jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Bingqing Lu | Jiaqi Wang | Paul T.J. Scheepers | A. Jan Hendriks | Tom M. Nolte
Source: Scientific Reports (article, 2022-10-24)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Generic prediction of exocytosis rate constants by size-based surface energies of nanoparticles and cells Nanotechnology brings benefits in fields such as biomedicine but nanoparticles (NPs) may also have adverse health effects. The effects of surface-modified NPs at the cellular level have major implications for both medicine and toxicology. Semi-empirical and mechanism-based models aid to understand the cellular transport of various NPs and its implications for quantitatively biological exposure while avoiding large-scale experiments. We hypothesized relationships between NPs-cellular elimination, surface functionality and elimination pathways by cells. Surface free energy components were used to characterize the transport of NPs onto membranes and with lipid vesicles, covering both influences by size and hydrophobicity of NPs. The model was built based on properties of neutral NPs and cells, defining Van de Waals forces, electrostatic forces and Lewis acid-base (polar) interactions between NPs and vesicles as well as between vesicles and cell membranes. We yielded a generic model for estimating exocytosis rate constants of various neutral NPs by cells based on the vesicle-transported exocytosis pathways. Our results indicate that most models are well fitted (R<sup>2</sup> ranging from 0.61 to 0.98) and may provide good predictions of exocytosis rate constants for NPs with differing surface functionalities (prediction errors are within 2 times for macrophages). Exocytosis rates differ between cancerous cells with metastatic potential and non-cancerous cells. Our model provides a reference for cellular elimination of NPs, and intends for medical applications and risk assessment. Exocytosis ; Vesicle ; Nanoparticle ; Chemistry ; Membrane ; Biophysics ; Nanotechnology ; van der Waals force ; Reaction rate constant ; Materials science ; Kinetics ; Molecule ; Biochemistry ; Biology ; Physics Gold and Silver Nanoparticles Synthesis and Applications ; Lipid Membrane Structure and Behavior ; Nanoparticle-Based Drug Delivery
Authors: Thomas Lopeman | Hossein Anbari | Gary A. Leeke | Joseph Wood
Source: Energy & Fuels (article, 2022-12-22)
Field: Chemistry — Analytical Chemistry

Numerical Modeling of Toe-to-Heel Air Injection and Its Catalytic Variant (CAPRI) under Varying Steam Conditions There are huge reserves of heavy oil (HO) throughout the world that can be energy-intensive to recover. Improving the energy efficiency of the recovery process and developing novel methods of cleaner recovery will be essential for the transition from traditional fossil fuel usage to net-zero. In situ combustion (ISC) is a less used technique, with toe-to-heel air injection (THAI) and catalytic processing in situ (CAPRI) being specialized novel versions of traditional ISC. They utilize a horizontal producing well and in the case of CAPRI, a catalyst. This paper aims to investigate the impact that injected steam has on both the THAI and CAPRI processes for the purpose of in situ HO upgrading and will help to bridge the gap between the extant laboratory research and the unknown commercial potential. This study also presents a novel method for modeling the THAI-CAPRI method using CMG STARS, proposing an in situ hydrogen production reaction scheme. THAI and CAPRI experimental-scale models were run under three conditions: dry, pre-steam, and constant steam. Starting from a reservoir American Petroleum Institute (API) of 10.5°, THAI reached an average API of ∼16 points, showing no increase in the API output with the use of steam injection. A decreased API output by ∼0.7 points during constant steam injection was achieved due to a high-temperature oxidation-dominant environment. This decreases the reactant availability for thermal cracking. The CAPRI dry run reached an API of 20.40 points and achieved an increased API output for both pre-steaming (∼21.17 points) and constant steaming (∼22.13 points). The mechanics for this increased upgrading were discussed, and catalytic upgrading, as opposed to thermal cracking, was shown to be the reason for the increased upgrading. Both processes produce similar cumulative oil (∼3150 cm<sup>3</sup>) during dry and pre-steamed runs, only increasing to ∼3300 cm<sup>3</sup> with the constant steam injection during THAI and 3500 cm<sup>3</sup> for CAPRI. Environmental science ; Steam injection ; Petroleum engineering ; Cracking ; Process engineering ; Computer science ; Materials science ; Geology ; Engineering Petroleum Processing and Analysis ; Enhanced Oil Recovery Techniques ; Hydrocarbon exploration and reservoir analysis
Authors: José Francisco Algorri | Pablo Roldán-Varona | María Gabriela Fernández-Manteca | José Miguel López Higuera | Luis Rodŕıguez-Cobo | Adolfo Cobo
Source: Biosensors (review, 2022-11-16)
Field: Materials Science — Biomaterials

Photonic Microfluidic Technologies for Phytoplankton Research Phytoplankton is a crucial component for the correct functioning of different ecosystems, climate regulation and carbon reduction. Being at least a quarter of the biomass of the world's vegetation, they produce approximately 50% of atmospheric O2 and remove nearly a third of the anthropogenic carbon released into the atmosphere through photosynthesis. In addition, they support directly or indirectly all the animals of the ocean and freshwater ecosystems, being the base of the food web. The importance of their measurement and identification has increased in the last years, becoming an essential consideration for marine management. The gold standard process used to identify and quantify phytoplankton is manual sample collection and microscopy-based identification, which is a tedious and time-consuming task and requires highly trained professionals. Microfluidic Lab-on-a-Chip technology represents a potential technical solution for environmental monitoring, for example, in situ quantifying toxic phytoplankton. Its main advantages are miniaturisation, portability, reduced reagent/sample consumption and cost reduction. In particular, photonic microfluidic chips that rely on optical sensing have emerged as powerful tools that can be used to identify and analyse phytoplankton with high specificity, sensitivity and throughput. In this review, we focus on recent advances in photonic microfluidic technologies for phytoplankton research. Different optical properties of phytoplankton, fabrication and sensing technologies will be reviewed. To conclude, current challenges and possible future directions will be discussed. Phytoplankton ; Environmental science ; Software portability ; Biomass (ecology) ; Microfluidics ; Computer science ; Nanotechnology ; Ecology ; Materials science ; Biology Diatoms and Algae Research ; Slime Mold and Myxomycetes Research ; Algal biology and biofuel production
Authors: Julian Klein | Benjamin Pingault | Matthias Florian | Marie-Christin Heißenbüttel | Alexander Steinhoff | Zhigang Song | Kierstin Torres | Florian Dirnberger | Jonathan B. Curtis | Mads Weile | Aubrey Penn | Thorsten Deilmann | Rami Dana | Rezlind Bushati | Jiamin Quan | Jan Luxa | Zdeněk Sofer | Andrea Alù | Vinod M. Menon | Ursula Wurstbauer | Michael Rohlfing | Prineha Narang | Marko Lončar | Frances M. Ross
Source: arXiv (Cornell University) (preprint, 2022-05-26)
Field: Materials Science — Materials Chemistry

The bulk van der Waals layered magnet CrSBr is a quasi-1D material Correlated quantum phenomena in one-dimensional (1D) systems that exhibit competing electronic and magnetic order are of strong interest for studying fundamental interactions and excitations, such as Tomonaga-Luttinger liquids and topological orders and defects with properties completely different from the quasiparticles expected in their higher-dimensional counterparts. However, clean 1D electronic systems are difficult to realize experimentally, particularly magnetically ordered systems. Here, we show that the van der Waals layered magnetic semiconductor CrSBr behaves like a quasi-1D material embedded in a magnetically ordered environment. The strong 1D electronic character originates from the Cr-S chains and the combination of weak interlayer hybridization and anisotropy in effective mass and dielectric screening with an effective electron mass ratio of $m^e_X/m^e_Y \sim 50$. This extreme anisotropy experimentally manifests in strong electron-phonon and exciton-phonon interactions, a Peierls-like structural instability and a Fano resonance from a van Hove singularity of similar strength of metallic carbon nanotubes. Moreover, due to the reduced dimensionality and interlayer coupling, CrSBr hosts spectrally narrow (1 meV) excitons of high binding energy and oscillator strength that inherit the 1D character. Overall, CrSBr is best understood as a stack of weakly hybridized monolayers and appears to be an experimentally attractive candidate for the study of exotic exciton and 1D correlated many-body physics in the presence of magnetic order. Condensed matter physics ; Van Hove singularity ; van der Waals force ; Quasiparticle ; Exciton ; Phonon ; Effective mass (spring–mass system) ; Physics ; Anisotropy ; Electron ; Materials science ; Quantum mechanics ; Superconductivity ; Fermi level 2D Materials and Applications ; Iron-based superconductors research ; Molecular Junctions and Nanostructures
Authors: Wenhua Li | Wenchao Tian
Source: Nanomaterials (article, 2022-05-18)
Field: Materials Science — Materials Chemistry

Molecular Dynamics Analysis of Graphene Nanoelectromechanical Resonators Based on Vacancy Defects Due to the limitation of graphene processing technology, the prepared graphene inevitably contains various defects. The defects will have a particular influence on the macroscopic characteristics of the graphene. In this paper, the defect-based graphene nanoresonators are studied. In this study, the resonant properties of graphene were investigated via molecular dynamic simulations. The effect of vacancy defects and hole defects at different positions, numbers, and concentrations on the resonance frequency of graphene nanoribbons was studied. The results indicated that single monatomic vacancy has no effect on graphene resonant frequency, and the concentration of the resonant frequency of graphene decreases almost linearly with the increase of single-atom vacancy concentration. When the vacancy concentration is 5%, the resonance frequency is reduced by 12.77% compared to the perfect graphene. Holes on the graphene cause the resonance frequency to decrease. As the circular hole defect is closer to the center of the graphene nanoribbon, not only does its resonant frequency increase, but the tuning range is also expanded accordingly. Under the external force of 10.715 nN, the resonant frequency of graphene reaches 429.57 GHz when the circular hole is located at the center of the graphene nanoribbon, which is 40 GHz lower than that of single vacancy defect graphene. When the circular hole is close to the fixed end of graphene, the resonant frequency is 379.62 GHz, which is 90 GHz lower than that of single vacancy graphene. When the hole defect is at the center of nanoribbon, the frequency tunable range of graphene reaches 120 GHz. The tunable frequency range of graphene is 100.12 GHz when the hole defect is near the fixed ends of the graphene nanoribbon. This work is of great significance for design and performance optimization of graphene-based nanoelectro-mechanical system (NEMS) resonators. Graphene ; Vacancy defect ; Materials science ; Resonance (particle physics) ; Resonator ; Graphene nanoribbons ; Molecular dynamics ; Condensed matter physics ; Monatomic ion ; Atom (system on chip) ; Optoelectronics ; Nanotechnology ; Atomic physics ; Physics ; Chemistry ; Computational chemistry Graphene research and applications ; Carbon Nanotubes in Composites ; Mechanical and Optical Resonators
Authors: Federica Agosta | Glen E. Kellogg | Pietro Cozzini
Source: Journal of Computer-Aided Molecular Design (article, 2022-10-31)
Field: Chemistry — Physical and Theoretical Chemistry

From oncoproteins to spike proteins: the evaluation of intramolecular stability using hydropathic force field Evaluation of the intramolecular stability of proteins plays a key role in the comprehension of their biological behavior and mechanism of action. Small structural alterations such as mutations induced by single nucleotide polymorphism can impact biological activity and pharmacological modulation. Covid-19 mutations, that affect viral replication and the susceptibility to antibody neutralization, and the action of antiviral drugs, are just one example. In this work, the intramolecular stability of mutated proteins, like Spike glycoprotein and its complexes with the human target, is evaluated through hydropathic intramolecular energy scoring originally conceived by Abraham and Kellogg based on the "Extension of the fragment method to calculate amino acid zwitterion and side-chain partition coefficients" by Abraham and Leo in Proteins: Struct. Funct. Genet. 1987, 2:130 - 52. HINT is proposed as a fast and reliable tool for the stability evaluation of any mutated system. This work has been written in honor of Prof. Donald J. Abraham (1936-2021). Intramolecular force ; Glycoprotein ; Mutation ; Chemistry ; Computational biology ; Stereochemistry ; Biology ; Biochemistry ; Gene thermodynamics and calorimetric analyses ; Protein Structure and Dynamics ; Computational Drug Discovery Methods
Authors: Wenrong Chen | Elijah N. McCool | Liangliang Sun | Yong Zang | Xia Ning | Xiaowen Liu
Source: Journal of Proteome Research (article, 2022-05-26)
Field: Chemistry — Spectroscopy

Evaluation of Machine Learning Models for Proteoform Retention and Migration Time Prediction in Top-Down Mass Spectrometry Reversed-phase liquid chromatography (RPLC) and capillary zone electrophoresis (CZE) are two primary proteoform separation methods in mass spectrometry (MS)-based top-down proteomics. Proteoform retention time (RT) prediction in RPLC and migration time (MT) prediction in CZE provide additional information for accurate proteoform identification and quantification. While existing methods are mainly focused on peptide RT and MT prediction in bottom-up MS, there is still a lack of methods for proteoform RT and MT prediction in top-down MS. We systematically evaluated eight machine learning models and a transfer learning method for proteoform RT prediction and five models and the transfer learning method for proteoform MT prediction. Experimental results showed that a gated recurrent unit (GRU)-based model with transfer learning achieved a high accuracy (<i>R</i> = 0.978) for proteoform RT prediction and that the GRU-based model and a fully connected neural network model obtained a high accuracy of <i>R</i> = 0.982 and 0.981 for proteoform MT prediction, respectively. Proteomics ; Chemistry ; Artificial intelligence ; Machine learning ; Computer science ; Biochemistry Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Alessio Cesaretti | Letizia Mencaroni | Carmela Bonaccorso | Valentina Botti | Eleonora Calzoni | Benedetta Carlotti | Cosimo G. Fortuna | Nicolò Montegiove | Anna Spalletti | Fausto Elisei
Source: Molecules (article, 2022-06-09)
Field: Chemistry — Organic Chemistry

Amphiphilicity-Controlled Localization of Red Emitting Bicationic Fluorophores in Tumor Cells Acting as Bio-Probes and Anticancer Drugs Small organic molecules arouse lively interest for their plethora of possible biological applications, such as anticancer therapy, for their ability to interact with nucleic acids, or bioimaging, thanks to their fluorescence emission. Here, a panchromatic series of styryl-azinium bicationic dyes, which have already proved to exhibit high water-solubility and significant red fluorescence in water, were investigated through spectrofluorimetric titrations to assess the extent of their association constants with DNA and RNA. Femtosecond-resolved transient absorption spectroscopy was also employed to characterize the changes in the photophysical properties of these fluorophores upon interaction with their biological targets. Finally, in vitro experiments conducted on tumor cell lines revealed that some of the bicationic fluorophores had a peculiar localization within cell nuclei exerting important antiproliferative effects, others were instead found to localize in the cytoplasm without leading to cell death, being useful to mark specific organelles in light of live cell bioimaging. Interestingly, this molecule-dependent behavior matched the different amphiphilicity featured by these bioactive compounds, which are thus expected to be caught in a tug-of-war between lipophilicity, ensured by the presence of aromatic rings and needed to pass cell membranes, and hydrophilicity, granted by charged groups and necessary for stability in aqueous media. Lipophilicity ; Fluorescence ; Chemistry ; Biophysics ; Nucleic acid ; Cytoplasm ; Organelle ; DNA ; Nanomedicine ; Molecule ; Membrane ; Combinatorial chemistry ; Photochemistry ; Nanotechnology ; Biochemistry ; Organic chemistry ; Materials science ; Nanoparticle ; Biology Click Chemistry and Applications ; Luminescence and Fluorescent Materials ; Molecular Sensors and Ion Detection
Authors: Weihan Li | Ma Qian | Yunfeng Zhang | Xianning Wu | Wei Wang | Shizhao Gao | Tianshuo Qiu | Tonghao Liu | Qiang Xiao | Jiaxuan Wei | Tingting Gu | Zhize Zhou | Fashuai Li | Qiang Cheng | Lianlin Li | Wenxuan Tang | Tie Jun Cui
Source: Research Square (preprint, 2022-06-14)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Intelligent metasurface system for automatic tracking of moving targets and wireless communications based on computer vision Tracking (education) ; Wireless ; Computer science ; Computer vision ; Tracking system ; Artificial intelligence ; Telecommunications ; Psychology Metamaterials and Metasurfaces Applications ; Antenna Design and Analysis ; Advanced Wireless Communication Technologies
Authors: Charalampos Livas | Emmanuel Tylianakis | George E. Froudakis
Source: Chemistry (article, 2022-06-16)
Field: Chemistry — Inorganic Chemistry

Enhancing of CO Uptake in Metal-Organic Frameworks by Linker Functionalization: A Multi-Scale Theoretical Study In the present work, the interaction strength of Carbon Monoxide (CO) with a set of forty-two, strategically selected, functionalized benzenes was calculated. Our ab initio calculations at the MP2/6-311++G** level of theory reveal that phenyl hydrogen sulfate (-OSO3H) showed the highest interaction with CO (−19.5 kJ/mol), which was approximately three times stronger compared with the unfunctionalized benzene (−5.3 kJ/mol). Moreover, the three top-performing functional groups (-OSO3H, -OPO3H2, -SO3H) were selected to modify the organic linker of IRMOF-8 and test their ability to capture CO at 298 K for a wide pressure range. Our Grand Canonical Monte Carlo (GCMC) simulations showed a significant increase in the CO uptake in the functionalized MOFs compared with the parent IRMOF-8. It is distinctive that for the volumetric uptake, a 60× increase was observed at 1 bar and 2× was observed at 100 bar. The proposed functionalization strategy can be applied for improving the CO uptake performance not only in MOFs but also in various other porous materials. Linker ; Metal-organic framework ; Benzene ; Carbon monoxide ; Surface modification ; Bar (unit) ; Density functional theory ; Hydrogen ; Ab initio ; Porosity ; Chemistry ; Carbon fibers ; Hydrogen bond ; Computational chemistry ; Materials science ; Physical chemistry ; Molecule ; Organic chemistry ; Catalysis ; Computer science ; Physics ; Composite material Metal-Organic Frameworks: Synthesis and Applications ; Phase Equilibria and Thermodynamics ; Carbon Dioxide Capture Technologies
Authors: Simone Monaco | Daniele Apiletti | Giovanni Malnati
Source: Electronics (article, 2022-09-09)
Field: Materials Science — Materials Chemistry

Theory-Guided Deep Learning Algorithms: An Experimental Evaluation The use of theory-based knowledge in machine learning models has a major impact on many engineering and physics problems. The growth of deep learning algorithms is closely related to an increasing demand for data that is not acceptable or available in many use cases. In this context, the incorporation of physical knowledge or a priori constraints has proven beneficial in many tasks. On the other hand, this collection of approaches is context-specific, and it is difficult to generalize them to new problems. In this paper, we experimentally compare some of the most commonly used theory-injection strategies to perform a systematic analysis of their advantages. Selected state-of-the-art algorithms were reproduced for different use cases to evaluate their effectiveness with smaller training data and to discuss how the underlined strategies can fit into new application contexts. Computer science ; Machine learning ; Context (archaeology) ; Artificial intelligence ; A priori and a posteriori ; Algorithm ; Deep learning ; Data science Machine Learning in Materials Science ; Machine Learning and Data Classification ; Topic Modeling
Authors: Yufei Tu | Qingquan Liu | Lipeng Hou | Puyuan Shi | Chaobin Jia | Jingjuan Su | Jiawen Zhang | Xiuyun Zhang | Bing Wang
Source: Frontiers in Physics (article, 2022-11-11)
Field: Materials Science — Materials Chemistry

Two-dimensional Cr-based ferromagnetic semiconductor: Theoretical simulations and design Two-dimensional (2D) material is the promising for next-generation information technology. The recently discovered intrinsic magnetic crystals have simulated a renaissance in 2D spintronics, which provides an ideal platform for exploring novel physical phenomena. However, current experimental trial-and-error methods in discovering new spintronic material are still very expensive and challenging. In contrast, based on well-developed first-principles calculations, computationally designing the spintronic materials provides a more efficient way for exploring new ferromagnetic (FM) materials and understanding the nature of magnetic properties. Several predictions, such as CrI 3 monolayer, CrGeTe 3 bilayer, CrSBr monolayer, FeCl 2 monolayer, and Fe 3 GeTe 2 monolayer have been confirmed by experiments, showing the great performance of computational approaches. This minireview article attempts to give a brief of discovering intrinsic 2D spintronics from theoretical aspect, and in particular, we emphasize roles played by calculation based on first-principles methods in designing 2D FM materials and devices. The current challenges and proposals on future developments of 2D spintronics are also discussed. Spintronics ; Monolayer ; Ferromagnetism ; Nanotechnology ; Materials science ; Bilayer ; Computer science ; Engineering physics ; Condensed matter physics ; Physics ; Chemistry 2D Materials and Applications ; MXene and MAX Phase Materials ; Heusler alloys: electronic and magnetic properties