jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Soheil Tavassoli | Afsaneh Mollahosseini | Saeed Damiri | Mehrshad Samadi
Source: Heliyon (article, 2024-11-28)
Field: Materials Science — Materials Chemistry

Luffa–Ni/Al layered double hydroxide bio-nanocomposite for efficient ibuprofen removal from aqueous solution: Kinetic, equilibrium, thermodynamic studies and GEP modeling Luffa is a robust, renewable biomaterial known for its low mass, high specific strength, and non-toxicity, making it ideal for composite development. This study modified luffa to create the LF@ppy@LDH nanocomposite, combining luffa, polypyrrole, and layered double hydroxides to efficiently remove ibuprofen from water. Techniques like FE-SEM, EDX, FTIR, and XRD confirmed the modification. To optimize adsorption efficiency, factors such as contact time <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow><mml:mrow><mml:mo>(</mml:mo> <mml:mrow><mml:mi>C</mml:mi> <mml:mi>t</mml:mi> <mml:mi>i</mml:mi> <mml:mi>m</mml:mi> <mml:mi>e</mml:mi></mml:mrow> <mml:mo>)</mml:mo></mml:mrow> </mml:mrow> </mml:math> , adsorbent dosage <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mo>(</mml:mo> <mml:mrow><mml:mi>A</mml:mi> <mml:mi>d</mml:mi></mml:mrow> <mml:mo>)</mml:mo></mml:mrow> </mml:math> , drug concentration <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mo>(</mml:mo> <mml:mrow><mml:mi>D</mml:mi> <mml:mi>c</mml:mi></mml:mrow> <mml:mo>)</mml:mo></mml:mrow> </mml:math> , temperature ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mi>θ</mml:mi> <mml:mo>)</mml:mo></mml:mrow> </mml:math> , stirring rate <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mo>(</mml:mo> <mml:mrow><mml:mi>S</mml:mi> <mml:mi>r</mml:mi></mml:mrow> <mml:mo>)</mml:mo></mml:mrow> </mml:math> , and pH were carefully fine-tuned to maximize efficiency. The highest ibuprofen removal occurred at pH 5, with an adsorption capacity of 44.306 mg/g at 298 K. The Temkin isotherm model, which points to chemisorption as the mechanism, accurately depicted the adsorption process with a high correlation coefficient (R<sup>2</sup> = 0.984). Moreover, the Elovich kinetic model proved to be the most precise in describing how ibuprofen adheres to the modified luffa, showing a very tight fit with the data (R<sup>2</sup> = 0.993). LF@ppy@LDH demonstrated outstanding reusability, maintaining steady adsorption over five repeated rounds. In addition, a powerful data-driven model, namely gene expression programming (GEP), was employed to provide an explicit formula relating input variables to removal efficiency, highlighting the potential of LF@ppy@LDH for water purification and environmental remediation. Hydroxide ; Aqueous solution ; Nanocomposite ; Kinetic energy ; Ibuprofen ; Chemical engineering ; Chemistry ; Layered double hydroxides ; Materials science ; Thermodynamics ; Nanotechnology ; Inorganic chemistry ; Physical chemistry ; Engineering ; Physics Layered Double Hydroxides Synthesis and Applications ; Mesoporous Materials and Catalysis ; Metal-Organic Frameworks: Synthesis and Applications
Authors: Huajian Yu | Luis A. Villaescusa | Zihao Gao | Miguel Á. Camblor
Source: Angewandte Chemie (article, 2024-08-14)
Field: Chemistry — Inorganic Chemistry

Stable Silica‐Based Zeolites with Three‐Dimensional Systems of Extra‐Large Pores Abstract Zeolites are microporous crystalline materials that find a very wide range of applications, which, however, are limited by the size and dimensionality of their pores. Stable silica zeolites with a three‐dimensional (3D) system of extra‐large pores (ELP, i.e., pores with minimum windows along the diffusion path consisting of more than 12 SiO 4/2 tetrahedra, 12R) are in demand for processing larger molecules than zeolites can currently handle. However, they have challenged worldwide synthetic capabilities for more than eight decades. In this review we first present a brief history of the discovery of ELP zeolites. Next, we show that earlier successes of zeolites with 3D ELP were not actually zeolites, but rather interrupted structures with, in addition, a composition that severely detracted from their stability. Finally, we present three new fully connected stable silica‐based 3D ELP zeolites ZEO‐1, ZEO‐3 and ZEO‐5, discuss their preparation methods and stability as well as the clear advantage of their increased porosity in catalysis and adsorption processes involving large molecules. We will discuss peculiar characteristics of their preparation and present two new reaction types giving rise to zeolites (1D‐to‐3D topotactic condensation and interchain expansion), highlighting how new synthesis methods can provide materials that would otherwise be unfeasible. Microporous material ; Porosity ; Zeolite ; Adsorption ; Chemical engineering ; Nanotechnology ; Molecule ; Catalysis ; Materials science ; Condensation ; Diffusion ; Chemistry ; Organic chemistry ; Composite material ; Physics ; Thermodynamics Zeolite Catalysis and Synthesis ; Mesoporous Materials and Catalysis ; Metal-Organic Frameworks: Synthesis and Applications
Authors: Sangen Zhao | Zhou Yang | Zhengfeng Guo | Honggang Gu | Yanqiang Li | Yi Peng Song | Shiyuan Liu | Maochun Hong | Junhua Luo
Source: Research Square (preprint, 2024-01-19)
Field: Materials Science — Electronic, Optical and Magnetic Materials

A solution-processable natural crystal with giant optical anisotropy for efficient manipulation of light polarization <title>Abstract</title> Optical anisotropy (e.g., birefringence and dichroism), a light-matter interaction phenomenon observed three centuries ago in natural Iceland crystal, is paramount for manipulating light polarization in modern optics. To date, various natural birefringent crystals are widely used, but their birefringence is limited to &lt; 0.3. Here, we demonstrate a solution-processable natural crystal C<sub>3</sub>H<sub>8</sub>N<sub>3</sub>I<sub>6</sub>·3H<sub>2</sub>O with giant birefringence up to 2.8 from visible to infrared spectral region, which hits a new high among natural crystals. Combining critical point analysis and the first-principles calculations, we reveal that this giant optical anisotropy mainly comes from the linear (I<sub>3</sub>)<sup>-</sup> structural units in a parallel arrangement, which maximizes the difference of polarizability along the different crystallographic axes. This work highlights the potential of natural polyiodide crystals as an outstanding platform to satisfy the increasing demand for next-generation polarized photonic applications in optical communication, 3D imaging, ultra-high-resolution sensing, etc. Birefringence ; Anisotropy ; Polarizability ; Polarization (electrochemistry) ; Materials science ; Dichroism ; Optics ; Crystal (programming language) ; Photonic crystal ; Optoelectronics ; Linear dichroism ; Crystallography ; Circular dichroism ; Physics ; Chemistry ; Molecule ; Computer science Crystal Structures and Properties ; Perovskite Materials and Applications ; Nonlinear Optical Materials Research
Authors: Stefano Racioppi | Alberto Otero‐de‐la‐Roza | Samad Hajinazar | Eva Zurek
Source: arXiv (Cornell University) (preprint, 2024-07-07)
Field: Materials Science — Materials Chemistry

Powder X-Ray Diffraction Assisted Evolutionary Algorithm for Crystal Structure Prediction Experimentally obtained X-ray diffraction (XRD) patterns can be difficult to solve, precluding the full characterization of materials, pharmaceuticals, and geological compounds. Herein, we propose a method based upon a multi-objective evolutionary search that uses both a structure's enthalpy and similarity to a reference XRD pattern (constituted by a list of peak positions and their intensities) to facilitate structure solution of inorganic systems. Because the similarity index is computed for locally optimized cells that are subsequently distorted to find the best match with the reference, this process transcends both computational (e.g. choice of theoretical method, and 0 K approximation) and experimental (e.g. external stimuli, and metastability) limitations. We illustrate how the proposed methodology can be employed to successfully uncover complex crystal structures by applying it to a range of test cases, including inorganic minerals, pure elements ramp-compressed to extreme conditions, and molecular crystals. The results demonstrate that our approach not only improves the accuracy of structure prediction but also significantly reduces the time required to achieve reliable solutions, thus providing a powerful tool for the advancement of materials science and related fields. Diffraction ; Algorithm ; Evolutionary algorithm ; Materials science ; Crystal structure ; Crystal structure prediction ; X-ray ; Powder diffraction ; X-ray crystallography ; Crystallography ; Computer science ; Physics ; Artificial intelligence ; Optics ; Chemistry X-ray Diffraction in Crystallography
Authors: Nagihan Çaylak Delibaş | Turgut SÜLEYMANOĞLU
Source: TURKISH JOURNAL OF CHEMISTRY (article, 2024-02-21)
Field: Materials Science — Electronic, Optical and Magnetic Materials

The effect of partial substitution of noble metal (Pd) at the B site of La0.6Sr0.4FeO3 as a supercapacitor electrode material Sol-gel combustion was used to produce the perovskite-type La<sub>0.6</sub>Sr<sub>0.4</sub>FeO<sub>3</sub> (LSF) and La<sub>0.6</sub>Sr<sub>0.4</sub>Fe<sub>0.9</sub>Pd<sub>0.1</sub>O<sub>3</sub> (LSFP) materials and assessed as supercapacitor electrodes. The synthesized materials' crystal structure, morphology, and electrochemical performance were thoroughly analyzed. The partial substitution of Pd in the B site of the LSF structure affected the electrochemical properties of this compound and improved its performance. In fact, the greatest effect of Pd substitution was on the content of oxygen vacancies, which are known as the active sites of the perovskite surface in the supercapacitor cell. The specific capacitance obtained for the sample containing Pd was about 80 F.g<sup>-1</sup> at a current density of 1 A.g<sup>-1</sup> in 1M KOH. In addition, this sample had a decreased intrinsic resistance to ion and electron diffusion. The remarkable structural and morphological features of LSFP contribute to its superior electrochemical performance. At a power density of 1000 W.kg<sup>-1</sup> and a current density of 1 A.g<sup>-1</sup>, an LSFP symmetrical cell had an energy density of 44.45 W.h.kg<sup>-1</sup>. Chemistry ; Supercapacitor ; Electrochemistry ; Electrode ; Current density ; Noble metal ; Capacitance ; Perovskite (structure) ; Power density ; Crystal structure ; Diffusion ; Metal ; Chemical engineering ; Inorganic chemistry ; Crystallography ; Physical chemistry ; Organic chemistry Supercapacitor Materials and Fabrication ; Advanced battery technologies research ; Electrocatalysts for Energy Conversion
Authors: Irina V. Lebedeva | С. А. Вырко | Alexander S. Sinitsa | Sergey V. Ratkevich | А. М. Попов | Andrey A. Knizhnik | N. A. Poklonski | Yu. E. Lozovik
Source: Computational and Theoretical Chemistry (article, 2024-10-10)
Field: Materials Science — Materials Chemistry

Magnetic and electronic properties of 1D hybrid nanoobjects composed of alternating polycyclic hydrocarbon regions and double carbon chains Chemistry ; Hydrocarbon ; Carbon fibers ; Carbon chain ; Polycyclic aromatic hydrocarbon ; Nanotechnology ; Organic chemistry ; Composite material Graphene research and applications ; Boron and Carbon Nanomaterials Research ; Fullerene Chemistry and Applications
Authors: Shi Yin | Xinyang Pan | Fengyan Wang | Lixin He
Source: arXiv (Cornell University) (preprint, 2024-05-09)
Field: Materials Science — Materials Chemistry

TraceGrad: a Framework Learning Expressive SO(3)-equivariant Non-linear Representations for Electronic-Structure Hamiltonian Prediction We propose a framework to combine strong non-linear expressiveness with strict SO(3)-equivariance in prediction of the electronic-structure Hamiltonian, by exploring the mathematical relationships between SO(3)-invariant and SO(3)-equivariant quantities and their representations. The proposed framework, called TraceGrad, first constructs theoretical SO(3)-invariant trace quantities derived from the Hamiltonian targets, and use these invariant quantities as supervisory labels to guide the learning of high-quality SO(3)-invariant features. Given that SO(3)-invariance is preserved under non-linear operations, the learning of invariant features can extensively utilize non-linear mappings, thereby fully capturing the non-linear patterns inherent in physical systems. Building on this, we propose a gradient-based mechanism to induce SO(3)-equivariant encodings of various degrees from the learned SO(3)-invariant features. This mechanism can incorporate powerful non-linear expressive capabilities into SO(3)-equivariant features with consistency of physical dimensions to the regression targets, while theoretically preserving equivariant properties, establishing a strong foundation for predicting Hamiltonian. Our method achieves state-of-the-art performance in prediction accuracy across eight challenging benchmark databases on Hamiltonian prediction. Experimental results demonstrate that this approach not only improves the accuracy of Hamiltonian prediction but also significantly enhances the prediction for downstream physical quantities, and also markedly improves the acceleration performance for the traditional Density Functional Theory algorithms. Equivariant map ; Representation (politics) ; Hamiltonian (control theory) ; Mathematics ; Algebra over a field ; Pure mathematics ; Computer science ; Political science ; Mathematical optimization ; Law Machine Learning in Materials Science ; Protein Structure and Dynamics ; Topic Modeling
Authors: Tobias Schäfer
Source: The Journal of Physical Chemistry Letters (article, 2024-12-18)
Field: Materials Science — Materials Chemistry

Ground States for Metals from Converged Coupled Cluster Calculations Many-electron correlation methods offer a systematic approach to predicting material properties with high precision. However, practically attaining accurate ground-state properties for bulk metals presents significant challenges. In this work, we propose a novel scheme to reach the thermodynamic limit of the total ground-state energy of metals using coupled cluster theory. We demonstrate that the coupling between long-range and short-range contributions to the correlation energy is sufficiently weak, enabling us to restrict long-range contributions to low-energy excitations in a controllable way. Leveraging this insight, we calculated the surface energy of aluminum and platinum (111), providing numerical evidence that coupled cluster theory is well-suited for modeling metallic materials, particularly in surface science. Notably, our results exhibit convergence with respect to finite-size effects, basis-set size, and coupled cluster expansion, yielding excellent agreement with experimental data. This paves the way for more efficient coupled cluster calculations for large systems and a broader utilization of theory in realistic metallic models of materials. Cluster (spacecraft) ; Coupled cluster ; Physics ; Computer science ; Quantum mechanics ; Molecule ; Computer network X-ray Diffraction in Crystallography ; Radioactive element chemistry and processing ; Crystal Structures and Properties
Authors: Goutam Mandal | Baibaswata Bhattacharjee
Source: Indian Journal of Science and Technology (article, 2024-08-24)
Field: Chemistry — Organic Chemistry

RSM-CCD Modeling and Optimization for Adsorptive Removal of Rose Bengal Dye from Aqueous Medium using CeO2 Nanoflowers Objective: The focus of the study was to synthesize cerium oxide (CeO2) nanoparticles (NPs) and use them as nano adsorbents to remove toxic Rose Bengal (RB) dye from wastewater. Methods: A simple chemical method was used to synthesize CeO2 nanostructures. The nanostructures were characterized using XRD spectra, FESEM, and UV-Vis spectroscopy. The nanoparticles are used as nano adsorbents for wastewater treatment. Here, we utilized response surface methodology-central composite design (RSM-CCD) to optimize the batch adsorption studies rather than using the usual one-variable-at-a-time approach. The parameters for our investigations were the agitation period, CeO2 NP dosage, solution pH, and initial RB dye concentration. Findings: The characterization study showed that nanoflowers of a mean particle size of 44 nm and band gap of 3.68 eV were formed. RSM-CCD methodology for optimization resulted in an agitation time of 29.36 min, an NP dose of 0.302 g/L, a solution pH of 6.96, and a starting dye concentration of 88.65 mg/L gives the highest adsorption of 88.46%. The kinetics data indicated a strong fit with the pseudo-second-order (PSO) equation, while the Freundlich isotherm model fitted the equilibrium data accurately, resulting in 187 mg/g. The thermodynamic analysis suggested that adsorption was characterized by being endothermic, spontaneous, and physical. Novelty: The unique nanoflowers were employed and removal efficiency was predicted using a 2nd-order polynomial equation in Stat-Ease Design Expert Software ver.13. The model showed an excellent match with an adjusted R2 value of 0.9736 and a projected R2 value of 0.9256. Keywords: Cerium oxide nanoparticles, Adsorption, Response surface methodology, Central composite design, Rose Bengal, Optimization Response surface methodology ; Central composite design ; Adsorption ; Freundlich equation ; Rose bengal ; Endothermic process ; Aqueous solution ; Materials science ; Cerium oxide ; Nuclear chemistry ; Nanoparticle ; Chemical engineering ; Chemistry ; Nanotechnology ; Chromatography ; Oxide ; Organic chemistry Nanomaterials for catalytic reactions
Authors: Man Vir Singh | Sandeep Saini | Duo Pan
Source: ES Energy & Environments (article, 2024-01-01)
Field: Materials Science — Materials Chemistry

Deformation of Waste Inner Tube Tyre into Valorized Reused Petrochemicals Through Pyrolysis Process Provides a comprehensive overview of rubber tyre types and their diverse applications.Furthermore, the chapter addresses the critical issue of waste rubber tyres, exploring the environmental impact and challenges associated with their disposal.Waste tyres were analyzed by thermogravimetric analysis (TGA) for thermal stability.Valorized reused petrochemicals are obtained by pyrolysis process through a glass reactor.The volume of liquids, gases, and residues from waste tyre was 100 gm (Gram) whose conversion rate in liquid hydrocarbons was 64 %, light gases 12.20 % and residue 23.80 %.Liquids, gases, and residues from waste tyre 90 gm plastic were collected, waste inner tube tyre plastic whose conversion rate in liquid hydrocarbons was 55 %, light gases 18.55 %, and residue 26.45 %.Liquids, gases, and residues from waste inner tube tyre 85 gm plastics whose conversion rate in liquid hydrocarbon was 64 %, light gases 11.64 %, and residue 24.36 %.GC-MS and FT-IR analyzed valorized reused petrochemicals obtained from the various types of green petrochemicals.Valorized reused petrochemicals can be used in the petrochemical industries for raw materials. Petrochemical ; Pyrolysis ; Tube (container) ; Process (computing) ; Deformation (meteorology) ; Materials science ; Waste management ; Composite material ; Engineering ; Computer science Graphite, nuclear technology, radiation studies ; Iron and Steelmaking Processes ; Catalysis and Hydrodesulfurization Studies
Authors: Rahul Khorana | Marcus M. Noack | Jin Qian
Source: arXiv (Cornell University) (preprint, 2024-09-23)
Field: Chemistry — Spectroscopy

Polyatomic Complexes: A topologically-informed learning representation for atomistic systems Developing robust representations of chemical structures that enable models to learn topological inductive biases is challenging. In this manuscript, we present a representation of atomistic systems. We begin by proving that our representation satisfies all structural, geometric, efficiency, and generalizability constraints. Afterward, we provide a general algorithm to encode any atomistic system. Finally, we report performance comparable to state-of-the-art methods on numerous tasks. We open-source all code and datasets. The code and data are available at https://github.com/rahulkhorana/PolyatomicComplexes. Representation (politics) ; Polyatomic ion ; Computer science ; Theoretical computer science ; Theoretical physics ; Physics ; Molecule ; Political science ; Quantum mechanics Analytical Chemistry and Chromatography ; Surface Chemistry and Catalysis
Authors: Himanshu Sharma | Kumar Vanka
Source: ChemRxiv (preprint, 2024-02-06)
Field: Chemistry — Organic Chemistry

The Discovery of an Aromatic Silicon Aluminium Compound Through A Novel Four-Pronged Computational Approach Traditional experimental methods for the design of molecules are time-consuming and inefficient, prompting a shift towards computational approaches. Here, we unveil a strategy that transcends traditional paradigms. Rooted in first principles and liberated from experimental constraints, our newly developed four-stage approach allows the discovery of new molecules that display interesting properties. The current work showcases an interesting molecule that has been discovered through this approach: a four membered cyclic compound of silicon and aluminium that displays 2π aromaticity, and capable of the activation of important small molecules. Aluminium ; Silicon ; Molecule ; Aromaticity ; Nanotechnology ; Work (physics) ; Materials science ; Computer science ; Chemistry ; Combinatorial chemistry ; Optoelectronics ; Engineering ; Organic chemistry ; Mechanical engineering Synthesis and Properties of Aromatic Compounds ; Boron and Carbon Nanomaterials Research ; Fullerene Chemistry and Applications