jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Elodia Rojas-Lima | Manolo Ortega-Romero | Octavio Gamaliel Aztatzi-Aguilar | Juan Carlos Rubio-Gutiérrez | Juana Narváez-Morales | Mariela Esparza-García | Pablo Méndez‐Hernández | Mara Medeiros-Domingo | Olivier Barbier
Source: Pediatric Nephrology (article, 2024-12-07)
Field: Chemistry — Inorganic Chemistry

Vanadium exposure and kidney markers in a pediatric population: a cross-sectional study Our study reports the effect of V on kidney markers in a healthy pediatric population. It could be related to tubulointerstitial lesions and function abnormalities. Medicine ; Renal function ; Internal medicine ; Kidney disease ; Population ; Creatinine ; Urinary system ; Nephrology ; Gastroenterology ; Cross-sectional study ; Lipocalin ; Confounding ; Urine ; Nephrotoxicity ; Cystatin C ; Kidney ; Pathology ; Environmental health Vanadium and Halogenation Chemistry ; Acute Kidney Injury Research ; Air Quality and Health Impacts
Authors: Ying Liu | Yin Wu | Yang Ji | Botao Zhao | Ziyi Jin | Shenghong Ju | Ying‐Hua Chu | Patrick Liebig | He Wang | Cong Li | Xiao‐Yong Zhang
Source: Journal of Magnetic Resonance Imaging (article, 2024-01-18)
Field: Materials Science — Materials Chemistry

<scp>pH</scp> Mapping of Gliomas Using Quantitative Chemical Exchange Saturation Transfer <scp>MRI</scp>: Quasi‐Steady‐State, Spillover‐, and <scp>MT</scp>‐Corrected Omega Plot Analysis NA TECHNICAL EFFICACY: Stage 1. Magnetization transfer ; Glioma ; Chemistry ; Nuclear magnetic resonance ; Analytical Chemistry (journal) ; Nuclear medicine ; Magnetic resonance imaging ; Medicine ; Chromatography ; Cancer research ; Physics Lanthanide and Transition Metal Complexes ; Magnetism in coordination complexes ; Radioactive element chemistry and processing
Authors: Dongyoon Shin | Yeongshin Kim | Junho Park | Youngsoo Kim
Source: Biomedical Journal (review, 2024-06-18)
Field: Chemistry — Spectroscopy

High-throughput proteomics-guided biomarker discovery of hepatocellular carcinoma Liver cancer stands as the fifth leading cause of cancer-related deaths globally. Hepatocellular carcinoma (HCC) comprises approximately 85%-90% of all primary liver malignancies. However, only 20-30% of HCC patients qualify for curative therapy, primarily due to the absence of reliable tools for early detection and prognosis of HCC. This underscores the critical need for molecular biomarkers for HCC management. Since proteins reflect disease status directly, proteomics has been utilized in biomarker developments for HCC. In particular, proteomics coupled with liquid chromatography-mass spectrometer (LC-MS) methods facilitate the process of discovering biomarker candidates for diagnosis, prognosis, and therapeutic strategies. In this work, we investigated LC-MS-based proteomics methods through recent reference reviews, with a particular focus on sample preparation and LC-MS methods appropriate for the discovery of HCC biomarkers and their clinical applications. We classified proteomics studies of HCC according to sample types, and we examined the coverage of protein biomarker candidates based on LC-MS methods in relation to study scales and goals. Comprehensively, we proposed protein biomarker candidates categorized by sample types and biomarker types for appropriate clinical use. In this review, we summarized recent LC-MS-based proteomics studies on HCC and proposed potential protein biomarkers. Our findings are expected to expand the understanding of HCC pathogenesis and enhance the efficiency of HCC diagnosis and prognosis, thereby contributing to improved patient outcomes. Biomarker ; Proteomics ; Biomarker discovery ; Hepatocellular carcinoma ; Medicine ; Quantitative proteomics ; Cancer ; Bioinformatics ; Oncology ; Computational biology ; Internal medicine ; Biology Advanced Proteomics Techniques and Applications ; Endoplasmic Reticulum Stress and Disease ; Metabolomics and Mass Spectrometry Studies
Authors: Andreas K. Lianos | Tianyang Zhou | S.R. Peterson | Pavan V. Kolluru | Dimitris C. Lagoudas | Satish Bukkapatnam
Source: Journal of Manufacturing Processes (article, 2024-04-20)
Field: Materials Science — Polymers and Plastics

Towards spatial property control of the glass transition temperature and microstructure of 3d printed shape memory polymers via set-point tuning of the extrusion temperature and extraction of the underlying physical model with gaussian process regression Materials science ; Differential scanning calorimetry ; Microstructure ; Glass transition ; Crystallinity ; Shape-memory polymer ; Polymer ; Composite material ; Extrusion ; Shape-memory alloy ; Thermodynamics Polymer composites and self-healing ; Advanced Memory and Neural Computing ; Advanced Polymer Synthesis and Characterization
Authors: Zheng Li | Meiting Guo | Chen Wang | Idris Temitope Bello | Na Yu | Xi Chen | Minfang Han | Jie Yu | Meng Ni
Source: International Journal of Hydrogen Energy (article, 2024-03-01)
Field: Materials Science — Materials Chemistry

Thermo-chemo-mechanical analysis of protonic ceramic electrolysis cell: A statistically-designed numerical study Multiphysics ; Thermal expansion ; Electrolysis ; Electrolyte ; Materials science ; Porosity ; Cathode ; Work (physics) ; Ceramic ; Stress (linguistics) ; Electrolytic cell ; Mechanical load ; High-temperature electrolysis ; Composite material ; Mechanical engineering ; Finite element method ; Thermodynamics ; Chemistry ; Physics ; Electrode ; Engineering Advancements in Solid Oxide Fuel Cells ; Fuel Cells and Related Materials ; Thermal Expansion and Ionic Conductivity
Authors: Yu Zhou | Enrique R. Batista | Ping Yang | Danny Pérez
Source: Journal of Chemical Theory and Computation (article, 2024-03-12)
Field: Materials Science — Materials Chemistry

Acceleration of Solvation Free Energy Calculation via Thermodynamic Integration Coupled with Gaussian Process Regression and Improved Gelman–Rubin Convergence Diagnostics The determination of the solvation free energy of ions and molecules holds profound importance across a spectrum of applications spanning chemistry, biology, energy storage, and the environment. Molecular dynamics simulations are powerful tools for computing this critical parameter. Nevertheless, the accurate and efficient calculation of the solvation free energy becomes a formidable endeavor when dealing with complex systems characterized by potent Coulombic interactions and sluggish ion dynamics and, consequently, slow transition across various metastable states. In the present study, we expose limitations stemming from the conventional calculation of the statistical inefficiency <i>g</i> in the thermodynamic integration method, a factor that can hinder the determination of convergence of the solvation free energy and its associated uncertainty. Instead, we propose a robust scheme based on Gelman-Rubin convergence diagnostics. We leverage this improved estimation of uncertainties to introduce an innovative accelerated thermodynamic integration method based on the Gaussian Process regression. This methodology is applied to the calculation of the solvation free energy of trivalent rare-earth elements immersed in ionic liquids, a scenario in which the aforementioned challenges render standard approaches ineffective. The proposed method proves to be effective in computing solvation free energy in situations where traditional thermodynamic integration methods fall short. Solvation ; Thermodynamic integration ; Statistical physics ; Computer science ; Convergence (economics) ; Molecular dynamics ; Gaussian process ; Energy (signal processing) ; Gaussian ; Chemistry ; Physics ; Ion ; Computational chemistry Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Spectroscopy and Quantum Chemical Studies
Authors: J. H. Lee | Corina Urdaniz | Stefano Reale | Kyungju Noh | D. S. Krylov | Andrin Doll | Luciano Colazzo | Yujeong Bae | Christoph Wolf | Fabio Donati
Source: Physical review. B./Physical review. B (article, 2024-06-20)
Field: Materials Science — Materials Chemistry

Interpreting x-ray absorption spectra of vanadyl phthalocyanines spin qubit candidates using a machine learning assisted approach The magnetic dilution of vanadyl phthalocyanine (VOPc) within the isostructural diamagnetic titanyl phthalocyanine (TiOPc) affords promising molecular spin qubit platforms for solid-state quantum computing. The development of quantitative methods for determining how the interactions with a supporting substrate impact the electronic structure of the system are fundamental to determine their potential integration in physical devices. In this work we propose a combined approach based on x-ray absorption spectroscopy (XAS), atomic multiplet calculations, and density functional theory (DFT) to investigate the $3d$ orbital level structure of VOPc on TiOPc/Ag(100). We characterize VOPc in different molecular environments realized by changing the thickness of the TiOPc interlayer and adsorption configuration on Ag(100). Depending on the molecular film structure, we find characteristic XAS features that we analyze using atomic multiplet calculations. We use a Bayesian optimization algorithm to accelerate the parameter search process in the multiplet calculations and identify the ground state properties, such as the $3d$ orbital occupancy and splitting, as well as intra-atomic interactions. Our analysis indicates that VOPc retains its spin $S=\frac{1}{2}$ character in all configurations. Conversely, the energy separation and sequence of the unoccupied V $3d$ orbitals sensitively depend on the interaction with the surface and TiOPc interlayer. We validate the atomic orbital picture obtained from the multiplet model by comparison with DFT, which further allows us to understand the VOPc electronic properties using a molecular orbital description. Qubit ; Absorption (acoustics) ; Spin (aerodynamics) ; Spectral line ; Materials science ; Analytical Chemistry (journal) ; Physics ; Chemistry ; Molecular physics ; Optics ; Quantum mechanics ; Chromatography ; Quantum Machine Learning in Materials Science ; Catalysis and Oxidation Reactions ; Advanced Electron Microscopy Techniques and Applications
Authors: Maximilian Jaugstetter | Xiao Qi | Emory M. Chan | Miquel Salmerón | Kevin R. Wilson | Slavomír Nemšák | Hendrik Bluhm
Source: ACS Nano (article, 2024-12-19)
Field: Materials Science — Materials Chemistry

Direct Observation of Morphological and Chemical Changes during the Oxidation of Model Inorganic Ligand-Capped Particles Functionalization and volatilization are competing reactions during the oxidation of carbonaceous materials and are important processes in many different areas of science and technology. Here, we present a combined ambient pressure X-ray photoelectron spectroscopy (APXPS) and grazing incidence X-ray scattering (GIXS) investigation of the oxidation of oleic acid ligands surrounding NaYF<sub>4</sub> nanoparticles (NPs) deposited onto SiO<sub><i>x</i></sub>/Si substrates. While APXPS monitors the evolution of the oxidation products, GIXS provides insight into the morphology of the ligands and particles before and after the oxidation. Our investigation shows that the oxidation of the oleic acid ligands proceeds at O<sub>2</sub> partial pressures of below 1 mbar in the presence of X-rays, with the oxidation eventually reaching a steady state in which mainly CH<sub><i>x</i></sub> and -COOH functional groups are observed. The scattering data reveal that the oxidation and volatilization reaction proceeds preferentially on the side of the particle facing the gas phase, leading to the formation of a chemically and morphologically asymmetric ligand layer. This comprehensive picture of the oxidation process could be obtained only by combining the X-ray scattering and APXPS data. The investigation presented here lays the foundation for further studies of the stability of NP layers in the presence of reactive trace gases and ionizing radiation and for other nanoscale systems where chemical and morphological changes happen simultaneously and cannot be understood in isolation. Oxidation state ; X-ray photoelectron spectroscopy ; Volatilisation ; Nanoparticle ; Ligand (biochemistry) ; Chemistry ; Chemical engineering ; Chemical state ; Chemical reaction ; Particle (ecology) ; Chemical stability ; Redox ; Materials science ; Photochemistry ; Inorganic chemistry ; Nanotechnology ; Organic chemistry ; Catalysis Catalytic Processes in Materials Science ; Advanced Photocatalysis Techniques ; Luminescence Properties of Advanced Materials
Authors: Ian C. Chagunda | Peter J. H. Williams | Tiago Fisher | Naomi L. Stock | Daniel G. Beach | Gilian T. Thomas | Jane Zhu | J. Scott McIndoe
Source: European Journal of Inorganic Chemistry (article, 2024-05-02)
Field: Chemistry — Analytical Chemistry

Comparative Assessment of ESI‐MS Softness for Inorganic Complexes: How Soft Is Your ESI‐MS? Abstract Electrospray ionization mass spectrometry (ESI‐MS) is a powerful tool for identifying and characterizing organometallic and coordination compounds. However, detection of fragile structures bound by weaker intermolecular forces can be significantly limited in ESI‐MS owing to the use of relatively harsh instrument conditions and configurations. In this study, a set of tests was developed to assess the softness of ESI‐MS systems. Two variants are presented: positive ion mode, utilizing a mixture of sodium ions and triphenylphosphine oxide producing [Na(OPPh 3 ) n ] + ions ( n =1–4), and negative ion mode utilizing Pd(PPh 3 ) 4 and sulfonated triphenylphosphine producing [Pd(L)(PPh 3 ) n ] − ions ( n =0–2), where softer instrument conditions preserve a higher proportion of the high‐coordinate ions and harsher conditions will result in increased detection of products of ion fragmentation. The results revealed notable variations in instrument softness, which were influenced by a combination of instrument design and experimental parameters. Meticulously optimizing experimental conditions and ESI‐MS parameters is essential to achieving the softest ionization possible, ensuring reliable analysis where applicable. This study offers valuable insight through straightforward tests that can be employed to assess the suitability of an instrument for specific research needs. Chemistry Analytical chemistry methods development ; Advanced Chemical Sensor Technologies ; Mass Spectrometry Techniques and Applications
Authors: Andreas J. Achazi | Xhesilda Fataj | Philip Rohland | Martin D. Hager | Ulrich S. Schubert | Doreen Mollenhauer
Source: Journal of Computational Chemistry (article, 2024-01-23)
Field: Chemistry — Organic Chemistry

Development of a multi‐step screening procedure for redox active molecules in organic radical polymer anodes and as redox flow anolytes Benzo[d]-X-zolyl-pyridinyl (XO, S, NH) radicals represent a promising class of redox-active molecules for organic batteries. We present a multistep screening procedure to identify the most promising radical candidates. Experimental investigations and highly correlated wave function-based calculations are performed to determine benchmark redox potentials. Based on these, the accuracies of different methods (semi-empirical, density functional theory, wave function-based), solvent models, dispersion corrections, and basis sets are evaluated. The developed screening procedure consists of three steps: First, a conformer search is performed with CREST. The molecules are selected based on the redox potentials calculated using GFN2-xTB. Second, HOMO energies calculated with reparametrized B3LYP-D3(BJ) and the def2-SVP basis set are used as selection criteria. The final molecules are selected based on the redox potentials calculated from Gibbs energies using BP86-D3(BJ)/def2-TZVP. With this multistep screening approach, promising molecules can be suggested for synthesis, and structure-property relationships can be derived. Redox ; Molecule ; Chemistry ; Radical ; Basis set ; Density functional theory ; Computational chemistry ; Function (biology) ; Wave function ; Conformational isomerism ; Chemical physics ; Organic chemistry ; Physics ; Atomic physics Free Radicals and Antioxidants ; Photochemistry and Electron Transfer Studies ; Conducting polymers and applications
Authors: Hendra Y. Agustian
Source: Laboratories (article, 2024-06-17)
Field: Chemistry — Physical and Theoretical Chemistry

Methodological Rigor in Laboratory Education Research Despite the growing number of published studies on student learning in the laboratory, there is a critical need to improve methodological rigor. Resonating with discussions on research methods, this paper outlines the importance of theory-informed research questions, the minimization of researcher and participant biases, and the use of triangulation and iteration in data collection to establish rigor. An illustrative case is presented within the context of a large interdisciplinary research project aimed at improving laboratory learning at the university level. The project incorporates two research avenues: one focusing on student and faculty perspectives, and the other on a comprehensive assessment of multidimensional learning in the laboratory. The project employs a mixed methods paradigm and is grounded in a conceptual framework that conceptualizes laboratory work as epistemic practice, requiring a holistic analysis of student learning. The article concludes by discussing the results and implications of the project’s findings, which are synthesized to highlight aspects of establishing methodological rigor. The overarching goal is to develop a comprehensive assessment instrument that captures the complexity and richness of the laboratory learning environment. The findings from this research are expected to contribute to the advancement of laboratory education research by providing a model for methodological rigor that can be applied across various scientific and interdisciplinary contexts. Engineering ethics ; Rigour ; Management science ; Psychology ; Mathematics education ; Epistemology ; Engineering ; Philosophy Various Chemistry Research Topics ; Science Education and Pedagogy ; Innovative Teaching Methods
Authors: Nur Faraliana Japri | Zaiton Abdul Mutalip | S.K. Ghoshal | Wan Hazman Danial | Hong Heng See | Muhammad Zamir Othman
Source: Carbohydrate Polymers (article, 2024-02-20)
Field: Materials Science — Materials Chemistry

On the versatility of graphene-cellulose composites: An overview and bibliometric assessment Scopus ; Sustainability ; Computer science ; Bibliometrics ; Data science ; Nanotechnology ; Business ; Political science ; Materials science ; Library science ; MEDLINE Graphene research and applications ; Graphene and Nanomaterials Applications ; Advanced Photocatalysis Techniques
Authors: Peter Obi | B. Jeevan | Charles Mariasoosai | Ayobami Diyaolu | Senthil Natesan
Source: Journal of Chemical Theory and Computation (article, 2024-06-28)
Field: Chemistry — Spectroscopy

Application of Generative Artificial Intelligence in Predicting Membrane Partitioning of Drugs: Combining Denoising Diffusion Probabilistic Models and MD Simulations Reduces the Computational Cost to One-Third The optimal interaction of drugs with plasma membranes and membranes of subcellular organelles is a prerequisite for desirable pharmacology. Importantly, for drugs targeting the transmembrane lipid-facing sites of integral membrane proteins, the relative affinity of a drug to the bilayer lipids compared to the surrounding aqueous phase affects the partitioning, access, and binding of the drug to the target site. Molecular dynamics (MD) simulations, including enhanced sampling techniques such as steered MD, umbrella sampling (US), and metadynamics, offer valuable insights into the interactions of drugs with the membrane lipids and water in atomistic detail. However, these methods are computationally prohibitive for the high-throughput screening of drug candidates. This study shows that applying denoising diffusion probabilistic models (DDPMs), a generative AI method, to US simulation data reduces the computational cost significantly. Specifically, the models used only partial (one-third) data from the US simulations and reproduced the complete potential of mean force (PMF) profiles for three FDA-approved drugs (β2-adrenergic agonists) and ∼20 biologically relevant chemicals with known experimentally characterized bilayer locations. Intriguingly, the model can predict the solvation-free energies for partitioning and crossing the bilayer, preferred bilayer locations (low-energy well), and orientations of the ligands with high accuracy. The results indicate that DDPMs can be used to characterize the complete membrane partitioning profile of drug molecules using fewer umbrella sampling simulations at select positions along the bilayer normal (<i>z</i>-axis), irrespective of their amphiphilic-lipophilic-cephalophilic characteristics. Computer science ; Artificial intelligence ; Probabilistic logic ; Machine learning ; Generative grammar ; Diffusion Analytical Chemistry and Chromatography ; Drug Solubulity and Delivery Systems ; Protein purification and stability
Authors: Maxim K. Rabchinskii | K. A. Shiyanova | Maria Brzhezinskaya | M. V. Gudkov | Svyatoslav D. Saveliev | Dina Yu. Stolyarova | Mikhail Torkunov | Ratibor G. Chumakov | A. Yu. Vdovichenko | Polina D. Cherviakova | N. I. Novosadov | Diana Z. Nguen | N. G. Ryvkina | A. V. Shvidchenko | Nikita D. Prasolov | В. П. Мельников
Source: Nanomaterials (article, 2024-10-16)
Field: Materials Science — Materials Chemistry

Chemistry of Reduced Graphene Oxide: Implications for the Electrophysical Properties of Segregated Graphene–Polymer Composites Conductive polymer composites (CPCs) with nanocarbon fillers are at the high end of modern materials science, advancing current electronic applications. Herein, we establish the interplay between the chemistry and electrophysical properties of reduced graphene oxide (rGO), separately and as a filler for CPCs with the segregated structure conferred by the chemical composition of the initial graphene oxide (GO). A set of experimental methods, namely X-ray photoelectron spectroscopy (XPS), ultraviolet-visible spectroscopy, van der Paw and temperature-dependent sheet resistance measurements, along with dielectric spectroscopy, are employed to thoroughly examine the derived materials. The alterations in the composition of oxygen groups along with their beneficial effect on nitrogen doping upon GO reduction by hydrazine are tracked with the help of XPS. The slight defectiveness of the graphene network is found to boost the conductivity of the material due to facilitating the impact of the nitrogen lone-pair electrons in charge transport. In turn, a sharp drop in material conductivity is indicated upon further disruption of the π-conjugated network, predominantly governing the charge transport. Particularly, the transition from the Mott variable hopping transport mechanism to the Efros-Shklovsky one is signified. Finally, the impact of rGO chemistry and physics on the electrophysical properties of CPCs with the segregated structure is evaluated. Taken together, our results give a hint at how GO chemistry manifests the properties of rGO and the CPC derived from it, offering compelling opportunities for their practical applications. Graphene ; Oxide ; Graphene oxide paper ; Composite material ; Materials science ; Polymer ; Nanotechnology ; Metallurgy Graphene research and applications ; Conducting polymers and applications ; Carbon Nanotubes in Composites