jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Xiang Chen
Source: arXiv (Cornell University) (preprint, 2024-12-05)
Field: Chemistry — Spectroscopy

LMDM:Latent Molecular Diffusion Model For 3D Molecule Generation n this work, we propose a latent molecular diffusion model that can make the generated 3D molecules rich in diversity and maintain rich geometric features. The model captures the information of the forces and local constraints between atoms so that the generated molecules can maintain Euclidean transformation and high level of effectiveness and diversity. We also use the lowerrank manifold advantage of the latent variables of the latent model to fuse the information of the forces between atoms to better maintain the geometric equivariant properties of the molecules. Because there is no need to perform information fusion encoding in stages like traditional encoders and decoders, this reduces the amount of calculation in the back-propagation process. The model keeps the forces and local constraints of particle bonds in the latent variable space, reducing the impact of underfitting on the surface of the network on the large position drift of the particle geometry, so that our model can converge earlier. We introduce a distribution control variable in each backward step to strengthen exploration and improve the diversity of generation. In the experiment, the quality of the samples we generated and the convergence speed of the model have been significantly improved. Diffusion ; Molecule ; Chemistry ; Physics ; Thermodynamics Analytical Chemistry and Chromatography ; Microfluidic and Capillary Electrophoresis Applications ; Innovative Microfluidic and Catalytic Techniques Innovation
Authors: Muhammad Luqman Mohamed Rijal | Azmi Mohamed Yusof | Rizal Mohamed Noor | Ahmad Zubair
Source: Jurnal Mekanikal (review, 2024-12-29)
Field: Materials Science — Surfaces, Coatings and Films

A MINI REVIEW ON THE EFFECTS OF SURFACE ROUGHNESS IN MICROFIUIDICS CHANNELS The effects of surface roughness at low Reynolds numbers are more pronounced and critical in microchannels due to the relative size of roughness to channel dimensions. Surface roughness in microfluidic channels originates from the machining process during fabrication. This review examines how surface roughness, resulting from various manufacturing processes, influences the performance of microfluidic devices. Different patterns of surface roughness generated through techniques such as photolithography, etching, precision machining, and 3D printing are highlighted. These techniques yield distinct surface characteristics that affect critical microchannel properties, including fluid flow, pressure drop, and stress distribution. In addition to that, specific fabrication methods can minimize surface roughness, enhancing the performance of microchannels for applications in diagnostics, lab-on-a-chip systems, and small-scale heat exchangers are addressed. The review provides insights into selecting optimal fabrication techniques to achieve desired performance characteristics in microfluidic devices. Surface roughness ; Materials science ; Surface finish ; Composite material Surface Modification and Superhydrophobicity ; Advanced Sensor and Energy Harvesting Materials ; Fluid Dynamics and Thin Films
Authors: Cheuk Hin Ho | Timon S. Gutleb | Christoph Ortner
Source: arXiv (Cornell University) (preprint, 2024-01-03)
Field: Materials Science — Materials Chemistry

Atomic Cluster Expansion without Self-Interaction The Atomic Cluster Expansion (ACE) (Drautz, Phys. Rev. B 99, 2019) has been widely applied in high energy physics, quantum mechanics and atomistic modeling to construct many-body interaction models respecting physical symmetries. Computational efficiency is achieved by allowing non-physical self-interaction terms in the model. We propose and analyze an efficient method to evaluate and parameterize an orthogonal, or, non-self-interacting cluster expansion model. We present numerical experiments demonstrating improved conditioning and more robust approximation properties than the original expansion in regression tasks both in simplified toy problems and in applications in the machine learning of interatomic potentials. Cluster expansion ; Cluster (spacecraft) ; Construct (python library) ; Homogeneous space ; Statistical physics ; Computer science ; Energy (signal processing) ; Coupled cluster ; Quantum ; Physics ; Theoretical physics ; Quantum mechanics ; Mathematics ; Geometry Machine Learning in Materials Science ; X-ray Diffraction in Crystallography ; Electron and X-Ray Spectroscopy Techniques
Authors: Alex Berlaga | Kaylyn Torkelson | Alan Seal | Jim Pfaendtner | Andrew L. Ferguson
Source: arXiv (Cornell University) (preprint, 2024-09-09)
Field: Materials Science — Materials Chemistry

A Modular and Extensible CHARMM-Compatible Model for All-Atom Simulation of Polypeptoids Peptoids (N-substituted glycines) are a class of sequence-defined synthetic peptidomimetic polymers with applications including drug delivery, catalysis, and biomimicry. Classical molecular simulations have been used to predict and understand the conformational dynamics of single peptoid chains and their self-assembly into diverse morphologies including sheets, tubes, spheres, and fibrils. The CGenFF-NTOID model based on the CHARMM General ForceField has demonstrated success in enabling accurate all-atom molecular modeling of the structure and thermodynamic behavior of peptoids. Extension of this force field to new peptoid side chain chemistries has historically required parameterization of new side chain bonded interactions against ab initio and/or experimental data. This fitting protocol improves the accuracy of the force field but is also burdensome and time consuming, and precludes modular extensibility of the model to arbitrary peptoid sequences. In this work, we develop and demonstrate a Modular Side Chain CGenFF-NTOID (MoSiC-CGenFF-NTOID) as an extension of CGenFF-NTOID employing a modular decomposition of the peptoid backbone and side chain parameterizations wherein arbitrary side chain chemistries within the large family of substituted methyl groups (i.e., -CH3, -CH2R, -CHRR' -CRR'R'') are directly ported from CGenFF without any additional reparameterization. We validate this approach against ab initio calculations and experimental data to to develop a MoSiC-CGenFF-NTOID model for all 20 natural amino acid side chains along with 13 commonly-used synthetic side chains, and present an extensible paradigm to efficiently determine whether a novel side chain can be directly incorporated into the model or whether refitting of the CGenFF parameters is warranted. We make the model freely available to the community along with a tool to perform automated initial structure generation. Modular design ; Extensibility ; Computer science ; Atom (system on chip) ; Theoretical computer science ; Computational science ; Parallel computing ; Programming language Machine Learning in Materials Science ; Protein Structure and Dynamics ; Chemical Synthesis and Analysis
Authors: S. Balamuralitharan
Source: Communications on Applied Nonlinear Analysis (article, 2024-02-20)
Field: Materials Science — Materials Chemistry

Analyzing Symmetry in Group Theory: Applications in Crystallography Mathematics relies heavily on symmetry to study crystallography because this concept acts as an essential factor. The paper investigates group theory applications towards crystallographic symmetry investigations through examination of symmetry operations and crystallographic point groups and space groups studies. A theoretical model explains why crystal physical features including optical properties as well as elasticity and thermal conductivity derive from symmetry relationships. The research emphasizes how group theory enables progress in material science and crystallographic issue resolution. Crystallographic point group ; Point group ; Group (periodic table) ; Symmetry (geometry) ; Symmetry operation ; Group theory ; Symmetry group ; Space group ; Crystal structure Quasicrystal Structures and Properties ; High-pressure geophysics and materials ; Crystal Structures and Properties
Authors: Gleydson Fernandes de Jesus | Erico S. Teixeira | Lucas Queiroz Galvão | Maria Heloísa Fraga da Silva | Mauro Q. Nooblath Neto | Belisario E. Fernández | Clebson Cruz
Source: arXiv (Cornell University) (preprint, 2024-11-01)
Field: Chemistry — Physical and Theoretical Chemistry

Exploiting the Variational Quantum Eigensolver for Determining Ground State Energy of Protocatechuic Acid The Variational Quantum Eigensolver (VQE) is a promising hybrid algorithm, utilizing both quantum and classical computers to obtain the ground state energy of molecules. In this context, this study applies VQE to investigate the ground state of protocatechuic acid, analyzing its performance with various Ansätze and active spaces. Subsequently, all VQE results were compared to those obtained with the Hartree-Fock (HF) method. The results demonstrate that Ansätze, like unitary coupled-cluster singles and doubles (UCCSD) and variations of Hardware-Efficient, generally achieve accuracy close to that of HF. Furthermore, the increase in active space has led to the models becoming more difficult to converge to values with a greater distance from the correct energy. In summary, the findings of this study reinforce the use of VQE as a powerful tool for analyzing molecular ground state energies. Finally, the results underscore the critical importance of Ansatz selection and active space size in VQE performance, providing valuable insights into its potential and limitations. Protocatechuic acid ; Ground state ; Quantum ; State (computer science) ; Energy (signal processing) ; Computer science ; Chemistry ; Algorithm ; Physics ; Quantum mechanics ; Organic chemistry Various Chemistry Research Topics
Authors: Hannah R. Lacey | Kevin D. Dobson | Emil A. Hernández-Pagán
Source: ACS Nanoscience Au (article, 2024-11-08)
Field: Materials Science — Materials Chemistry

Flexible Cation Exchange Environment via Ligand-Free Metal Chalcogenide Thin Films Cation exchange (CE) has emerged as a premier postsynthetic method to carefully tune the chemical composition and properties of nanocrystals with excellent morphology retention. However, reaction conditions are typically dictated by the ubiquitous ligands bound to their surface, limiting their solubility and influencing the thermodynamics/kinetics of the reaction. To bypass these challenges, we report on CE reactions with Cu<sup>+</sup>, Ag<sup>+</sup>, Cu<sup>2+</sup>, Cd<sup>2+</sup>, Zn<sup>2+</sup>, and Mn<sup>2+</sup> utilizing ligand-free CdS and Cu <sub><i>x</i></sub> Se <sub><i>y</i></sub> thin films as host templates. The exchange reactions could be performed sequentially or simultaneously (i.e., two guest cations) to access compositionally diverse products. The incorporation of cations on the host films was confirmed using SEM-EDS, XPS, and ICP-MS analyses, as well as tracking wavelength shifts in the UV-vis absorption spectra. The flexibility of this approach was demonstrated as reactions were carried out using an array of different guest precursor salts and solvents with a range of polarities. Moreover, the reactions were generalizable among selenide and sulfide films and proceeded under milder conditions in comparison with reported nanocrystal reactions. A ligand-free environment with flexible reaction conditions, as the work herein, could aid in deconvoluting the different factors involved in CE reactions and further expand its use for fundamental research and applications like photovoltaics, optoelectronics, and catalysis. Chalcogenide ; Metal ; Ligand (biochemistry) ; Materials science ; Thin film ; Chemistry ; Chemical engineering ; Nanotechnology ; Optoelectronics ; Metallurgy ; Engineering Quantum Dots Synthesis And Properties ; Chalcogenide Semiconductor Thin Films ; 2D Materials and Applications
Authors: Vincent Onuegu Izionworu | W.B. Wan Nik | Mohammad Fakhratul Ridwan Zulkifli | Walid Daoudi | Mohd Sabri Mohd Ghazali | Richard Victor James
Source: International Journal of Frontiers in Engineering and Technology Research (article, 2024-04-28)
Field: Materials Science — Materials Chemistry

Corrosion inhibition of acid pickling –descaling-cleaning action on mild steel using aqueous hydroxyethyl cellulose The corrosion inhibition capability of aqueous Hydroxyethyl cellulose (HEC) on mild steel corrosion in 1 M HCl solution proposed for mild steel pickling, industrial cleaning, and descaling was evaluated at different concentrations and immersion times using gravimetric measurement. HEC demonstrated efficiency in mild steel corrosion inhibition with a maximum inhibition efficiency of 87% for a 300 ml acid pickling, industrial cleaning, and descaling solution composed of 20% aqueous solution of 0.01 M HEC and 80% of 1 M HCl solution, within an immersion time of 120 hours. The inhibition efficiency was found to increase with the increase in the concentration of HEC implying that HEC’s inhibition action is concentration and time-dependent. The mechanism of adsorption of HEC was identified to be chemisorption with hydroxyl (-OH) moiety donated to the active sites of mild steel coupled with HEC molecules encapsulation of chloride ions on mild steel surface thus preventing the corrosive action of Cl ions on the mild steel. Pickling ; Aqueous solution ; Corrosion ; Cellulose ; Chemistry ; Materials science ; Metallurgy ; Organic chemistry Corrosion Behavior and Inhibition ; Concrete Corrosion and Durability ; Hydrogen embrittlement and corrosion behaviors in metals
Authors: Nini Pryds | Neetu Lamba | Braulio Beltrán-Pitarch | Tianbo Yu | Muhamed Dawod | Alexander Berner | Benny Guralnik | Andrey Orekhov | Nicolas Gauquelin | Yaron Amouyal | Johan Verbeeck | Ole Hansen | Dirch Hjorth Petersen
Source: Research Square (preprint, 2024-04-18)
Field: Materials Science — Materials Chemistry

Thermal diffusivity microscope – zooming-in on anisotropic heat transport Thermal diffusivity ; Zoom ; Microscope ; Anisotropy ; Materials science ; Thermal ; Mechanics ; Optics ; Thermodynamics ; Physics Thermal properties of materials ; Thermal Radiation and Cooling Technologies ; Advanced Thermoelectric Materials and Devices
Authors: Prihantono Prihantono | Sulistiani Jarre | Indah Raya | Santi Santi | Kartika Paramita | Salman Ardi Syamsu | Nilam Smaradania | Muhammad Faruk
Source: Asian Pacific Journal of Cancer Prevention (article, 2024-10-01)
Field: Chemistry — Organic Chemistry

Integrated Molecular Docking and Experimental Analysis of Ni(II) Proline Dithiocarbamate Cytotoxicity in MCF-7 Breast Cancer Cells The Ni(II)ProDtc complex was successfully synthesized and demonstrates anticancer activity in MCF-7 breast cancer cells, indicating significant potential as an anticancer agent for breast cancer. MCF-7 ; Dithiocarbamate ; Cytotoxicity ; Docking (animal) ; Breast cancer ; Chemistry ; Cancer research ; Human breast ; Cancer ; Biochemistry ; In vitro ; Biology ; Internal medicine ; Medicine ; Organic chemistry Organometallic Compounds Synthesis and Characterization ; Synthesis and Characterization of Heterocyclic Compounds ; Metal complexes synthesis and properties
Authors: Benjamin Udofia | Tushar Jogi | Markus Stricker
Source: arXiv (Cornell University) (preprint, 2024-06-21)
Field: Materials Science — Materials Chemistry

Dislocation cartography: Representations and unsupervised classification of dislocation networks with unique fingerprints Detecting structure in data is the first step to arrive at meaningful representations for systems. This is particularly challenging for dislocation networks evolving as a consequence of plastic deformation of crystalline systems. Our study employs Isomap, a manifold learning technique, to unveil the intrinsic structure of high-dimensional density field data of dislocation structures from different compression axis. The resulting maps provide a systematic framework for quantitatively comparing dislocation structures, offering unique fingerprints based on density fields. Our novel, unbiased approach contributes to the quantitative classification of dislocation structures which can be systematically extended. Dislocation ; Artificial intelligence ; Cartography ; Pattern recognition (psychology) ; Computer science ; Geography ; Physics ; Condensed matter physics Microstructure and mechanical properties
Authors: C. Braxton Owens | Nithin Mathew | Tyce W. Olaveson | Jacob P. Tavenner | Edward M. Kober | Garritt J. Tucker | Gus L. W. Hart | Eric R. Homer
Source: arXiv (Cornell University) (preprint, 2024-07-30)
Field: Materials Science — Materials Chemistry

Describe, Transform, Machine Learning: Feature Engineering for Grain Boundaries and Other Variable-Sized Atom Clusters Obtaining microscopic structure-property relationships for grain boundaries are challenging because of the complex atomic structures that underlie their behavior. This has led to recent efforts to obtain these relationships with machine learning, but representing a grain boundary structure in a manner suitable for machine learning is not a trivial task. There are three key steps common to property prediction in grain boundaries and other variable-sized atom clustered structures. These are: (1) describe the atomic structure as a feature matrix, (2) transform the variable-sized feature matrices of different structures to a fixed length common to all structures, and (3) apply machine learning to predict properties from the transformed feature matrices. We examine these feature engineering steps to understand how they impact the accuracy of grain boundary energy predictions. A database of over 7000 grain boundaries serves to evaluate the different feature engineering combinations. We also examine how these combination of engineered features provide interpretability, or the ability to extract insightful physics from the obtained structure-property relationships. Feature (linguistics) ; Variable (mathematics) ; Atom (system on chip) ; Artificial intelligence ; Materials science ; Computer science ; Pattern recognition (psychology) ; Mathematics ; Parallel computing ; Philosophy ; Mathematical analysis Machine Learning in Materials Science
Authors: Vinoth Kumar Selvaraj | Jeyanthi Subramanian
Source: Research Square (preprint, 2024-04-26)
Field: Materials Science — Polymers and Plastics

Assessment of open cell bio-based flexible polyurethane composites on mechanical, thermal and electrical properties for futuristic applications: An Initiative towards net-zero carbon emissions <title>Abstract</title> This study proposes a novel approach to enhance the sustainability of polyurethane foam (PUF) by using renewable castor oil as a partial substitute for petrochemical polyols. The research focuses on developing an organic, low-density PUF reinforced with graphite nanoparticles (GNP), bamboo charcoal (BC), and zirconium oxide (ZrO<sub>2</sub>) nanoparticles. These reinforcements are incorporated using an absorption and hydrothermal reduction (AHR) technique. The resulting composite material is then evaluated for its multifunctional attributes, including density, tensile strength, flammability, and dielectric constant. The experimental results demonstrate significant improvements in the mechanical properties of the bio-based PUF, with the tensile strength increasing from 80 to 114 KPa due to the addition of nanoparticles. Moreover, the flammability tests show that while the bio-based PUF without nanoparticles achieved a UL-94 flame rating of V-2, the nanoparticle-reinforced PUF achieved higher ratings of V-0 and V-1, indicating improved flame retardancy. Furthermore, the study systematically assesses the dielectric properties of the open-cell bio-foam, comparing experimental results with a statistical experimental design. Optimization using an RSM central composite design (CCD) reveals a composition of 0.5 wt.% GNP, 0.5 wt.% ZrO<sub>2</sub>, and 2.5 wt.% BC results in a high dielectric constant of 4.95, making it suitable for effective dielectric applications. Experimental confirmation and simulation using COMSOL Multiphysics validate the optimized parameters, with error percentages of 3.12% and 2.48%, respectively. Overall, these findings underscore the potential of the proposed material as a sustainable alternative to conventional materials, aligning it with the growing demand for environmentally conscious solutions. Polyurethane ; Composite material ; Materials science ; Thermal ; Carbon fibers ; Zero (linguistics) ; Net (polyhedron) ; Composite number ; Physics ; Mathematics ; Thermodynamics Polymer composites and self-healing ; Natural Fiber Reinforced Composites
Authors: Nathan London | Siyu Bu | Britta Johnson | Nandini Ananth
Source: arXiv (Cornell University) (preprint, 2024-05-07)
Field: Materials Science — Materials Chemistry

Mean-Field Ring Polymer Rates Using a Population Dividing Surface Mean-field Ring Polymer Molecular Dynamics (MF-RPMD) offers a computationally efficient method for the simulation of reaction rates in multi-level systems. Previous work has established that, to model a nonadiabatic state-to-state reaction accurately, the dividing surface must be chosen to explicitly sample kinked ring polymer configurations where at least one bead is in a different electronic state than the others. Building on this, we introduce a population difference coordinate and a kink-constrained dividing surface, and we test the accuracy of the resulting mean-field rate theory on a series of linear vibronic coupling model systems as well as spin-boson models. We demonstrate that this new MF-RPMD rate approach is efficient to implement and quantitatively accurate for models over a wide range of driving forces, coupling strengths, and temperatures. Ring (chemistry) ; Surface (topology) ; Field (mathematics) ; Population ; Statistics ; Materials science ; Mathematics ; Geometry ; Demography ; Sociology ; Chemistry ; Pure mathematics Block Copolymer Self-Assembly
Authors: Rakesh Chandrashekar | Q. Mohammad | Madhavi Arelli | Amit Dutt | Vandana Arora Sethi | Rao A. L N
Source: E3S Web of Conferences (article, 2024-01-01)
Field: Chemistry — Organic Chemistry

RETRACTED: Enhanced Surface Protection: Microwave-Assisted Metallic Cladding of Ni-ZrO2 Mixture onto SS-304 Following the publication of the Retraction notice , this article was formally retracted on 3 April 2026. Materials science ; Cladding (metalworking) ; Metal ; Microwave ; Composite material ; Metallurgy ; Engineering ; Telecommunications Microwave-Assisted Synthesis and Applications ; Advanced ceramic materials synthesis ; Intermetallics and Advanced Alloy Properties