jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Junjie Wang | Yong Wang | Haoting Zhang | Ziyang Yang | Zhixin Liang | Jiuyang Shi | Hui‐Tian Wang | Dingyu Xing | Jian Sun
Source: Nature Communications (article, 2024-09-01)
Field: Materials Science — Materials Chemistry

E(n)-Equivariant cartesian tensor message passing interatomic potential Machine learning potential (MLP) has been a popular topic in recent years for its capability to replace expensive first-principles calculations in some large systems. Meanwhile, message passing networks have gained significant attention due to their remarkable accuracy, and a wave of message passing networks based on Cartesian coordinates has emerged. However, the information of the node in these models is usually limited to scalars, and vectors. In this work, we propose High-order Tensor message Passing interatomic Potential (HotPP), an E(n) equivariant message passing neural network that extends the node embedding and message to an arbitrary order tensor. By performing some basic equivariant operations, high order tensors can be coupled very simply and thus the model can make direct predictions of high-order tensors such as dipole moments and polarizabilities without any modifications. The tests in several datasets show that HotPP not only achieves high accuracy in predicting target properties, but also successfully performs tasks such as calculating phonon spectra, infrared spectra, and Raman spectra, demonstrating its potential as a tool for future research. Tensor (intrinsic definition) ; Message passing ; Computer science ; Cartesian coordinate system ; Artificial neural network ; Node (physics) ; Embedding ; Equivariant map ; Scalability ; Algorithm ; Artificial intelligence ; Physics ; Mathematics ; Quantum mechanics ; Distributed computing ; Geometry Machine Learning in Materials Science ; Quantum many-body systems ; Protein Structure and Dynamics
Authors: Ahmed M. Agiba | Nihal Mohamed Elmahdy Elsayyad | Hala N. ElShagea | Mahmoud A. Metwalli | Amin Orash Mahmoud Salehi | Saeed Beigi-Boroujeni | Omar Lozano | Alan Aguirre‐Soto | José Luis Arreola-Ramírez | Patricia Segura-Medina | Raghda Rabe Hamed
Source: Pharmaceutics (review, 2024-07-31)
Field: Materials Science — Biomaterials

Advances in Light-Responsive Smart Multifunctional Nanofibers: Implications for Targeted Drug Delivery and Cancer Therapy Over the last decade, scientists have shifted their focus to the development of smart carriers for the delivery of chemotherapeutics in order to overcome the problems associated with traditional chemotherapy, such as poor aqueous solubility and bioavailability, low selectivity and targeting specificity, off-target drug side effects, and damage to surrounding healthy tissues. Nanofiber-based drug delivery systems have recently emerged as a promising drug delivery system in cancer therapy owing to their unique structural and functional properties, including tunable interconnected porosity, a high surface-to-volume ratio associated with high entrapment efficiency and drug loading capacity, and high mass transport properties, which allow for controlled and targeted drug delivery. In addition, they are biocompatible, biodegradable, and capable of surface functionalization, allowing for target-specific delivery and drug release. One of the most common fiber production methods is electrospinning, even though the relatively two-dimensional (2D) tightly packed fiber structures and low production rates have limited its performance. Forcespinning is an alternative spinning technology that generates high-throughput, continuous polymeric nanofibers with 3D structures. Unlike electrospinning, forcespinning generates fibers by centrifugal forces rather than electrostatic forces, resulting in significantly higher fiber production. The functionalization of nanocarriers on nanofibers can result in smart nanofibers with anticancer capabilities that can be activated by external stimuli, such as light. This review addresses current trends and potential applications of light-responsive and dual-stimuli-responsive electro- and forcespun smart nanofibers in cancer therapy, with a particular emphasis on functionalizing nanofiber surfaces and developing nano-in-nanofiber emerging delivery systems for dual-controlled drug release and high-precision tumor targeting. In addition, the progress and prospective diagnostic and therapeutic applications of light-responsive and dual-stimuli-responsive smart nanofibers are discussed in the context of combination cancer therapy. Nanofiber ; Nanotechnology ; Drug delivery ; Electrospinning ; Nanocarriers ; Materials science ; Surface modification ; Targeted drug delivery ; Controlled release ; Chemistry ; Polymer ; Composite material Electrospun Nanofibers in Biomedical Applications ; Advanced Sensor and Energy Harvesting Materials ; Graphene and Nanomaterials Applications
Authors: Zhibin Yin | Wenjie Huang | Kun Li | Alisdair R. Fernie | Shijuan Yan
Source: The Plant Journal (review, 2024-07-11)
Field: Chemistry — Spectroscopy

Advances in mass spectrometry imaging for plant metabolomics—Expanding the analytical toolbox Mass spectrometry imaging (MSI) has become increasingly popular in plant science due to its ability to characterize complex chemical, spatial, and temporal aspects of plant metabolism. Over the past decade, as the emerging and unique features of various MSI techniques have continued to support new discoveries in studies of plant metabolism closely associated with various aspects of plant function and physiology, spatial metabolomics based on MSI techniques has positioned it at the forefront of plant metabolic studies, providing the opportunity for far higher resolution than was previously available. Despite these efforts, profound challenges at the levels of spatial resolution, sensitivity, quantitative ability, chemical confidence, isomer discrimination, and spatial multi-omics integration, undoubtedly remain. In this Perspective, we provide a contemporary overview of the emergent MSI techniques widely used in the plant sciences, with particular emphasis on recent advances in methodological breakthroughs. Having established the detailed context of MSI, we outline both the golden opportunities and key challenges currently facing plant metabolomics, presenting our vision as to how the enormous potential of MSI technologies will contribute to progress in plant science in the coming years. Metabolomics ; Context (archaeology) ; Toolbox ; Plant metabolism ; Biology ; Data science ; Computational biology ; Computer science ; Bioinformatics Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Analytical Chemistry and Chromatography
Authors: Ding Luo | Zerui Liu | Jin Cao | Yuying Yan
Source: Applied Thermal Engineering (article, 2024-11-17)
Field: Materials Science — Materials Chemistry

Feasibility and parametric study of a groove-type thermoelectric generator under multiphysics field conditions Multiphysics ; Groove (engineering) ; Thermoelectric generator ; Generator (circuit theory) ; Mechanical engineering ; Parametric statistics ; Field (mathematics) ; Materials science ; Thermoelectric effect ; Engineering ; Engineering physics ; Structural engineering ; Finite element method ; Physics ; Mathematics ; Thermodynamics Advanced Thermoelectric Materials and Devices ; Heat Transfer and Optimization ; Thermal Radiation and Cooling Technologies
Authors: Rui Lu | Jian Wang | Tingzhi Duan | Tian‐Yi Hu | Guangliang Hu | Yupeng Liu | Weijie Fu | Qiuyang Han | Yiqin Lu | Lu Lu | Shao‐Dong Cheng | Yanzhu Dai | Dengwei Hu | Zhonghui Shen | Chun‐Lin Jia | Chunrui Ma | Ming Liu
Source: Nature Communications (article, 2024-08-03)
Field: Materials Science — Materials Chemistry

Metadielectrics for high-temperature energy storage capacitors Dielectric capacitors are highly desired for electronic systems owing to their high-power density and ultrafast charge/discharge capability. However, the current dielectric capacitors suffer severely from the thermal instabilities, with sharp deterioration of energy storage performance at elevated temperatures. Here, guided by phase-field simulations, we conceived and fabricated the self-assembled metadielectric nanostructure with HfO<sub>2</sub> as second-phase in BaHf<sub>0.17</sub>Ti<sub>0.83</sub>O<sub>3</sub> relaxor ferroelectric matrix. The metadielectric structure can not only effectively increase breakdown strength, but also broaden the working temperature to 400 <sup>o</sup>C due to the enhanced relaxation behavior and substantially reduced conduction loss. The energy storage density of the metadielectric film capacitors can achieve to 85 joules per cubic centimeter with energy efficiency exceeding 81% in the temperature range from 25 °C to 400 °C. This work shows the fabrication of capacitors with potential applications in high-temperature electric power systems and provides a strategy for designing advanced electrostatic capacitors through a metadielectric strategy. Capacitor ; Energy storage ; Computer science ; Materials science ; Electrical engineering ; Physics ; Engineering ; Thermodynamics ; Voltage Ferroelectric and Piezoelectric Materials ; Dielectric materials and actuators ; Semiconductor materials and devices
Authors: Shulin Bai | Dongrui Liu | Haonan Shi | Yongxin Qin | Bingchao Qin | Tao Hong | Tian Gao | Yuting Qiu | Yu Liu | Zhen Li | Peng Kang | Lei Zheng | Li‐Dong Zhao
Source: Advanced Functional Materials (article, 2024-09-27)
Field: Materials Science — Materials Chemistry

Revealing the Origin of Anisotropic Rashba Spin‐Orbital Splitting and Four‐Phonon Scattering in Strontium‐Tin‐Selenium Thermoelectrics Abstract Inspired by the remarkable performance of SnSe‐based compounds in thermoelectrics, a strontium‐tin‐selenium (SrSnSe 2 ) compound is theoretically designed, observing anisotropic Rashba spin‐orbital splitting and strong four‐phonon scattering behavior. Through comprehensive analyses of elastic constants, phonon dispersion, and ab initio molecular dynamics calculations, the mechanical, dynamic, and thermal stability of SrSnSe 2 is demonstrated. Electronic calculations reveal that the anisotropic band is decomposed into two distinct bands (heavy and light) due to anisotropic Rashba spin splitting, significantly impacting the electrical transport properties for n ‐type and p ‐type systems. Moreover, phonon dispersion analysis shows an avoided‐crossing behavior in SrSnSe 2 , attributed to the expression of the 5s 2 lone pair. Notably, four‐phonon scattering in SrSnSe 2 lacking phonon bandgap is particularly pronounced compared to SnSe, which is ascribed to the Jahn‐Teller‐like distortion of the SrSe6 octahedron. Combining multiple scattering mechanisms, the optimal thermoelectric performance is evaluated, achieving a ZT of ≈2.57 at 900 K for n ‐type and ≈2.47 at 900 K for p ‐type SrSnSe₂ under different carrier concentrations and temperatures. The results discover the underlying unusual transport mechanisms in SrSnSe 2 thermoelectrics, providing a theoretical case for manipulating anisotropic Rashba band splitting and phonon scattering selection rule. Materials science ; Condensed matter physics ; Phonon ; Tin ; Thermoelectric materials ; Anisotropy ; Scattering ; Spin (aerodynamics) ; Strontium ; Phonon scattering ; Physics ; Optics ; Nuclear physics ; Metallurgy Advanced Thermoelectric Materials and Devices ; Topological Materials and Phenomena ; Heusler alloys: electronic and magnetic properties
Authors: Yanqiu Zhu | Shuxiang Fan | Min Zuo | Baohua Zhang | Qingzhen Zhu | Jianlei Kong
Source: Foods (article, 2024-05-17)
Field: Chemistry — Analytical Chemistry

Discrimination of New and Aged Seeds Based on On-Line Near-Infrared Spectroscopy Technology Combined with Machine Learning The harvest year of maize seeds has a significant impact on seed vitality and maize yield. Therefore, it is vital to identify new seeds. In this study, an on-line near-infrared (NIR) spectra collection device (899-1715 nm) was designed and employed for distinguishing maize seeds harvested in different years. Compared with least squares support vector machine (LS-SVM), k-nearest neighbor (KNN), and extreme learning machine (ELM), the partial least squares discriminant analysis (PLS-DA) model has the optimal recognition performance for maize seed harvest years. Six different preprocessing methods, including Savitzky-Golay smoothing (SGS), standard normal variate transformation (SNV), multiplicative scatter correction (MSC), Savitzky-Golay 1 derivative (SG-D1), Savitzky-Golay 2 derivative (SG-D2), and normalization (Norm), were used to improve the quality of the spectra. The Monte Carlo cross-validation uninformative variable elimination (MC-UVE), competitive adaptive reweighted sampling (CARS), bootstrapping soft shrinkage (BOSS), successive projections algorithm (SPA), and their combinations were used to obtain effective wavelengths and decrease spectral dimensionality. The MC-UVE-BOSS-PLS-DA model achieved the classification with an accuracy of 88.75% using 93 features based on Norm preprocessed spectral data. This study showed that the self-designed NIR collection system could be used to identify the harvested years of maize seed. Binary Golay code ; Artificial intelligence ; Mathematics ; Linear discriminant analysis ; Partial least squares regression ; Pattern recognition (psychology) ; Extreme learning machine ; Normalization (sociology) ; Algorithm ; Support vector machine ; Smoothing ; Computer science ; Statistics ; Artificial neural network Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Smart Agriculture and AI
Authors: Lara van Tetering | Sylvia Spies | Quirine D. K. Wildeman | Kas J. Houthuijs | Rianne E. van Outersterp | Jonathan Martens | Ron A. Wevers | David S. Wishart | Giel Berden | Jos Oomens
Source: Communications Chemistry (article, 2024-02-14)
Field: Chemistry — Spectroscopy

A spectroscopic test suggests that fragment ion structure annotations in MS/MS libraries are frequently incorrect Modern untargeted mass spectrometry (MS) analyses quickly detect and resolve thousands of molecular compounds. Although features are readily annotated with a molecular formula in high-resolution small-molecule MS applications, the large majority of them remains unidentified in terms of their full molecular structure. Collision-induced dissociation tandem mass spectrometry (CID-MS<sup>2</sup>) provides a diagnostic molecular fingerprint to resolve the molecular structure through a library search. However, for de novo identifications, one must often rely on in silico generated MS<sup>2</sup> spectra as reference. The ability of different in silico algorithms to correctly predict MS<sup>2</sup> spectra and thus to retrieve correct molecular structures is a topic of lively debate, for instance in the CASMI contest. Underlying the predicted MS<sup>2</sup> spectra are the in silico generated product ion structures, which are normally not used in de novo identification, but which can serve to critically assess the fragmentation algorithms. Here we evaluate in silico generated MS<sup>n</sup> product ion structures by comparison with structures established experimentally by infrared ion spectroscopy (IRIS). For a set of three dozen product ion structures from five precursor molecules, we find that virtually all fragment ion structure annotations in three major in silico MS<sup>2</sup> libraries (HMDB, METLIN, mzCloud) are incorrect and caution the reader against their use for structure annotation of MS/MS ions. In silico ; Fragmentation (computing) ; Chemistry ; Tandem mass spectrometry ; Mass spectrometry ; Collision-induced dissociation ; Ion-mobility spectrometry ; Ion ; Computational biology ; Computer science ; Chromatography ; Biology Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Analytical Chemistry and Chromatography
Authors: Claudio Bonizzoni | Alberto Ghirri | Fabio Santanni | M. Affronte
Source: npj Quantum Information (article, 2024-04-23)
Field: Materials Science — Materials Chemistry

Quantum sensing of magnetic fields with molecular spins Abstract Spins are prototypical systems with the potential to probe magnetic fields down to the atomic scale limit. Exploiting their quantum nature through appropriate sensing protocols allows to enlarge their applicability to fields not always accessible by classical sensors. Here we first show that quantum sensing protocols for AC magnetic fields can be implemented with molecular spin ensembles embedded into hybrid quantum circuits. We then show that, using only echo detection at microwave frequency and no optical readout, Dynamical Decoupling protocols synchronized with the AC magnetic fields can enhance sensitivity up to S ≈ 10 −10 − 10 −9 T Hz −1/2 with a low (4-5) number of applied pulses. These results paves the way for the development of strategies to exploit molecular spins as quantum sensors. Spins ; Quantum computer ; Physics ; Quantum ; Magnetic field ; Computer science ; Quantum mechanics ; Theoretical physics ; Condensed matter physics Diamond and Carbon-based Materials Research ; Carbon Nanotubes in Composites ; Atomic and Subatomic Physics Research
Authors: Sara Rojas-Vázquez | Beatriz Lozano‐Torres | Alba García‐Fernández | Irene Galiana | Ana Pérez‐Villalba | Pablo Martí‐Rodrigo | M. José Palop | Marcia Domínguez | Mar Orzáez | Félix Sancenón | Juan F. Blandez | Isabel Fariñas | Ramón Martínez‐Máñez
Source: Nature Communications (article, 2024-01-26)
Field: Materials Science — Materials Chemistry

A renal clearable fluorogenic probe for in vivo β-galactosidase activity detection during aging and senolysis Accumulation of senescent cells with age leads to tissue dysfunction and related diseases. Their detection in vivo still constitutes a challenge in aging research. We describe the generation of a fluorogenic probe (sulfonic-Cy7Gal) based on a galactose derivative, to serve as substrate for β-galactosidase, conjugated to a Cy7 fluorophore modified with sulfonic groups to enhance its ability to diffuse. When administered to male or female mice, β-galactosidase cleaves the O-glycosidic bond, releasing the fluorophore that is ultimately excreted by the kidneys and can be measured in urine. The intensity of the recovered fluorophore reliably reflects an experimentally controlled load of cellular senescence and correlates with age-associated anxiety during aging and senolytic treatment. Interestingly, our findings with the probe indicate that the effects of senolysis are temporary if the treatment is discontinued. Our strategy may serve as a basis for developing fluorogenic platforms designed for easy longitudinal monitoring of enzymatic activities in biofluids. Fluorophore ; In vivo ; Glycosidic bond ; Fluorescence ; Substrate (aquarium) ; Chemistry ; Enzyme ; Biochemistry ; Biophysics ; Cell biology ; Biology Advanced Nanomaterials in Catalysis ; Photoreceptor and optogenetics research ; Nanoplatforms for cancer theranostics