jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Katja‐Sophia Csizi | Markus Reiher
Source: Wiley Interdisciplinary Reviews Computational Molecular Science (article, 2023-02-01)
Field: Materials Science — Materials Chemistry

Universal<scp>QM</scp>/<scp>MM</scp>approaches for general nanoscale applications Abstract Quantum mechanics/molecular mechanics (QM/MM) hybrid models allow one to address chemical phenomena in complex molecular environments. Whereas this modeling approach can cope with a large system size at moderate computational costs, the models are often tedious to construct and require manual preprocessing and expertise. As a result, transferability to new application areas can be limited and the many parameters are not easy to adjust to reference data that are typically scarce. Therefore, it is desirable to devise automated procedures of controllable accuracy, which enables such modeling in a standardized and black‐box‐type manner. Although diverse best‐practice protocols have been set up for the construction of individual components of a QM/MM model (e.g., the MM potential, the type of embedding, the choice of the QM region), automated procedures that reconcile all steps of the QM/MM model construction are still rare. Here, we review the state of the art of QM/MM modeling with a focus on automation. We elaborate on MM model parametrization, on atom‐economical physically‐motivated QM region selection, and on embedding schemes that incorporate mutual polarization as critical components of the QM/MM model. In view of the broad scope of the field, we mostly restrict the discussion to methodologies that build de novo models based on first‐principles data, on uncertainty quantification, and on error mitigation with a high potential for automation. Ultimately, it is desirable to be able to set up reliable QM/MM models in a fast and efficient automated way without being constrained by specific chemical or technical limitations. This article is categorized under: Electronic Structure Theory &gt; Combined QM/MM Methods Computer science ; QM/MM ; Embedding ; Automation ; Multiscale modeling ; Set (abstract data type) ; Model selection ; Theoretical computer science ; Distributed computing ; Artificial intelligence ; Molecular dynamics ; Chemistry ; Engineering ; Programming language Machine Learning in Materials Science ; Advanced Chemical Physics Studies ; Computational Drug Discovery Methods
Authors: Lu Liu | Guangcai Shao | Chuanlong Ma | Anton Nikiforov | Nathalie De Geyter | Rino Morent
Source: Journal of Hazardous Materials (review, 2023-02-27)
Field: Materials Science — Materials Chemistry

Plasma-catalysis for VOCs decomposition: A review on micro- and macroscopic modeling Decomposition ; Catalysis ; Plasma ; Biochemical engineering ; Chemistry ; Nanotechnology ; Process engineering ; Materials science ; Organic chemistry ; Engineering ; Physics Catalytic Processes in Materials Science ; Plasma Applications and Diagnostics ; Gas Sensing Nanomaterials and Sensors
Authors: Özge Payanda Konuk | Ala Abdulalem Abdo Moqbel Alsuhile | Hamed Yousefzadeh | Zeynep Ülker | Selmi Erim Bozbağ | Carlos A. García‐González | Ирина Смирнова | Can Erkey
Source: Frontiers in Chemistry (review, 2023-10-23)
Field: Chemistry — Spectroscopy

The effect of synthesis conditions and process parameters on aerogel properties Aerogels are remarkable nanoporous materials with unique properties such as low density, high porosity, high specific surface area, and interconnected pore networks. In addition, their ability to be synthesized from various precursors such as inorganics, organics, or hybrid, and the tunability of their properties make them very attractive for many applications such as adsorption, thermal insulation, catalysts, tissue engineering, and drug delivery. The physical and chemical properties and pore structure of aerogels are crucial in determining their application areas. Moreover, it is possible to tailor the aerogel properties to meet the specific requirements of each application. This review presents a comprehensive review of synthesis conditions and process parameters in tailoring aerogel properties. The effective parameters from the dissolution of the precursor step to the supercritical drying step, including the carbonization process for carbon aerogels, are investigated from the studies reported in the literature. Aerogel ; Supercritical drying ; Carbonization ; Materials science ; Nanoporous ; Supercritical fluid ; Porosity ; Specific surface area ; Adsorption ; Chemical engineering ; Nanotechnology ; Dissolution ; Process (computing) ; Catalysis ; Composite material ; Organic chemistry ; Chemistry ; Computer science Aerogels and thermal insulation ; Mesoporous Materials and Catalysis ; Catalytic Processes in Materials Science
Authors: Jesús Carrete | Hadrián Montes‐Campos | Ralf Wanzenböck | Esther Heid | Georg K. H. Madsen
Source: The Journal of Chemical Physics (article, 2023-05-22)
Field: Materials Science — Materials Chemistry

Deep ensembles vs committees for uncertainty estimation in neural-network force fields: Comparison and application to active learning A reliable uncertainty estimator is a key ingredient in the successful use of machine-learning force fields for predictive calculations. Important considerations are correlation with error, overhead during training and inference, and efficient workflows to systematically improve the force field. However, in the case of neural-network force fields, simple committees are often the only option considered due to their easy implementation. Here, we present a generalization of the deep-ensemble design based on multiheaded neural networks and a heteroscedastic loss. It can efficiently deal with uncertainties in both energy and forces and take sources of aleatoric uncertainty affecting the training data into account. We compare uncertainty metrics based on deep ensembles, committees, and bootstrap-aggregation ensembles using data for an ionic liquid and a perovskite surface. We demonstrate an adversarial approach to active learning to efficiently and progressively refine the force fields. That active learning workflow is realistically possible thanks to exceptionally fast training enabled by residual learning and a nonlinear learned optimizer. Computer science ; Artificial neural network ; Artificial intelligence ; Machine learning ; Inference ; Deep learning ; Estimator ; Workflow ; Force field (fiction) ; Generalization ; Active learning (machine learning) ; Mathematics Machine Learning in Materials Science ; Electronic and Structural Properties of Oxides ; Advanced Memory and Neural Computing
Authors: Marco Deluca | Hailong Hu | Maxim N. Popov | Jürgen Spitaler | Thomas Dieing
Source: Communications Materials (article, 2023-10-09)
Field: Materials Science — Materials Chemistry

Advantages and developments of Raman spectroscopy for electroceramics Abstract Despite being applied with success in many fields of materials science, Raman spectroscopy is not yet determinant in the study of electroceramics. Recent experimental and theoretical developments, however, should increase the popularity of Raman spectroscopy in this class of materials. In this review, we outline the fields of application of Raman spectroscopy and microscopy in various electroceramic systems, defining current key bottlenecks and explaining promising recent developments. We focus our attention on recent experimental developments, including coupling Raman spectroscopy with other methodologies and modelling approaches involving both the model-based data interpretation and the ab initio calculation of realistic Raman spectra. Raman spectroscopy ; Spectroscopy ; Materials science ; Nanotechnology ; Physics ; Optics Ferroelectric and Piezoelectric Materials ; Electronic and Structural Properties of Oxides ; Semiconductor materials and devices
Authors: Nisreen S. Ali | Issam K. Salih | Hamed N. Harharah | Hasan Sh. Majdi | Hussein G. Salih | Khairi R. Kalash | Ali Al‐Shathr | Farah T. Al-Sudani | Mahir A. Abdulrahman | Jamal M. Ali | Talib M. Albayati | Noori M. Cata Saady | Sohrab Zendehboudi
Source: Catalysts (article, 2023-07-22)
Field: Chemistry — Inorganic Chemistry

Utilization of Loaded Cobalt onto MCM-48 Mesoporous Catalyst as a Heterogeneous Reaction in a Fixed Bed Membrane Reactor to Produce Isomerization Product from n-Heptane The use of catalytic membranes as microstructured reactors without a separative function has proved effective. High catalytic activity is possible with minimal mass transport resistances if the reactant mixture is pushed to flow through the pores of a membrane that has been impregnated with catalyst. In this study, n-heptane (C7H16) was hydrocracked and hydro-isomerized within a plug-flow zeolitic catalytic membrane-packed bed reactor. The metallic cobalt (Co) precursor at 3 wt.% was loaded onto support mesoporous materials MCM-48 to synthesize heterogeneous catalysis. The prepared MCM-48 was characterized by utilizing characterization techniques such as scanning electron microscopy (SEM), X-ray diffraction (XRD), energy dispersive X-ray analysis (EDAX), Fourier transform infrared (FTIR), nitrogen adsorption–desorption isotherms, and the Brunauer–Emmett–Teller (BET) surface area. The structural and textural characteristics of MCM-48 after encapsulation with Co were also investigated. The analyses were performed before and after metal loading. According to the results, the 3 wt.% Co/MCM-48 of metallic catalyst in a fixed bed membrane reactor (MR) appears to have an excellent catalytic activity of ~83% during converting C7H16 at 400 °C, whereas a maximum selectivity was approximately ~65% at 325 °C. According to our findings, the synthesized catalyst exhibits an acceptable selectivity to isomers with multiple branches, while making low aromatic components. In addition, a good catalytic stability was noticed for this catalyst over the reaction. Use of 3 wt.% Co/MCM-48 catalyst led to the highest isomerization selectivity as well as n-heptane conversion. Therefore, the heterogeneous catalysis MCM-48 is a promising option/ alternative for traditional hydrocracking and hydro-isomerization processes. Catalysis ; Mesoporous material ; Cobalt ; Isomerization ; Selectivity ; Materials science ; Chemical engineering ; Membrane ; Heptane ; Heterogeneous catalysis ; Chemistry ; Inorganic chemistry ; Organic chemistry Zeolite Catalysis and Synthesis ; Mesoporous Materials and Catalysis ; Catalysis and Hydrodesulfurization Studies
Authors: Sayan Ganguly | Shlomo Margel
Source: Pharmaceutics (review, 2023-02-17)
Field: Materials Science — Biomaterials

Bioimaging Probes Based on Magneto-Fluorescent Nanoparticles Novel nanomaterials are of interest in biology, medicine, and imaging applications. Multimodal fluorescent-magnetic nanoparticles demand special attention because they have the potential to be employed as diagnostic and medication-delivery tools, which, in turn, might make it easier to diagnose and treat cancer, as well as a wide variety of other disorders. The most recent advancements in the development of magneto-fluorescent nanocomposites and their applications in the biomedical field are the primary focus of this review. We describe the most current developments in synthetic methodologies and methods for the fabrication of magneto-fluorescent nanocomposites. The primary applications of multimodal magneto-fluorescent nanoparticles in biomedicine, including biological imaging, cancer treatment, and drug administration, are covered in this article, and an overview of the future possibilities for these technologies is provided. Nanotechnology ; Biomedicine ; Drug delivery ; Magnetic nanoparticles ; Nanomaterials ; Materials science ; Nanoparticle ; Computer science ; Bioinformatics ; Biology Nanoparticle-Based Drug Delivery ; Advanced biosensing and bioanalysis techniques ; Gold and Silver Nanoparticles Synthesis and Applications
Authors: Kaitlin M. Hartung | Ellen M. Sletten
Source: Chem (article, 2023-06-05)
Field: Chemistry — Organic Chemistry

Bioorthogonal chemistry: Bridging chemistry, biology, and medicine Bridging (networking) ; Bioorthogonal chemistry ; Chemistry ; Nanotechnology ; Computational biology ; Combinatorial chemistry ; Biology ; Computer science ; Click chemistry ; Materials science Click Chemistry and Applications ; Chemical Synthesis and Analysis ; Monoclonal and Polyclonal Antibodies Research
Authors: Mohammad Rezayat | Mojtaba Karamimoghadam | Mahmoud Moradi | Giuseppe Casalino | J.J. Roa | A. Mateo
Source: Metals (article, 2023-07-14)
Field: Materials Science — Metals and Alloys

Overview of Surface Modification Strategies for Improving the Properties of Metastable Austenitic Stainless Steels Metastable austenitic stainless steels (MASS) are widely used in various industrial applications due to their exceptional compromise between mechanical properties and corrosion resistance. However, the mechanical properties of these materials can be further enhanced by surface treatments. This paper reviews various surface treatment methodologies used to improve the mechanical properties of MASS, with particular attention to laser treatments. The effects of these surface treatments on the microstructure and chemical composition in the thermal affected zone of the MASS are discussed, and their impact on the material’s mechanical properties, such as hardness, tensile strength, and fatigue life, are investigated in detail. Additionally, the paper highlights the limitations of these surface treatments and points out some areas where further research is needed. The findings presented can be used to guide the selection of appropriate surface treatment techniques for specific applications, ultimately improving the performance and lifespan of MASS in various industrial settings. Materials science ; Surface modification ; Austenite ; Ultimate tensile strength ; Microstructure ; Metastability ; Corrosion ; Metallurgy ; Austenitic stainless steel ; Composite material ; Mechanical engineering ; Engineering Hydrogen embrittlement and corrosion behaviors in metals ; High Entropy Alloys Studies ; Surface Treatment and Residual Stress
Authors: Lim Heo | Michael Feig
Source: Structure (article, 2023-11-23)
Field: Materials Science — Materials Chemistry

One bead per residue can describe all-atom protein structures Resolution (logic) ; Computer science ; Amino acid residue ; Biological system ; Algorithm ; Atom (system on chip) ; Chemistry ; Artificial intelligence ; Peptide sequence ; Biology Enzyme Structure and Function ; Advanced Electron Microscopy Techniques and Applications ; Protein Structure and Dynamics
Authors: Z.H. Zhang | Hongyu Shi | Luyi Wang | Juan Chen | Xiaoming Chen | Jianjia Yi | Anxue Zhang | Haiwen Liu
Source: Nanomaterials (review, 2023-01-28)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Recent Advances in Reconfigurable Metasurfaces: Principle and Applications Metasurfaces have shown their great capability to manipulate electromagnetic waves. As a new concept, reconfigurable metasurfaces attract researchers' attention. There are many kinds of reconfigurable components, devices and materials that can be loaded on metasurfaces. When cooperating with reconfigurable structures, dynamic control of the responses of metasurfaces are realized under external excitations, offering new opportunities to manipulate electromagnetic waves dynamically. This review introduces some common methods to design reconfigurable metasurfaces classified by the techniques they use, such as special materials, semiconductor components and mechanical devices. Specifically, this review provides a comparison among all the methods mentioned and discusses their pros and cons. Finally, based on the unsolved problems in the designs and applications, the challenges and possible developments in the future are discussed. Computer science ; Metamaterial ; Electronic engineering ; Computer architecture ; Engineering ; Physics ; Optoelectronics Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Antenna Design and Analysis
Authors: Dong-Min Jeon | Kilsoo Shin | Seong‐Won Moon | Junsuk Rho
Source: Nano Convergence (review, 2023-05-24)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Recent advancements of metalenses for functional imaging Metasurfaces can modulate light with periodically arranged subwavelength scatterers, and they can generate arbitrary wavefronts. Therefore, they can be used to realize various optical components. In particular, metasurfaces can be used to realize lenses, so-called metalenses. In the last decade, metalenses have been actively studied and developed. In this review, we firstly introduce the fundamental principles of metalenses in terms of materials, phase modulation method, and design method. Based on these principles, the functionalities and the applications can consequently be realized. Metalenses have a much larger number of degrees of freedom compared with that of existing refractive or diffractive lenses. Thus, they afford functionalities such as tunability, high numerical aperture, and aberration correction. Metalenses with these functionalities can be applied in various optical systems such as imaging systems and spectrometers. Finally, we discuss the future applications of metalenses. Computer science Metamaterials and Metasurfaces Applications ; Advanced Memory and Neural Computing ; Molecular Communication and Nanonetworks
Authors: Sébastien Leblanc | Feriel Yala | Nicolas Provencher | Jean‐François Lucier | Maxime Levesque | Xavier Lapointe | Jean‐François Jacques | Isabelle Fournier | Michel Salzet | Aïda Ouangraoua | Michelle S. Scott | François‐Michel Boisvert | Marie A. Brunet | Xavier Roucou
Source: Nucleic Acids Research (article, 2023-11-13)
Field: Chemistry — Spectroscopy

OpenProt 2.0 builds a path to the functional characterization of alternative proteins The OpenProt proteogenomic resource (https://www.openprot.org/) provides users with a complete and freely accessible set of non-canonical or alternative open reading frames (AltORFs) within the transcriptome of various species, as well as functional annotations of the corresponding protein sequences not found in standard databases. Enhancements in this update are largely the result of user feedback and include the prediction of structure, subcellular localization, and intrinsic disorder, using cutting-edge algorithms based on machine learning techniques. The mass spectrometry pipeline now integrates a machine learning-based peptide rescoring method to improve peptide identification. We continue to help users explore this cryptic proteome by providing OpenCustomDB, a tool that enables users to build their own customized protein databases, and OpenVar, a genomic annotator including genetic variants within AltORFs and protein sequences. A new interface improves the visualization of all functional annotations, including a spectral viewer and the prediction of multicoding genes. All data on OpenProt are freely available and downloadable. Overall, OpenProt continues to establish itself as an important resource for the exploration and study of new proteins. Pipeline (software) ; Proteome ; Biology ; Computational biology ; Computer science ; Visualization ; Resource (disambiguation) ; Open reading frame ; Proteogenomics ; Identification (biology) ; Interface (matter) ; Set (abstract data type) ; Genome ; Artificial intelligence ; Bioinformatics ; Genomics ; Gene ; Peptide sequence ; Genetics ; Programming language Advanced Proteomics Techniques and Applications ; RNA and protein synthesis mechanisms ; Machine Learning in Bioinformatics
Authors: Jennifer G. Abelin | Erik J. Bergstrom | Keith Rivera | Hannah B. Taylor | Susan Klaeger | Charles Xu | Eva K. Verzani | C. Jackson White | Hilina Woldemichael | Maya Virshup | Meagan E. Olive | Myranda Maynard | Stephanie Vartany | Joseph D. Allen | Kshiti Meera Phulphagar | M. Harry Kane | Suzanna Rachimi | D.R. Mani | Michael A. Gillette | Shankha Satpathy | Karl R. Clauser | Namrata D. Udeshi | Steven A. Carr
Source: Nature Communications (article, 2023-04-03)
Field: Chemistry — Spectroscopy

Workflow enabling deepscale immunopeptidome, proteome, ubiquitylome, phosphoproteome, and acetylome analyses of sample-limited tissues Serial multi-omic analysis of proteome, phosphoproteome, and acetylome provides insights into changes in protein expression, cell signaling, cross-talk and epigenetic pathways involved in disease pathology and treatment. However, ubiquitylome and HLA peptidome data collection used to understand protein degradation and antigen presentation have not together been serialized, and instead require separate samples for parallel processing using distinct protocols. Here we present MONTE, a highly sensitive multi-omic native tissue enrichment workflow, that enables serial, deep-scale analysis of HLA-I and HLA-II immunopeptidome, ubiquitylome, proteome, phosphoproteome, and acetylome from the same tissue sample. We demonstrate that the depth of coverage and quantitative precision of each 'ome is not compromised by serialization, and the addition of HLA immunopeptidomics enables the identification of peptides derived from cancer/testis antigens and patient specific neoantigens. We evaluate the technical feasibility of the MONTE workflow using a small cohort of patient lung adenocarcinoma tumors. Proteome ; Workflow ; Computational biology ; Computer science ; Biology ; Chemistry ; Bioinformatics ; Database Advanced Proteomics Techniques and Applications ; vaccines and immunoinformatics approaches ; Protein Degradation and Inhibitors
Authors: Luke Reilly | E. C. Lara | Daniel M. Ramos | Ziyi Li | Caroline B. Pantazis | Julia T. Stadler | Marianita Santiana | Jessica Roberts | Faraz Faghri | Ying Hao | Mike A. Nalls | Priyanka Narayan | Yansheng Liu | Andrew Singleton | Mark Cookson | Michael E. Ward | Yue Qi
Source: Cell Reports Methods (article, 2023-09-19)
Field: Chemistry — Spectroscopy

A fully automated FAIMS-DIA mass spectrometry-based proteomic pipeline Here, we present a standardized, "off-the-shelf" proteomics pipeline working in a single 96-well plate to achieve deep coverage of cellular proteomes with high throughput and scalability. This integrated pipeline streamlines a fully automated sample preparation platform, a data-independent acquisition (DIA) coupled with high-field asymmetric waveform ion mobility spectrometer (FAIMS) interface, and an optimized library-free DIA database search strategy. Our systematic evaluation of FAIMS-DIA showing single compensation voltage (CV) at -35 V not only yields the deepest proteome coverage but also best correlates with DIA without FAIMS. Our in-depth comparison of direct-DIA database search engines shows that Spectronaut outperforms others, providing the highest quantifiable proteins. Next, we apply three common DIA strategies in characterizing human induced pluripotent stem cell (iPSC)-derived neurons and show single-shot mass spectrometry (MS) using single-CV (-35 V)-FAIMS-DIA results in >9,000 quantifiable proteins with <10% missing values, as well as superior reproducibility and accuracy compared with other existing DIA methods. Ion-mobility spectrometry ; Pipeline (software) ; Proteome ; Chemistry ; Mass spectrometry ; Computer science ; Analytical Chemistry (journal) ; Chromatography ; Biochemistry Mass Spectrometry Techniques and Applications ; Advanced Proteomics Techniques and Applications ; Metabolomics and Mass Spectrometry Studies