jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Tobias Binninger | Yin‐Ying Ting | Piotr M. Kowalski | Michael Eikerling
Source: arXiv (Cornell University) (preprint, 2024-01-04)
Field: Materials Science — Materials Chemistry

Optimization of ionic configurations in battery materials by quantum annealing Energy materials with disorder in site occupation are challenging for computational studies due to an exponential scaling of the configuration space. We herein present a grand-canonical optimization method that enables the use of quantum annealing (QA) for sampling the ionic ground state. The method relies on a Legendre transformation of the Coulomb energy cost function that strongly reduces the effective coupling strengths of the fully connected problem, which is essential for effectiveness of QA. The approach is expected to be applicable to a variety of materials optimization problems. Quantum annealing ; Coulomb ; Simulated annealing ; Scaling ; Ionic bonding ; Quantum ; Computer science ; Mathematical optimization ; Ground state ; Exponential function ; Transformation (genetics) ; Legendre transformation ; Statistical physics ; Quantum computer ; Physics ; Algorithm ; Mathematics ; Quantum mechanics ; Chemistry ; Ion ; Mathematical analysis ; Thermodynamics Machine Learning in Materials Science ; Advanced Chemical Physics Studies ; X-ray Diffraction in Crystallography
Authors: Guangjing Li | Shawn Chiu | Harry W. T. Morgan | Autumn Fuchs | А. В. Исаков | Patricia Poths | Zisheng Zhang | Anastassia N. Alexandrova | Scott L. Anderson
Source: ChemRxiv (preprint, 2024-12-15)
Field: Materials Science — Materials Chemistry

Size-dependent effects of Ge addition on the coking and sintering tendency of PtnGex/alumina(n=4,7,11) model catalysts The reactivity and adsorbate binding properties of alumina-supported Ptn and PtnGem (n/m = 4/1, 7/2, 11/4) model catalysts were studied using a combination of ethylene and CO temperatureprogrammed desorption (TPD), He+ ion scattering (ISS), and detailed density functional theory (DFT). The Ptn/alumina catalysts gradually deactivated in repeated CO TPD runs and deactivated more rapidly in repeated ethylene TPD runs due to the effects of sintering and carbon deposition (coking). PtnGem/alumina catalysts were dramatically more stable against deactivation by both sintering and coking. Carbon addition to Ptn/alumina also increased stability against sintering, but not coking. Ion scattering was used to probe the nature of adsorbate binding, including the effects of both carbon and Ge addition on the accessibility of strong Pt-associated binding sites for ethylene and CO. DFT was used to examine the electronic and geometric structures and ethylene and CO binding properties of Ptn (n = 4, 7) with added Ge, carbon, or both. Consistent with the ISS results, DFT shows that loss of strong adsorbate binding sites mostly resulted from changes to the electronic properties of the clusters, rather than simple blocking of binding sites by Ge or carbon Sintering ; Catalysis ; Materials science ; Coke ; Business ; Chemical engineering ; Metallurgy ; Chemistry ; Engineering ; Organic chemistry Catalytic Processes in Materials Science ; Zeolite Catalysis and Synthesis ; Catalysis and Oxidation Reactions
Authors: Marwa M. Abdelhameed | Tawfik A. Khattab | Yasser A. Attia
Source: Egyptian Journal of Chemistry (article, 2024-09-30)
Field: Materials Science — Polymers and Plastics

Development of electroconductive colorless films using printing technology toward flexible electronics The promising and remarkable qualities of graphene have piqued curiosity, making it a viable alternative to many standard materials in a variety of applications including conductive ink which used in construction of flexible electronics. Many methods have been applied to produce graphene-based conductive inks to print flexible substrates. Diverse flexible electronic devices have been reported during the last ten years. The development of graphene-based ink is discussed, focusing on the type of the graphene-like materials used in the conductive ink as well as the composition and properties of these inks. The second objective of this study is clarifying the advantages and disadvantages of graphene-based ink and comparing it with its counterparts from other electrically conductive materials like silver (Ag), gold (Au), and copper (Cu) nanoparticles (NPs), as well as carbon nanotubes and conducting polymers. Additionally, this work discussed graphene hybrid-based inks using various types of metallic nanoparticles to enhance the characteristics of conducting ink. Electronics ; Materials science ; Nanotechnology ; Polymer science ; Engineering ; Electrical engineering Conducting polymers and applications
Authors: Md. Menhazul Abedin | Koji Tabata | Yoshihiro Matsumura | Tamiki Komatsuzaki
Source: The Journal of Chemical Physics (article, 2024-07-03)
Field: Materials Science — Materials Chemistry

Multi-armed bandit algorithm for sequential experiments of molecular properties with dynamic feature selection Sequential optimization is one of the promising approaches in identifying the optimal candidate(s) (molecules, reactants, drugs, etc.) with desired properties (reaction yield, selectivity, efficacy, etc.) from a large set of potential candidates, while minimizing the number of experiments required. However, the high dimensionality of the feature space (e.g., molecular descriptors) makes it often difficult to utilize the relevant features during the process of updating the set of candidates to be examined. In this article, we developed a new sequential optimization algorithm for molecular problems based on reinforcement learning, multi-armed linear bandit framework, and online, dynamic feature selections in which relevant molecular descriptors are updated along with the experiments. We also designed a stopping condition aimed to guarantee the reliability of the chosen candidate from the dataset pool. The developed algorithm was examined by comparing with Bayesian optimization (BO), using two synthetic datasets and two real datasets in which one dataset includes hydration free energy of molecules and another one includes a free energy difference between enantiomer products in chemical reaction. We found that the dynamic feature selection in representing the desired properties along the experiments provides a better performance (e.g., time required to find the best candidate and stop the experiment) as the overall trend and that our multi-armed linear bandit approach with a dynamic feature selection scheme outperforms the standard BO with fixed feature variables. The comparison of our algorithm to BO with dynamic feature selection is also addressed. Curse of dimensionality ; Feature (linguistics) ; Computer science ; Feature selection ; Set (abstract data type) ; Bayesian optimization ; Algorithm ; Reinforcement learning ; Artificial intelligence ; Pattern recognition (psychology) Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Advanced Multi-Objective Optimization Algorithms
Authors: M.C. López-Escalante | M. Valle Martínez de Yuso | Ana Cuevas | J. Benavente
Source: Micromachines (article, 2024-05-31)
Field: Materials Science — Materials Chemistry

Optical Modification of a Nanoporous Alumina Structure Associated with Surface Coverage by the Ionic Liquid AliquatCl This manuscript analyses changes in the optical parameters of a commercial alumina nanoporous structure (Anodisc<sup>TM</sup> or AND support) due to surface coverage by the ionic liquid (IL) AliquatCl (AlqCl). XPS measurements were performed for chemical characterization of the composite AND/AlqCl and the AND support, but XPS resolved angle analysis (from 15° to 75°) was carried out for the homogeneity estimation of the top surface of the ANDAlqCl sample. Optical characterization of both the composite AND/AlqCl and the AND support was performed by three non-destructive and non-invasive techniques: ellipsometry spectroscopy (SE), light transmittance/reflection, and photoluminescence. SE measurements (wavelength ranging from 250 nm to 1250 nm) allow for the determination of the refraction index of the AND/AlqCl sample, which hardly differs from that corresponding to the IL, confirming the XPS results. The presence of the IL significantly increases the light transmission of the alumina support in the visible region and reduces reflection, affecting also the maximum position of this latter curve, as well as the photoluminescence spectra. Due to these results, illuminated I-V curves for both the composite AND/AlqCl film and the AND support were also measured to estimate its possible application as a solar cell. The optical behaviour exhibited by the AND/AlqCl thin film in the visible region could be of interest for different applications. X-ray photoelectron spectroscopy ; Materials science ; Ellipsometry ; Photoluminescence ; Refractive index ; Nanoporous ; Transmittance ; Analytical Chemistry (journal) ; Optics ; Homogeneity (statistics) ; Thin film ; Spectroscopy ; Ionic liquid ; Optoelectronics ; Nanotechnology ; Chemistry ; Chemical engineering Mesoporous Materials and Catalysis ; Semiconductor materials and devices ; Catalytic Processes in Materials Science
Authors: J. Michael McBride | Aleksei Koshevarnikov | Marta Siek | Bartosz A. Grzybowski | Tsvi Tlusty
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2024-07-19)
Field: Materials Science — Biomaterials

Statistical Survey of Chemical and Geometric Patterns on Protein Surfaces as a Blueprint for Protein-mimicking Nanoparticles Despite recent breakthroughs in understanding how protein sequence relates to structure and function, considerably less attention has been paid to the general features of protein surfaces beyond those regions involved in binding and catalysis. This paper provides a systematic survey of the universe of protein surfaces and quantifies the sizes, shapes, and curvatures of the positively/negatively charged and hydrophobic/hydrophilic surface patches as well as correlations between such patches. It then compares these statistics with the metrics characterizing nanoparticles functionalized with ligands terminated with positively and negatively charged ligands. These particles are of particular interest because they are also surface-patchy and have been shown to exhibit both antibiotic and anticancer activities – via selective interactions against various cellular structures – prompting loose analogies to proteins. Our analyses support such analogies in several respects (e.g., patterns of charged protrusions and hydrophobic niches similar to those observed in proteins), although there are also significant differences. Looking forward, this work provides a blueprint for the rational design of synthetic nanoobjects with further enhanced mimicry of proteins’ surface properties. Blueprint ; Statistical survey ; Nanoparticle ; Nanotechnology ; Statistical analysis ; Computer science ; Materials science ; Engineering ; Mathematics ; Statistics ; Mechanical engineering Diatoms and Algae Research ; nanoparticles nucleation surface interactions
Authors: John Communications | I-Yun Hsiao | Yoshiaki Teranishi | Hiroki Nakamura | Chaithanya Hareendran | Parth Shaligram | Rajesh Gonnade | T Ajithkumar | Abdul Malhan | Krishnan Thirumoorthy | Ching-Hung Wu | Ling-Hua Huang | Chi-Chung Hua | Jiaqi Li | Xinlu Cheng | Hong Zhang | Zhang Wu | Rumeng Liu | Ning Wei | Lifeng Wang | Yuting Bai | Derek Hao | Sisi Feng | Liping Lu | Qi Wang | Xiao-Xiao Jose garc a-Calvo | Naomi Chen | Stefan Sakai | Toma s Matile | Torres
Source: Physical Chemistry Chemical Physics (article, 2024-01-01)
Field: Materials Science — Materials Chemistry

Contents list Permissions Request permissions Contents list Phys. Chem. Chem. Phys., 2024, 26, 3671 DOI: 10.1039/D4CP90024C This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. You can use material from this article in other publications without requesting further permissions from the RSC, provided that the correct acknowledgement is given. Read more about how to correctly acknowledge RSC content. Chemistry Chemical and Physical Properties of Materials ; Advanced Physical and Chemical Molecular Interactions ; Machine Learning in Materials Science
Authors: Qi Zhang | Amitava Choudhury | Aleksandr Chernatynskiy
Source: arXiv (Cornell University) (preprint, 2024-07-31)
Field: Materials Science — Materials Chemistry

A symmetry-oriented crystal structure prediction method for crystals with rigid bodies We have developed an efficient crystal structure prediction (CSP) method for desired chemical compositions, specifically suited for compounds featuring recurring molecules or rigid bodies. We applied this method to two metal chalcogenides: $\text{Li}_3\text{PS}_4$ and $\text{Na}_6\text{Ge}_2\text{Se}_6$, treating $\text{PS}_4$ as a tetrahedral rigid body and $\text{Ge}_2\text{Se}_6$ as an ethane-like dimer rigid body. Initial trials not only identified the experimentally observed structures of these compounds but also uncovered several novel phases, including a new stannite-type $\text{Li}_3\text{PS}_4$ structure and a potential metastable structure for $\text{Na}_6\text{Ge}_2\text{Se}_6$ that exhibits significantly lower energy than the observed phase, as evaluated by density functional theory (DFT) calculations. We compared our results with those obtained using USPEX, a popular CSP package leveraging genetic algorithms. Both methods predicted the same lowest energy structures in both compounds. However, our method demonstrated better performance in predicting metastable structures. The method is implemented with Python code which is available at https://github.com/ColdSnaap/sgrcsp.git. Symmetry (geometry) ; Crystal structure ; Crystal (programming language) ; Crystallography ; Materials science ; Theoretical physics ; Physics ; Condensed matter physics ; Geometry ; Computer science ; Mathematics ; Chemistry Machine Learning in Materials Science
Authors: Hio‐Ieng Un | Kamil Iwanowski | Jordi Ferrer Orri | Ian E. Jacobs | Naoya Fukui | David Cornil | David Beljonne | Michele Simoncelli | Hiroshi Nishihara | Henning Sirringhaus
Source: arXiv (Cornell University) (preprint, 2024-10-15)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Defect-tolerant electron and defect-sensitive phonon transport in quasi-2D conjugated coordination polymers Thermoelectric materials, enabling direct waste-heat to electricity conversion, need to be highly electrically conducting while simultaneously thermally insulating. This is fundamentally challenging since electrical and thermal conduction are usually coupled. Here, we discover that quasi-2D conjugated coordination polymer films exhibit this ideal mix of antithetical properties due to coexistence of defect-tolerant charge transport and defect-sensitive heat propagation. The former is highlighted by the highest conductivities &gt; 2000 S cm-1 with metallic temperature dependence observed in disordered films with paracrystallinity &gt; 10%, while the latter manifests in low, temperature-activated lattice thermal conductivities (&lt; 0.38 W m-1 K-1) originating from small-amplitude, quasi-harmonic lattice dynamics with disorder-limited lifetimes and vibrational scattering length on the order of interatomic spacing. Based on temperature-dependent thermoelectric and magnetotransport experiments we identify a two-carrier (hole-electron), ambipolar metallic transport regime as the origin of relatively small Seebeck coefficients in these materials. Our findings identify conjugated coordination polymers as attractive materials for applications in thermoelectric energy harvesting, (bio)electronics and energy storage. Conjugated system ; Phonon ; Polymer ; Electron ; Materials science ; Condensed matter physics ; Chemical physics ; Physics ; Quantum mechanics ; Composite material Organic and Molecular Conductors Research ; Metal-Organic Frameworks: Synthesis and Applications ; Conducting polymers and applications
Authors: Asmaa Ahmed Hatem Sultan | Rana Jalal Shaker
Source: International Journal of Health and Medical Sciences (article, 2024-01-01)
Field: Materials Science — Materials Chemistry

Green Synthesis of NiO-CoO Nanocomposites and its Antibacterial Activity This research aims to manufacture and characterize green synthesis in this study, nano-solutions were prepared by the green synthesis method, using nickel nitrate with saffron and cobalt nitrate with aloe vera as raw materials.Then various physical analyses and measurements were carried out, such as XRD, SEM, TEM, UV-Vis, and FTIR.The X-ray diffraction (XRD) study showed the films, which were deposited on a glass substrate by drop casting method, have a polycrystalline structure with a cubic phase.The morphological surface of the Nano composites was studied by a scanning electron microscope; the particles were of irregular shapes and microscopic sizes, with an average diameter of about 127 nm.From the results of the transmission electron microscope, it is found that the shape of the particles is spherical and the average size of the particles ranged between 12-20 nm.NiO-CoO formation with high purity phase confirmed by Fourier transform infrared (FT-IR) spectra.UV-Visb spectrum was used to study the optical properties, where the bandgap of the Nanocomposites (nickel oxide with cobalt oxide) was 2.75 eV.The Nanocomposites are investigated against the anti-bacterial activity of Staphylococcus aureus and Pseudomonas aerogenes, where it recorded good efficacy and within the permissible specifications.It can be used as a treatment against bacterial species that have multiple resistance to antibiotics in skin infections caused by burns. Non-blocking I/O ; Nanocomposite ; Antibacterial activity ; Materials science ; Chemical engineering ; Nuclear chemistry ; Chemistry ; Nanotechnology ; Catalysis ; Organic chemistry ; Geology ; Engineering Magnesium Oxide Properties and Applications ; Nanoparticles: synthesis and applications ; Pigment Synthesis and Properties
Authors: C. Y. Janey Wang | Mao Ye | Ruiting Tu | Lanjingting Li | Kean Pei | Y. Thomas Hou
Source: International Journal of Materials Science and Technology Studies (article, 2024-12-10)
Field: Materials Science — Polymers and Plastics

Polymer Advancements in Renewable Energy Technologies: Bridging Sustainability and Practicality Renewable energy technologies have seen substantial progress in recent years, with solar, wind, and water becoming key sustainable energy sources. Solar photovoltaic technology, in particular, has advanced significantly, driving down costs and making renewable energy more economically viable across many regions. Despite these advancements, challenges such as technological maturity, high costs, and inefficiencies in energy storage and transmission continue to hinder widespread adoption. Conductive polymers have emerged as promising materials to address these challenges, particularly in enhancing organic solar cell efficiency. Their lightweight and flexible properties make them ideal for portable and adaptable energy applications. Structural modifications, including adjustments to conjugation lengths, side chains, and the incorporation of nanomaterials, have improved light absorption, charge transport, and overall energy conversion efficiency. This review explores the critical role of polymers in renewable energy technologies, focusing on their application in solar cells, energy storage, and sustainable material design. It highlights innovative approaches to polymer development, such as nanocomposite integration and chemical modifications, which have enabled significant advancements in energy efficiency and sustainability. By addressing current challenges and uncovering future potential, this study emphasizes the importance of polymers in driving the transition to renewable energy systems. Bridging (networking) ; Sustainability ; Renewable energy ; Computer science ; Engineering ; Electrical engineering Polymer Science and PVC
Authors: F E Abeng
Source: Portugaliae electrochimica acta (article, 2024-01-01)
Field: Materials Science — Materials Chemistry

Experimental Study and Response Surface Methodology of Azo Dye as an Eco-Friendly Corrosion Inhibitor for Stainless Steel in a Chloride Solution DAD was investigated as CI for SS corrosion in a 3.5% NaCl solution, using WL, thermometric and RSM techniques.The analyses results show that IE(%) of DAD was dependent on its Ct and T. The highest IE(%) values were recorded on 5.0 g/L, at 303 K, by thermometric and WL methods (90.0 and 98%, respectively).DAD adsorption onto the SS surface was found to be spontaneous, obeyed Langmuir's isotherm, and its mechanism appeared to be partly physical, partly chemical.The results of RSM techniques supported experimental data.Finally, SEM was used to examine SS surfaces morphology without and with DAD, and its results confirmed the CI process. Corrosion ; Chloride ; Corrosion inhibitor ; Materials science ; Environmentally friendly ; Metallurgy Corrosion Behavior and Inhibition
Authors: Chee Sien Wong | Benediktus Madika | Jiwon Yeom | Youngwoo Choi | Seungbum Hong
Source: arXiv (Cornell University) (preprint, 2024-05-13)
Field: Materials Science — Materials Chemistry

Crystal Structure-Based Multioutput Property Prediction of Lithium Manganese Nickel Oxide using EfficientNet-B0 Here, we present an EfficientNet-B0-based model to directly predict multiple properties of lithium manganese nickel oxides (LMNO) using their crystal structure images. The model is supposed to predict the energy above the convex hull, bandgap energy, crystal systems, and crystal space groups of LMNOs. In the last layer of the model, a linear function is used to predict the bandgap energy and energy above the convex hull, while a SoftMax function is used to classify the crystal systems and crystal space groups. In the test set, the percentages of coefficient of determination (R2) scores are 97.73% and 96.50% for the bandgap energy and energy above the convex hull predictions, respectively, while the percentages of accuracy are 99.45% and 99.27% for the crystal system and crystal space group classifications, respectively. The class saliency maps explain that the model pays more attention to the shape of the crystal lattices and gradients around the lattice region occupied by the larger ions. This work provides new insight into using an intelligent model to directly relate the crystal structures of LMNO materials with their properties. Manganese ; Nickel ; Lithium (medication) ; Property (philosophy) ; Materials science ; Manganese oxide ; Metallurgy ; Philosophy Machine Learning in Materials Science ; Extraction and Separation Processes ; Geochemistry and Geologic Mapping