jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Sanyukta Ghosh | Harshita Naithani | Byungki Ryu | Gregor Oppitz | Eckhard Müller | Johannes de Boor
Source: Materials Today Physics (article, 2023-09-26)
Field: Materials Science — Materials Chemistry

Towards energy filtering in Mg2X-based composites: Investigating local carrier concentration and band alignment via SEM/EDX and transient Seebeck microprobe analysis A comprehensive understanding of multi-phase materials requires the characterization of transport properties at the micro/nano-scale. Optimized alignments of the conduction bands and valence bands at the interfaces of multi-phase materials can enhance the properties of thermoelectric materials by filtering out undesired charge carriers and is a promising path towards high performance thermoelectric devices. Here, a micro-scale characterization technique using transient Seebeck microprobe analysis, scanning electron microscopy with energy-dispersive X-ray spectroscopy, and electronic transport modelling based on the Boltzmann transport equation modeling is introduced to assess the band diagram and estimate the band offset in multi-phase materials. This characterization technique is applied to a composite of magnesium silicide-based materials. This material class is prone to form self-assembling nano-structured composites driven by a miscibility gap in the solid solutions series. Our analysis reveals changes in carrier concentration upon composite formation and considerable band offsets for both conduction and valence band when synthesizing nominally undoped composites. Employing Bi as dopant we show that Bi exhibits a preference for the Sn-rich phase, changing the carrier concentration differently in the Sn-rich matrix phase compared to the Si-rich secondary phase, effectively altering the band alignment of the composite. This demonstrates that our approach can be utilized to measure and manipulate the band offset within the composite to achieve optimal thermoelectric performance. Materials science ; Thermoelectric effect ; Seebeck coefficient ; Thermoelectric materials ; Band offset ; Dopant ; Band diagram ; Composite number ; Charge carrier ; Band gap ; Composite material ; Optoelectronics ; Doping ; Thermal conductivity ; Thermodynamics ; Valence band Advanced Thermoelectric Materials and Devices ; Semiconductor materials and interfaces ; Chalcogenide Semiconductor Thin Films
Authors: S.B. Kim | Dohun Kim | Kenji Watanabe | Takashi Taniguchi | J. H. Smet | Youngwook Kim
Source: Advanced Science (article, 2023-05-31)
Field: Materials Science — Materials Chemistry

Orbitally Controlled Quantum Hall States in Decoupled Two‐Bilayer Graphene Sheets The authors report on integer and fractional quantum Hall states in a stack of two twisted Bernal bilayer graphene sheets. By exploiting the momentum mismatch in reciprocal space, the single-particle tunneling between both bilayers is suppressed. Since the bilayers are spatially separated by only 0.34 nm, the stack benefits from strong interlayer Coulombic interactions. These interactions can cause the formation of a Bose-Einstein condensate. Indeed, such a condensate is observed for half-filling in each bilayer sheet. However, only when the partially filled levels have orbital index 1. It is absent for partially filled levels with orbital index 0. This discrepancy is tentatively attributed to the role of skyrmion/anti-skyrmion pair excitations and the dependence of the energy of these excitations on the orbital index. The application of asymmetric top and bottom gate voltages enables to influence the orbital nature of the electronic states of the graphene bilayers at the chemical potential and to navigate in orbital mixed space. The latter hosts an even denominator fractional quantum Hall state at total filling of -3/2. These observations suggest a unique edge reconstruction involving both electrons and chiral p-wave composite fermions. Bilayer graphene ; Bilayer ; Graphene ; Quantum Hall effect ; Condensed matter physics ; Nanotechnology ; Materials science ; Quantum dot ; Physics ; Quantum mechanics ; Chemistry ; Membrane Graphene research and applications ; Quantum and electron transport phenomena ; Quantum Computing Algorithms and Architecture
Authors: Hongni Zhu | Jianing Zhang | Xin Dai | Vince St. Dollente Mesias | Huanyu Chi | Congcheng Wang | Chi Shun Yeung | Qing Chen | Wei Liu | Jinqing Huang
Source: Analytical and Bioanalytical Chemistry (article, 2023-04-21)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Tunable lipid-coated nanoporous silver sheet for characterization of protein-membrane interactions by surface-enhanced Raman scattering (SERS) Membrane environments affect protein structures and functions through protein-membrane interactions in a wide range of important biological processes. To better study the effects from the lipid's hydrophilic and hydrophobic interaction with protein on different membrane regions, we developed the lipid-coated nanoporous silver sheets to provide tunable supported lipid monolayer/bilayer environments for in situ surface-enhanced Raman vibrational spectroscopy (SERS) characterizations. Under the controllable surface pressure, lipid monolayer/bilayer was coated along the microscopic curved surface of nanoporous silver sheets to serve as a cell membrane mimic as well as a barrier to avoid protein denaturation while empowering the high SERS enhancements from the underlying metallic bases allowing detection sensitivity at low physiological concentrations. Moreover, we fine-tuned the lipid packing density and controlled the orientation of the deposited lipid bilayers and monolayers to directly monitor the protein structures upon interactions with various membrane parts/positions. Our results indicate that lysozyme adopted the α-helical structure in both hydrophilic and hydrophobic interaction with lipid membrane. Interestingly, alpha-synuclein folded into the α-helical structure on the negatively charged lipid heads, whereas the hydrophobic lipid tails induced the β-sheet structural conversion of alpha-synuclein originated from its unstructured monomers. These direct observations on protein hydrophilic and hydrophobic interaction with lipid membrane might provide profound insights into the formation of the β-sheet-containing alpha-synuclein oligomers for further membrane disruptions and amyloid genesis associated with Parkinson's disease. Hence, with the controllability and tunability of lipid environments, our platform holds great promise for more general applications in investigating the influences from membranes and the correlative structures of proteins under both hydrophilic and hydrophobic effects. Lipid bilayer ; Membrane ; Monolayer ; Chemistry ; Nanoporous ; Bilayer ; Biophysics ; Model lipid bilayer ; Raman scattering ; Peripheral membrane protein ; Hydrophobic effect ; Raman spectroscopy ; Lipid bilayer phase behavior ; Chemical engineering ; Membrane protein ; Nanotechnology ; Materials science ; Organic chemistry ; Integral membrane protein ; Biochemistry Gold and Silver Nanoparticles Synthesis and Applications ; Protein Interaction Studies and Fluorescence Analysis ; Electrochemical Analysis and Applications
Authors: Hamdy Ibrahim | Caroline Billings | Moataz Abdalla | Ahmed Korra | David E. Anderson
Source: Bioengineering (article, 2023-07-24)
Field: Materials Science — Biomaterials

In Vivo Assessment of High-Strength and Corrosion-Controlled Magnesium-Based Bone Implants The biodegradable nature of magnesium in aqueous mediums makes it an attractive material for various biomedical applications when it is not recommended that the material stay permanently in the body. Some of the main challenges that hinder the use of magnesium for bone fracture repair are its limited mechanical strength and fast corrosion rates. To this end, we developed a novel Mg-Zn-Ca-Mn-based alloy and post-fabrication methods that can deliver high-strength and corrosion-controlled implant materials to address these challenges. This study is focused on assessing the in vitro corrosion and in vivo biocompatibility of the developed magnesium-based alloy and post-fabrication processes. The developed heat treatment process resulted in an increase in the microhardness from 71.9 ± 5.4 HV for the as-cast Mg alloy to as high as 98.1 ± 6.5 HV for the heat-treated Mg alloy, and the ceramic coating resulted in a significant reduction in the corrosion rate from 10.37 mm/yr for the uncoated alloy to 0.03 mm/yr after coating. The in vivo assessments showed positive levels of biocompatibility in terms of degradation rates and integration of the implants in a rabbit model. In the rabbit studies, the implants became integrated into the bone defect and showed minimal evidence of an immune response. The results of this study show that it is possible to produce biocompatible Mg-based implants with stronger and more corrosion-controlled properties based on the developed Mg-Zn-Ca-Mn-based alloy and post-fabrication methods. Biocompatibility ; Corrosion ; Materials science ; Magnesium alloy ; Coating ; Alloy ; Fabrication ; Magnesium ; Metallurgy ; Simulated body fluid ; Ceramic ; Biomedical engineering ; Composite material ; Scanning electron microscope ; Medicine Magnesium Alloys: Properties and Applications ; Aluminum Alloys Composites Properties ; Titanium Alloys Microstructure and Properties
Authors: Adelaide Nespoli | Antonio Mattia Grande | Francesca Passaretti | Daniela Rigamonti | Giuseppe Sala | Paolo Bettini
Source: The International Journal of Advanced Manufacturing Technology (article, 2023-02-28)
Field: Materials Science — Materials Chemistry

Damping property of a NiTi auxetic structure fabricated through selective laser melting Abstract The present work aims at studying the damping response of a NiTi auxetic structure fabricated through additive manufacturing. Furthermore, an electropolishing route has been accounted for improving the roughness on the external surface of the printed samples. The damping capacity of the manufactured auxetic NiTi components is evaluated through the amount of energy dissipated per cycle and through the loss factor index. Results show that the damping capacity of the auxetic NiTi cell takes advantage of electropolishing and it is superior to that of traditional materials. Particularly, a maximum dissipated energy of 55 mJ was registered in the austenite state after 10 min of electropolishing; additionally, the loss factor shows a maximum of 0.0523 in the R-phase. Materials science ; Auxetics ; Electropolishing ; Nickel titanium ; Austenite ; Surface finish ; Composite material ; Surface roughness ; Shape-memory alloy ; Microstructure Shape Memory Alloy Transformations ; Cellular and Composite Structures ; Additive Manufacturing Materials and Processes
Authors: Libby J. Marshall | Simona Bianco | Rebecca E. Ginesi | James Doutch | Emily R. Draper | Dave J. Adams
Source: Soft Matter (article, 2023-01-01)
Field: Materials Science — Biomaterials

Investigating multigelator systems across multiple length scales Preparation of multicomponent systems provides a method for changing the properties of low molecular weight gelator (LMWG)-based systems. Here we have prepared a variety of multicomponent systems where both components are <i>N</i>-functionalised dipeptide-based LMWGs that may either co-assemble or self-sort when mixed. We exemplify how varying the concentration ratio of the two components can be used to tune the properties of the multicomponent systems pre-gelation, during gelation and in the gel state using viscosity and rheology measurements, circular dichroism, NMR and small angle neutron scattering. We also investigate the effect of changing the chirality of a single component on the properties of these systems. While predicting the outcome of multicomponent assembly is a challenge, the preparation of a variety of systems allows us to probe the factors affecting their design. This work provides insights into how the properties of multicomponent systems composed of two gelators with the same basic structural design can be tuned by varying the chirality and the concentration ratio of the two components and considering the behaviour of the two components when alone. Length scale ; Statistical physics ; Computer science ; Physics ; Mechanics Supramolecular Self-Assembly in Materials ; Polydiacetylene-based materials and applications ; Photochromic and Fluorescence Chemistry
Authors: Charlotte Soneson | Vytautas Iešmantavičius | Daniel Heß | Michael Stadler | Jan Seebacher
Source: The Journal of Open Source Software (article, 2023-09-11)
Field: Chemistry — Spectroscopy

einprot: flexible, easy-to-use, reproducible workflowsfor statistical analysis of quantitative proteomics data Soneson et al., (2023). einprot: flexible, easy-to-use, reproducible workflows for statistical analysis of quantitative proteomics data. Journal of Open Source Software, 8(89), 5750, https://doi.org/10.21105/joss.05750 Workflow ; Computer science ; Statistical analysis ; Software ; Proteomics ; Statistical software ; Open source ; Quantitative proteomics ; Data science ; Data mining ; Software engineering ; Statistics ; Database ; Chemistry ; Programming language ; Mathematics Advanced Proteomics Techniques and Applications ; Bioinformatics and Genomic Networks ; Gene expression and cancer classification
Authors: Wouter Van den Broek | Daen Jannis | Johan Verbeeck
Source: Ultramicroscopy (article, 2023-08-14)
Field: Materials Science — Surfaces, Coatings and Films

Convexity constraints on linear background models for electron energy-loss spectra Convexity ; Quadratic equation ; Range (aeronautics) ; Energy (signal processing) ; Spectral line ; Linearity ; Computer science ; Sample (material) ; Electron ; Power (physics) ; Nonlinear system ; Computational physics ; Mathematical optimization ; Statistical physics ; Algorithm ; Physics ; Mathematics ; Materials science ; Statistics ; Quantum mechanics ; Geometry Electron and X-Ray Spectroscopy Techniques ; Advanced biosensing and bioanalysis techniques ; Advanced Electron Microscopy Techniques and Applications
Authors: Cameron N. Naylor | Brian H. Clowers | Florian Schlottmann | Nic Solle | Stefan Zimmermann
Source: Journal of the American Society for Mass Spectrometry (article, 2023-06-05)
Field: Chemistry — Spectroscopy

Implementation of an Open-Source Multiplexing Ion Gate Control for High Kinetic Energy Ion Mobility Spectrometry (HiKE-IMS) With ion mobility spectrometry increasingly used in mass spectrometry to enhance separation by increasing orthogonality, low ion throughput is a challenge for the drift-tube ion mobility experiment. The High Kinetic Energy Ion Mobility Spectrometer (HiKE-IMS) is no exception and routinely uses duty cycles of less than 0.1%. Multiplexing techniques such as Fourier transform and Hadamard transform represent two of the most common approaches used in the literature to improve ion throughput for the IMS experiment; these techniques promise increased duty cycles of up to 50% and an increased signal-to-noise ratio (SNR). With no instrument modifications required, we present the implementation of Hadamard Transform on the HiKE-IMS using a low cost, high-speed (600 MHz), open source microcontroller, a Teensy 4.1. Compared to signal average mode, 7- to 10-bit pseudorandom binary sequences resulted in increased analyte signal by over a factor of 3. However, the maximum SNR gain of 10 did not approach the theoretical <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msqrt><mml:mrow><mml:msup><mml:mrow><mml:mn>2</mml:mn></mml:mrow><mml:mrow><mml:mi>n</mml:mi></mml:mrow></mml:msup><mml:mo>-</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:msqrt></mml:math> gain largely due to capacitive coupling of the ion gate modulation with the Faraday plate used as a detector. Even when utilizing an inverse Hadamard technique, capacitive coupling was not completely eliminated. Regardless, the benefits of multiplexing IMS coupled to mass spectrometers are well documented throughout literature, and this first effort serves as a proof of concept for multiplexing HiKE-IMS. Finally, the highly flexible Teensy used in this effort can be used to multiplex other devices or can be used for Fourier transform instead of Hadamard transform. Ion-mobility spectrometry ; Hadamard transform ; Multiplexing ; Chemistry ; Mass spectrometry ; Duty cycle ; Analytical Chemistry (journal) ; Computer science ; Telecommunications ; Physics ; Voltage Mass Spectrometry Techniques and Applications ; Analytical Chemistry and Sensors ; Microfluidic and Capillary Electrophoresis Applications
Authors: Akshay J. Thomas | Mateusz Jaszczuk | Eduardo Barocio | Gourab Ghosh | Ilias Bilionis | R. Byron Pipes
Source: Computer Methods in Applied Mechanics and Engineering (article, 2023-11-27)
Field: Materials Science — Materials Chemistry

Probabilistic physics-guided transfer learning for material property prediction in extrusion deposition additive manufacturing Extrusion ; Thermal conductivity ; Materials science ; Material properties ; Deposition (geology) ; Composite material ; Composite number ; Mechanical engineering ; Fused deposition modeling ; Thermal ; Ultimate tensile strength ; Characterization (materials science) ; 3D printing ; Engineering ; Nanotechnology ; Physics ; Thermodynamics Thermal properties of materials ; Composite Material Mechanics ; Additive Manufacturing and 3D Printing Technologies
Authors: Karol Prałat | Justyna Ciemnicka | Piotr Jankowski | E. Wierzbicka | Arkadiusz Plis
Source: Polish Journal of Chemical Technology (article, 2023-03-01)
Field: Chemistry — Spectroscopy

Experimental research on the thermal properties of innovative insulation boards made of polyurethane-polyisocyanurate (PUR/PIR) Abstract In this work, the results of investigations of polyurethane materials were presented. Innovative materials based on polyurethane-polyisocyanurate (PUR/PIR) foam were obtained. Different types of additives (flame retardants, aerogels – additives that decrease thermal conductivity) are used in the composition of PUR/PIR foam. Foams are a type of composite composed of two phases: continuous (polyurethane polymers) and dispersed (composed of gases). All samples have been tested for thermal parameters: thermal conductivity, specific heat, and thermal diffusivity. Then they have been compared with each other and with a reference sample (RS) without additives. Based on the research, it was shown that innovative insulation materials were characterized by thermal conductivity λ in the range of 0.0254–0.0294 W/(m · K). The thermal properties of foams depending on the type and chemical composition of the material. Depending on the used substrates, their molar ratio, type, synthesis conditions, modifying agents and catalysts, a different polyurethane material is obtained. Polyurethane ; Materials science ; Thermal conductivity ; Thermal diffusivity ; Composite material ; Thermal insulation ; Composite number ; Polymer ; Thermal effusivity ; Thermal ; Chemical engineering ; Thermal resistance ; Thermal contact conductance Aerogels and thermal insulation ; Silicone and Siloxane Chemistry ; Building materials and conservation
Authors: Kevin Cruse | Viktoriia Baibakova | Maged Abdelsamie | Kootak Hong | Christopher J. Bartel | Amalie Trewartha | Anubhav Jain | Carolin M. Sutter‐Fella | Gerbrand Ceder
Source: Chemistry of Materials (article, 2023-12-29)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Text Mining the Literature to Inform Experiments and Rationalize Impurity Phase Formation for BiFeO<sub>3</sub> We used data-driven methods to understand the formation of impurity phases in BiFeO<sub>3</sub> thin-film synthesis through the sol-gel technique. Using a high-quality dataset of 331 synthesis procedures and outcomes extracted manually from 177 scientific articles, we trained decision tree models that reinforce important experimental heuristics for the avoidance of phase impurities but ultimately show limited predictive capability. We find that several important synthesis features, identified by our model, are often not reported in the literature. To test our ability to correctly impute missing synthesis parameters, we attempted to reproduce nine syntheses from the literature with varying degrees of "missingness". We demonstrate how a text-mined dataset can be made useful by informing new controlled experiments and forming a better understanding for impurity phase formation in this complex oxide system. Impurity ; Heuristics ; Phase (matter) ; Decision tree ; Computer science ; Materials science ; Missing data ; Quality (philosophy) ; Data mining ; Machine learning ; Physics Multiferroics and related materials ; Expert finding and Q&A systems ; Machine Learning in Materials Science
Authors: Dominik Lemm | Guido Falk von Rudorff | O. Anatole von Lilienfeld
Source: Digital Discovery (article, 2023-10-17)
Field: Chemistry — Physical and Theoretical Chemistry

Impact of noise on inverse design: the case of NMR spectra matching The effectiveness of computational NMR spectra matching for inverse structure elucidation depends on the interplay of number of candidates, chemical shift accuracy, as well as the usage of multiple shift types. Matching (statistics) ; Inverse ; Spectral line ; Noise (video) ; NMR spectra database ; Chemical shift ; Inverse problem ; Mathematics ; Algorithm ; Computer science ; Nuclear magnetic resonance ; Statistical physics ; Physics ; Mathematical analysis ; Statistics ; Artificial intelligence ; Quantum mechanics ; Geometry Various Chemistry Research Topics ; Machine Learning in Materials Science ; NMR spectroscopy and applications
Authors: Sergei V. Kalinin | Ondrej Dyck | Ayana Ghosh | Yongtao Liu | Bobby G. Sumpter | Maxim Ziatdinov
Source: APL Machine Learning (article, 2023-06-01)
Field: Materials Science — Materials Chemistry

Unsupervised machine learning discovery of structural units and transformation pathways from imaging data We show that unsupervised machine learning can be used to learn chemical transformation pathways from observational Scanning Transmission Electron Microscopy (STEM) data. To enable this analysis, we assumed the existence of atoms, a discreteness of atomic classes, and the presence of an explicit relationship between the observed STEM contrast and the presence of atomic units. With only these postulates, we developed a machine learning method leveraging a rotationally invariant variational autoencoder (VAE) that can identify the existing molecular fragments observed within a material. The approach encodes the information contained in STEM image sequences using a small number of latent variables, allowing the exploration of chemical transformation pathways by tracing the evolution of atoms in the latent space of the system. The results suggest that atomically resolved STEM data can be used to derive fundamental physical and chemical mechanisms involved, by providing encodings of the observed structures that act as bottom-up equivalents of structural order parameters. The approach also demonstrates the potential of variational (i.e., Bayesian) methods in the physical sciences and will stimulate the development of more sophisticated ways to encode physical constraints in the encoder–decoder architectures and generative physical laws and causal relationships in the latent space of VAEs. Autoencoder ; Unsupervised learning ; Artificial intelligence ; Computer science ; ENCODE ; Generative model ; Invariant (physics) ; Data-driven ; Transformation (genetics) ; Pattern recognition (psychology) ; Latent variable ; Tracing ; Physical law ; Microscale chemistry ; Generative grammar ; Machine learning ; Deep learning ; Mathematics ; Physics ; Biology Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Advanced Electron Microscopy Techniques and Applications