Cui | Hui Feng
Source: PhotoniX (article, 2024-12-02)
Field: Materials Science — Electronic, Optical and Magnetic Materials

High-security nondeterministic encryption communication based on spin-space-frequency multiplexing metasurface Abstract Information security plays an important role in every aspect of life to protect data from stealing and deciphering. However, most of the previously reported works were based on pure algorithm layer or pure physical layer encryptions, which have certain limitations in security. In this paper, a nondeterministic message encryption communication scheme is proposed based on a spin-space-frequency multiplexing metasurface (SSFMM), which integrates both algorithmic and physical layer encryptions, and can also produce multiple different ciphertexts for the same message to prevent the message from being cracked through frequency analysis, thus greatly enhancing the security of the information. To be specific, an SSFMM is first designed as a physical-layer meta-key, which can generate eight independent dot matrix holograms with different spin, space, and frequency characteristics. The target message is then encrypted based on these dot matrix holograms combined with algorithmic operations, and the encrypted message is converted into a quick response (QR) code for easy sending to the target users. Once the target user gets that QR code, he/she can scan it to obtain the encryption information, and then recover the target message according to the pre-agreed encryption protocol combined with the eight dot matrix holograms of SSFMM. Finally, the feasibility of the proposed encryption scheme was experimentally validated at the microwave frequency band. Encryption ; Computer science ; Multiplexing ; Physics ; Computer network ; Telecommunications Metamaterials and Metasurfaces Applications ; Wireless Communication Security Techniques ; Orbital Angular Momentum in Optics
Authors: Kento Abeywardane | C. Franklin Goldsmith
Source: ACS Physical Chemistry Au (article, 2024-02-27)
Field: Chemistry — Organic Chemistry

Accurate Enthalpies of Formation for PFAS from First-Principles: Combining Different Levels of Theory in a Generalized Thermochemical Hierarchy The enthalpies of formation are computed for a large number of per- and poly fluoroalkyl substances (PFAS) using a connectivity-based hierarchy (CBH) approach. A combination of different electronic structure methods are used to provide the reference data in a hierarchical manner. The ANL0 method, in conjunction with the active thermochemical tables, provides enthalpies of formation for smaller species with subchemical accuracy. Coupled-cluster theory with explicit correlations are used to compute enthalpies of formation for intermediate species, based upon the ANL0 results. For the largest PFAS, including perfluorooctanoic acid (PFOA) and heptafluoropropylene oxide dimer acid (GenX), coupled-cluster theory with local correlations is used. The sequence of homodesmotic reactions proposed by the CBH are determined automatically by a new open-source code, AutoCBH. The results are the first reported enthalpies of formation for the majority of the species. A convergence analysis and global uncertainty quantification confirm that the enthalpies of formation at 0 K should be accurate to within ±5 kJ/mol. This new approach is not limited to PFAS, but can be applied to many chemical systems. Standard enthalpy of formation ; Hierarchy ; Cluster (spacecraft) ; Perfluorooctanoic acid ; Chemistry ; Coupled cluster ; Convergence (economics) ; Standard enthalpy change of formation ; Thermodynamics ; Computational chemistry ; Statistical physics ; Computer science ; Molecule ; Physical chemistry ; Physics ; Environmental chemistry ; Organic chemistry Chemical Thermodynamics and Molecular Structure ; Atmospheric chemistry and aerosols ; Advanced Chemical Physics Studies
Authors: Muhammad Awais Aslam | Simon Leitner | Shubham Tyagi | Alexandros Provias | Vadym Tkachuk | Egon Pavlica | Martina Dienstleder | Daniel Knez | Kenji Watanabe | Takashi Taniguchi | Dayu Yan | Youguo Shi | Theresia Knobloch | Michael Waltl | Udo Schwingenschlögl | Tibor Grasser | Aleksandar Matković
Source: Nano Letters (article, 2024-05-24)
Field: Materials Science — Materials Chemistry

All van der Waals Semiconducting PtSe<sub>2</sub> Field Effect Transistors with Low Contact Resistance Graphite Electrodes Contact resistance is a multifaceted challenge faced by the 2D materials community. Large Schottky barrier heights and gap-state pinning are active obstacles that require an integrated approach to achieve the development of high-performance electronic devices based on 2D materials. In this work, we present semiconducting PtSe<sub>2</sub> field effect transistors with all-van-der-Waals electrode and dielectric interfaces. We use graphite contacts, which enable high <i>I</i><sub>ON</sub>/<i>I</i><sub>OFF</sub> ratios up to 10<sup>9</sup> with currents above 100 μA μm<sup>-1</sup> and mobilities of 50 cm<sup>2</sup> V<sup>-1</sup> s<sup>-1</sup> at room temperature and over 400 cm<sup>2</sup> V<sup>-1</sup> s<sup>-1</sup> at 10 K. The devices exhibit high stability with a maximum hysteresis width below 36 mV nm<sup>-1</sup>. The contact resistance at the graphite-PtSe<sub>2</sub> interface is found to be below 700 Ω μm. Our results present PtSe<sub>2</sub> as a promising candidate for the realization of high-performance 2D circuits built solely with 2D materials. Contact resistance ; van der Waals force ; Materials science ; Schottky barrier ; Graphite ; Electrode ; Field-effect transistor ; Hysteresis ; Optoelectronics ; Dielectric ; Transistor ; Nanotechnology ; Condensed matter physics ; Electrical engineering ; Chemistry ; Voltage ; Layer (electronics) ; Composite material Graphene research and applications ; 2D Materials and Applications ; MXene and MAX Phase Materials