jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Barry Y. Li | Claire E. Dickerson | Ashley J. Shin | Changling Zhao | Yi Shen | Yongjia He | Paula L. Diaconescu | Anastassia N. Alexandrova | Justin R. Caram
Source: Chemical Science (article, 2024-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Elucidating ultranarrow <sup>2</sup> F <sub>7/2</sub> to <sup>2</sup> F <sub>5/2</sub> absorption in ytterbium( <scp>iii</scp> ) complexes Achieving ultranarrow absorption linewidths in the condensed phase enables optical state preparation of specific non-thermal states, a prerequisite for quantum-enabled technologies. The 4f orbitals of lanthanide(iii) complexes are often referred to as "atom-like," reflecting their isolated nature, and are promising substrates for the optical preparation of specific quantum states. To better understand the photophysical properties of 4f states and assess their potential for quantum applications, theoretical building blocks are required for rapid screening. In this study, an atomic-level perturbative calculation (<i>i.e.</i>, spin-orbit crystal field, SOCF) is applied to various Yb(iii) complexes to investigate their linear absorption and emission through a fitting mechanism of their experimentally determined transition energies and oscillator strengths. In particular, the optical properties of (thiolfan)YbCl(THF) (thiolfan = 1,1'-bis(2,4-di-<i>tert</i>-butyl-6-thiomethylenephenoxy)ferrocene), a recently reported complex with an ultranarrow optical linewidth, are computed and compared to those of other Yb(iii) compounds. Through a transition energy sampling study, major contributors to the optical linewidth are identified. We observe particularly isolated f-f transitions and narrow linewidths, which we attribute to two distinct factors. Firstly, the ultra-high atomic similarity of the orbitals involved in the optical transition, along with the presence of an anisotropic crystal field, collectively contribute to the observed narrow transitions. Secondly, we note highly correlated excited-ground energy fluctuations that serve to greatly suppress inhomogeneous line-broadening. This article illustrates how SOCF can be used as a low-cost method to probe the influence of crystal field environment on the optical properties of Yb(iii) complexes to assist the development of novel lanthanide series quantum materials. Ytterbium ; Absorption (acoustics) ; Chemistry ; Analytical Chemistry (journal) ; Radiochemistry ; Physics ; Optics ; Laser ; Organic chemistry Magnetism in coordination complexes ; Lanthanide and Transition Metal Complexes ; Inorganic Fluorides and Related Compounds
Authors: Karima Ata | Tzonka Mineva | Bruno Alonso
Source: Molecules (article, 2024-09-21)
Field: Chemistry — Inorganic Chemistry

Strength of London Dispersion Forces in Organic Structure Directing Agent—Zeolite Assemblies Herein, we study the London dispersion forces between organic structure directing agents (OSDAs)-here tetraalkyl-ammonium or -phosphonium molecules-and silica zeolite frameworks (FWs). We demonstrate that the interaction energy for these dispersion forces is correlated to the number of H atoms in OSDAs, irrespective of the structures of OSDAs or FWs, and of variations in charges and thermal motions. All calculations considered-DFT-D3 and BOMD undertaken by us, and molecular mechanics from an accessible database-led to the same trend. The mean energy of these dispersion forces is ca. -2 kcal.mol<sup>-1</sup> per H for efficient H-O contacts. London dispersion force ; Dispersion (optics) ; Zeolite ; Molecule ; Chemical physics ; Interaction energy ; Phosphonium ; Chemistry ; Molecular dynamics ; Ammonium ; Computational chemistry ; Materials science ; Nanotechnology ; Chemical engineering ; Physics ; Organic chemistry ; Catalysis ; Optics Metal-Organic Frameworks: Synthesis and Applications ; Zeolite Catalysis and Synthesis ; Advanced NMR Techniques and Applications
Authors: Peter Fox | Jeongin Choi | Erin R. Johnson | Mark Stradiotto
Source: Chemistry - A European Journal (article, 2024-09-19)
Field: Chemistry — Organic Chemistry

Mapping Electrophile Chemoselectivity in DalPhos/Nickel <i>N</i>‐Arylation Catalysis: The Unusual Influence of Remote Sterics We disclose herein our evaluation of competitive (hetero)aryl-X (X: Br>Cl>OTf) reactivity preferences in bisphosphine/Ni-catalyzed C-N cross-coupling catalysis, using furfurylamine as a prototypical nucleophile, and employing DalPhos and DPPF as representative ancillary ligands with established efficacy. Beyond this general (pseudo)halide ranking, other intriguing structure-reactivity trends were noted experimentally, including the unexpected observation that bulky alkyl (e. g., R=tBu) substitution in para-R-aryl-X electrophiles strongly discourages (pseudo)halide reactivity relative to smaller substituents (e. g., nBu, Et, Me), despite being both remote from, and having a similar electronic influence on, the reacting C-X bond; such effects on nickel oxidative addition have not been documented previously and were not observed in our comparator reactions presented herein involving palladium. Density functional theory modeling of such PhPAd-DalPhos/Ni-catalyzed C-N cross-couplings revealed the origins of competitive turnover of C-Br over C-Cl, and possible ways in which bulky para-alkyl substitution might discourage net electrophile uptake/turnover, leading to inversion of halide selectivity. Chemoselectivity ; Electrophile ; Steric effects ; Nickel ; Catalysis ; Chemistry ; Organic chemistry Catalytic Cross-Coupling Reactions ; Asymmetric Hydrogenation and Catalysis ; Chemical Synthesis and Analysis
Authors: Yoshiki Hasukawa | Micke Kuwahara | Lauren Takahashi | Keisuke Takahashi
Source: Science and Technology of Advanced Materials Methods (article, 2024-01-04)
Field: Materials Science — Materials Chemistry

Development of graphical user interface for design of experiments via Gaussian process regression and its case study Bayesian optimization, coupled with Gaussian process regression and acquisition functions, has proven to be a powerful tool in the field of experimental design.Nevertheless, it demands a profound proficiency in software programming, machine learning, and statistical concepts.This steep learning curve presents a substantial obstacle when implementing Bayesian optimization for experimental design.In order to overcome this challenge, a user-friendly graphical interface for Gaussian process regression and acquisition functions is proposed.This accessible tool can be readily accessed via web browsers, courtesy of the established CADS platform (available at https://cads.eng.hokudai.ac.jp/).Thus, the interface offers to perform Bayesian optimization without any programming or any extensive prior knowledge about Bayesian optimization and machine learning. Bayesian optimization ; Kriging ; Computer science ; Machine learning ; Gaussian process ; Bayesian probability ; Artificial intelligence ; Interface (matter) ; Process (computing) ; User interface ; Graphical user interface ; Human–computer interaction ; Data mining ; Gaussian ; Programming language Machine Learning in Materials Science ; Advanced Multi-Objective Optimization Algorithms ; Computational Drug Discovery Methods
Authors: Batuhan S. Can | Norman V. V. Blümel | Erik P. van Geest | Max Makurat | J. M. van Ruitenbeek | Grégory F. Schneider
Source: Applied Physics Letters (article, 2024-05-20)
Field: Materials Science — Materials Chemistry

A Perspective on graphene junctions for recognition tunneling Biopolymer sequencing with graphene edge-based tunnel junctions has the potential to overcome current limitations with the third generation of sequencing based on biological nanopores. Detection of nucleotides via (recognition) tunneling with noble metal break junctions shows promising results; however, the bulky nature and a range of physical and chemical instabilities of the electrodes prevent advancing toward long-read sequencing with single base-calling accuracy. Graphene edges as tunnel electrodes may overcome these limitations, with the possibility to reach true single-molecule readout, thanks to their 2D nature. Currently, the development of graphene tunnel sequencers faces challenges in terms of targeted chemical functionalization of the graphene edge to enable recognition tunneling and the eventual integration in a nanopore configuration to realize long-read sequencing of biopolymers. Herein, we discuss the current developments that encourage active research toward graphene edge junctions for single-molecule detection, recognition, and sequencing applications with nucleotides and deoxyribonucleic acid as example. Graphene ; Quantum tunnelling ; Perspective (graphical) ; Materials science ; Nanotechnology ; Condensed matter physics ; Physics ; Optoelectronics ; Computer science ; Artificial intelligence Graphene research and applications ; Nanopore and Nanochannel Transport Studies ; Advancements in Semiconductor Devices and Circuit Design
Authors: Miguel Recio-Poo | Ángel Morales‐García | Francesc Illas | Stefan T. Bromley
Source: The Journal of Physical Chemistry Letters (article, 2024-08-06)
Field: Materials Science — Materials Chemistry

Size-Dependent Ab Initio Atomistic Thermodynamics from Cluster to Bulk: Application to Hydration of Titania Nanoparticles Ab initio atomistic thermodynamics (AIAT) has become an indispensable tool to estimate Gibbs free energy changes for solid surfaces interacting with gaseous species relative to pressure (<i>p</i>) and temperature (<i>T</i>). For such systems, AIAT assumes that solid vibrational contributions to Gibbs free energy differences cancel out. However, the validity of this assumption is unclear for nanoscale systems. Using hydrated titania nanoparticles (NPs) as an example, we estimate the vibrational contributions to the Gibbs free energy of hydration (Δ<i>G</i><sub><i>hyd</i></sub>(<i>T</i>,<i>p</i>)) for arbitrary NP size and degree of hydration. Comparing Δ<i>G</i><sub><i>hyd</i></sub>(<i>T</i>,<i>p</i>) phase diagrams for NPs when considering these contributions (AIAT<sub>nano</sub>) relative to a standard AIAT approach reveals significant qualitative and quantitative differences, which only become negligible for large systems. By constructing a size-dependent Δ<i>G</i><sub><i>hyd</i></sub>(<i>T</i>,<i>p</i>) phase diagram, we illustrate how our approach can provide deeper insights into how nanosytems interact with their environments, with many potential applications (e.g., catalytic nanoparticles, biological colloids, nanoparticulate pollutants). Cluster (spacecraft) ; Ab initio ; Thermodynamics ; Nanoparticle ; Materials science ; Chemical physics ; Nanotechnology ; Chemistry ; Physics Machine Learning in Materials Science ; Catalysis and Oxidation Reactions ; Advanced Chemical Physics Studies
Authors: Leandro Goulart de Araujo | Gabriel Fuitem Martins | Alexssandra Andrea Antunes Campera | Júlio Takehiro Marumo | Sabine Neusatz Guilhen
Source: Frontiers in Environmental Chemistry (article, 2024-09-18)
Field: Chemistry — Analytical Chemistry

Biosorption of methylene blue by bone meal: experimental and modeling with machine learning and full factorial design Sorption technologies have been proposed for the treatment of water containing methylene blue (MB), a toxic and persistent pollutant. Despite its environmental risks, the role of process variables in MB removal has not been fully explored through experimental design. The objective of this study is to assess the potential of bone meal powder (BMP), an underexplored agricultural byproduct, as an affordable adsorbent for the removal of MB from water. BMP was subjected to a series of analytical characterization techniques, and its adsorption capacity was evaluated through a comprehensive factorial design, which investigated the effects of biosorbent dosage, solution pH, and initial MB concentration. The study revealed that the highest adsorption level was 14.49 mg g −1 , attained under the following conditions: 1 g L −1 BMP, pH 11, and 100 mg L −1 MB. The adsorption equilibrium was reached within 60 min, with a measured capacity (qexp) of 18 mg g −1 . Theoretical adsorption isotherms indicated a capacity of 63 mg g −1 , which aligned well with the Langmuir model. To predict adsorption outcomes, machine learning models were applied, with multiple linear regression performing best. Optimization of decision trees and neural networks improved accuracy but risked overfitting. FT-IR, XRD, and ICP analyses indicated ion exchange as a significant mechanism of adsorption. In desorption studies, H 2 SO 4 was the most effective agent, achieving 68.72% desorption efficiency. BMP exhibited optimal recyclability for up to four cycles before efficiency declined. Methylene blue ; Biosorption ; Factorial experiment ; Fractional factorial design ; Meal ; Chemistry ; Computer science ; Mathematics ; Food science ; Machine learning ; Adsorption ; Organic chemistry Dye analysis and toxicity ; Adsorption and biosorption for pollutant removal
Authors: Teobald Kupka | Natalina Makieieva | Paweł Świsłowski | Małgorzata Rajfur | Artur Małolepszy | Leszek Stobiński | Stefania Grzeszczyk | Krystian Jurowski | Adam Sudoł | R. Wrzalik | Oimahmad Rahmonov | Krzysztof Ejsmont
Source: Molecules (article, 2024-11-14)
Field: Materials Science — Materials Chemistry

Carbon Nanotubes in Cement—A New Approach for Building Composites and Its Influence on Environmental Effect of Material An addition of carbon nanostructures to cement paste is problematic due to the difficulties in obtaining homogenous mixtures. The paper reports on a more effective way of mixing carboxylated multi-walled carbon nanotubes (MWCNT-COOH) in cement pastes. The additional biological impact of the studied nanomodified cement was analyzed in the case of two moss species' vitality. The applied approach of obtaining a homogeneous mixture is based on intense mechanochemical mixing of MWCNT-COOH together with polycarboxylate superplasticizer (SP). As a result, a more homogenous suspension of MWCNT-COOH within a liquid superplasticizer, suitable for addition to hydrophilic cement paste, was obtained. FT-IR/Raman spectroscopy was used for materials' characterization. To explain the mixing process at the molecular level, systematic theoretical studies using density functional theory (DFT) were performed. The structures, interaction energies and IR/Raman vibrational spectra of model carboxylic acids, mixed with functionalized SWCNTs as simplified models of real MWCNTs, were obtained. Due to the controversial opinions on the environmental hazards of carbon nanostructures, additional in vivo studies were performed. In this case, effects of cement modified by the addition of small amounts of MWCNT-COOH with SP in comparison to the composite without carbon nanostructures and control subsoil on the vitality of mosses <i>Polytrichum formosum</i> and <i>Pseudoscleropodium purum</i> were studied. Cement ; Composite material ; Carbon nanotube ; Materials science ; Carbon fibers ; Composite number Carbon Nanotubes in Composites ; Nanotechnology research and applications ; Advanced Energy Technologies and Civil Engineering Innovations
Authors: Jian Wang | Bingsheng Li | Shiwei Xie | Bin Ji
Source: Water (article, 2024-08-18)
Field: Materials Science — Materials Chemistry

Degradation of Bisphenol A Using Self-Excited Oscillating Jets in Synergy with Fenton and Periodate Oxidation: Experimental and Artificial Neural Network Modeling Study Bisphenol A (BPA) is an environmental endocrine-disrupting compound that is resistant to conventional biological treatment, making it crucial to develop an oxidation process. This study introduces a novel hydrodynamic cavitation (HC) coupled with a Fenton + periodate (PI) oxidation system for the efficient degradation of BPA. By systematically examining the key parameters such as inlet pressure, Fe (II), H2O2, and PI concentration, it was found that HC performed optimally at a pressure of 0.5 MPa. A conversion of 98.14% was achieved within 60 min when the molar ratio of BPA, Fe (II), H2O2, and PI was approximately 1:1:5:1. Further analysis revealed that the gray correlation between H2O2 and PI concentrations on the degradation efficiency was 0.833 and 0.843, respectively, indicating that both of them had significant effects on the degradation process. The free radical quenching assay confirmed the hydroxyl radical (•OH) as the main active substance. Additionally, the toxicity of the degradation intermediates was evaluated using the Toxicity Estimation Software Tool (TEST). An artificial neural network (ANN)-based model was constructed to predict the BPA-degradation process, facilitating precise reagent dosing and providing robust support for the intelligent application of water-treatment technologies. Degradation (telecommunications) ; Periodate ; Bisphenol A ; Chemistry ; Reagent ; Advanced oxidation process ; Artificial neural network ; Catalysis ; Nuclear chemistry ; Organic chemistry ; Computer science Ultrasound and Cavitation Phenomena ; Advanced oxidation water treatment ; Toxic Organic Pollutants Impact
Authors: Guo, Shuhan | Yatao Bian | Wang, Ruibing | Yin, Nan | Wang, Zhen | Yao, Quanming
Source: arXiv (Cornell University) (preprint, 2024-08-01)
Field: Materials Science — Materials Chemistry

UniMoT: Unified Molecule-Text Language Model with Discrete Token Representation The remarkable success of Large Language Models (LLMs) across diverse tasks has driven the research community to extend their capabilities to molecular applications. However, most molecular LLMs employ adapter-based architectures that do not treat molecule and text modalities equally and lack a supervision signal for the molecule modality. To address these issues, we introduce UniMoT, a Unified Molecule-Text LLM adopting a tokenizer-based architecture that expands the vocabulary of LLM with molecule tokens. Specifically, we introduce a Vector Quantization-driven tokenizer that incorporates a Q-Former to bridge the modality gap between molecule and text. This tokenizer transforms molecules into sequences of molecule tokens with causal dependency, encapsulating high-level molecular and textual information. Equipped with this tokenizer, UniMoT can unify molecule and text modalities under a shared token representation and an autoregressive training paradigm, enabling it to interpret molecules as a foreign language and generate them as text. Following a four-stage training scheme, UniMoT emerges as a multi-modal generalist capable of performing both molecule-to-text and text-to-molecule tasks. Extensive experiments demonstrate that UniMoT achieves state-of-the-art performance across a wide range of molecule comprehension and generation tasks. Security token ; Representation (politics) ; Computer science ; Theoretical computer science ; Natural language processing ; Computer network ; Political science Machine Learning in Materials Science ; Chemical Synthesis and Analysis
Authors: Bioru Okumura | Eriko Yamaguchi | Naoko Komura | Taku Ohtomi | S. Kawano | Hiroyasu Sato | Hiroshi Katagiri | Hiromune Ando | Masato Ikeda
Source: Communications Materials (article, 2024-09-10)
Field: Chemistry — Organic Chemistry

Photodegradable glyco-microfibers fabricated by the self-assembly of cellobiose derivatives bearing nitrobenzyl groups Stimuli-responsive materials constructed via the self-assembly of small biomolecules are attracting increasing attention because of their biocompatibility, sustainability, and variety of (bio)applications. Nevertheless, the research on oligosaccharide-based molecular designs for such stimuli-responsive materials (or stimuli-responsive glyco-materials) is limited, partly due to the intrinsic structural diversity of oligosaccharides and the difficulty associated with their selective chemical syntheses. Herein, we report the construction of photodegradable glyco-microfibers by the self-assembly of cellobiose derivatives bearing nitrobenzyl groups. The atomic-scale, self-assembled architecture of the photodegradable glyco-microfibers is unveiled and compared with those of pristine cellobiose and cellulose polymorphs in previous reports. Stimuli-responsive oligosaccharide-based molecular designs are limited due to their intrinsic structural diversity and difficulties in selective synthesis. Here, photodegradable glyco-microfibers are synthesized by the selfassembly of cellobiose derivatives bearing nitrobenzyl groups. Microfiber ; Cellobiose ; Bearing (navigation) ; Materials science ; Chemistry ; Polymer science ; Composite material ; Polymer chemistry ; Organic chemistry ; Computer science ; Cellulose Polydiacetylene-based materials and applications ; Supramolecular Self-Assembly in Materials ; biodegradable polymer synthesis and properties
Authors: Ziwen Zhao | Nikolaos Kostopoulos | Sagar Ganguli | Paul L. Bergstrom | Alina Sekretareva
Source: ChemRxiv (preprint, 2024-03-04)
Field: Chemistry — Electrochemistry

Single-Entity Protein Electrochemistry of Diffusion-Limited Enzymes Single-entity electrochemistry has recently emerged as a promising method for label-free exploration of the catalytic functions of individual enzymes. However, skepticism within the scientific community regarding the applicability of the method for single enzyme measurements has arisen due to issues in the experimental data presented in the literature and limited theoretical modeling of such data. Here, we address these concerns through a thorough experimental investigation of two diffusion-limited enzymes, catalase and superoxide dismutase, employing a combination of protein film voltammetry and single-entity protein electrochemistry measurements. We then introduce a novel theoretical model for simulating the current responses, generated by the reduction of the product of the enzymatic reaction of single enzyme molecules at the electrode. This model is based on a combination of finite element simulations using COMSOL Multiphysics and random walk simulations. It incorporates the diffusion-limited enzymatic kinetics of the investigated enzymes and introduces a geometry that mimics the substrate diffusion channel of the enzyme. Our work demonstrates that the experimentally detected current signals align with the simulated current signals, affirming that they can be attributed to the catalytic activity of single enzymes detected via the product of the enzymatic reaction. Electrochemistry ; Diffusion ; Enzyme ; Chemistry ; Computer science ; Biochemistry ; Computational biology ; Biology ; Physics ; Physical chemistry ; Thermodynamics ; Electrode Electrochemical Analysis and Applications ; Biotin and Related Studies ; Molecular Junctions and Nanostructures
Authors: Jonas Keukelier | Wouter Devulder | Stefanie Sergeant | Thomas Nuytten | Johan Meersschaut | Karl Opsomer | Christophe Detavernier
Source: Journal of Non-Crystalline Solids (article, 2024-08-20)
Field: Materials Science — Materials Chemistry

Study of SiGeAsTe and SiGeAsSe chalcogenide thin films by Raman spectroscopy and understanding of their OTS properties Chalcogenide ; Raman spectroscopy ; Materials science ; Nanotechnology ; Thin film ; Spectroscopy ; Optoelectronics ; Optics ; Physics Phase-change materials and chalcogenides ; Chalcogenide Semiconductor Thin Films ; Semiconductor materials and interfaces