jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Isabel V. L. Wilkinson | Max Bottlinger | Yassmine El Harraoui | Stephan A. Sieber
Source: Angewandte Chemie International Edition (article, 2022-12-10)
Field: Chemistry — Spectroscopy

Profiling the Heme‐Binding Proteomes of Bacteria Using Chemical Proteomics Heme is a cofactor with myriad roles and essential to almost all living organisms. Beyond classical gas transport and catalytic functions, heme is increasingly appreciated as a tightly controlled signalling molecule regulating protein expression. However, heme acquisition, biosynthesis and regulation is poorly understood beyond a few model organisms, and the heme-binding proteome has not been fully characterised in bacteria. Yet as heme homeostasis is critical for bacterial survival, heme-binding proteins are promising drug targets. Herein we report a chemical proteomics method for global profiling of heme-binding proteins in live cells for the first time. Employing a panel of heme-based clickable and photoaffinity probes enabled the profiling of 32-54 % of the known heme-binding proteomes in Gram-positive and Gram-negative bacteria. This simple-to-implement profiling strategy could be interchangeably applied to different cell types and systems and fuel future research into heme biology. Proteome ; Proteomics ; Profiling (computer programming) ; Computational biology ; Heme ; Bacteria ; Chemistry ; Biology ; Biochemistry ; Computer science ; Genetics ; Enzyme Mass Spectrometry Techniques and Applications ; Advanced Proteomics Techniques and Applications ; Protein Structure and Dynamics
Authors: Pablo Díaz‐Rodríguez | M. Panizo-Laiz | César González | R. Iglesias | Ignacio Martin‐Bragado | R. González-Arrabal | J.M. Perlado | O. Peña | A. Rivera
Source: Emergent Materials (article, 2022-01-24)
Field: Materials Science — Materials Chemistry

Direct observation of hydrogen permeation through grain boundaries in tungsten Abstract In this paper, we report on an enhanced hydrogen permeation effect along grain boundaries in tungsten. Sputtered nanocolumnar tungsten layers (column lateral dimensions 100–150 nm and layer thickness 2 μm) were analysed by hydrogen permeation measurements in the temperature range 520–705 K. The experiments constitute a direct observation of this effect, previously postulated by means of a combination of indirect experiments and simulations and considered controversial due to the lack of direct measurements. DFT results support this observation since (i) the hydrogen binding energy to the grain boundary is 1.05 eV and (ii) the migration energies along the grain boundary and along the bulk are 0.12 eV and 0.20 eV, respectively. OKMC simulations, parametrized by DFT data, were used as a supporting tool to attain a better understanding of the involved phenomena. The OKMC results are also compatible with the observations. Indeed, they show that the fraction of hydrogen flux along grain boundaries in the steady-state permeation regime increases when decreasing the ratio of lateral dimensions to length of the nanocolumns, rapidly approaching unity when this ratio is &lt; 2. Therefore, grain boundaries act as preferential migration pathways for H atoms at the studied temperature range in the studied samples. This behaviour has interesting implications to reduce the retention of hydrogen in several applications, in particular, fusion materials exposed to plasma discharges. Grain boundary ; Permeation ; Tungsten ; Hydrogen ; Materials science ; Grain size ; Binding energy ; Atmospheric temperature range ; Chemical physics ; Thermodynamics ; Chemistry ; Metallurgy ; Atomic physics ; Microstructure ; Physics ; Membrane Fusion materials and technologies ; Nuclear Materials and Properties ; Ion-surface interactions and analysis
Authors: Shehu Nura Aliyu Yaro | Muslich Hartadi Sutanto | Aliyu Usman | Ahmad Hussaini Jagaba | Muktar Yakubu Sakadadi
Source: CONSTRUCTION (article, 2022-06-11)
Field: Materials Science — Polymers and Plastics

The Influence of Waste Rice Straw Ash as Surrogate Filler for Asphalt Concrete Mixtures Mineral fillers in asphalt concrete have improved the mix design qualities significantly. However, the high cost, scarcity, adverse impact towards environment and the inability of conventiona filller to enhance mixtures performance due to the increase in traffic loading have necessitated an investigation into viable alternatives in manufacturing asphalt concrete. Thus, researchers have been looking into using agricultural waste in asphalt pavements to improve sustainability and pavement performance. Waste rice straw (WRS) is a high-volume agricultural waste often burnt for electricity or discarded. In this study, WRS ash (WRSA) was sourced locally, incinerated, ball-milled, and sieved to pass BS sieve No.200 to generate fine powder WRSA, which can be utilised as the surrogate mineral filler. This study evaluated the effect of utilising WRSA as a partial substitute of mineral filler on the volumetric and Marshall properties of the WRSA modified asphalt mixtures. The tests were conducted on a series of asphalt concrete specimens prepared based on Marshall's design with the optimal bitumen content for all varying substitution percentages 0 (control), 25, 50, 75, and 100% WRSA and, the engineering properties of the asphalt mixtures were investigated. The study outcomes show that using WRSA as a surrogate filler inmproves asphalt concrete's Marshall stability and quotients value by 33% and 61% at the optimal replacement of 75%. Based on the result, it can be clinched that WRSA can be incorporated as a filler surrogate to promote sustainability. Asphalt ; Filler (materials) ; Incineration ; Waste management ; Materials science ; Asphalt concrete ; Sieve analysis ; Environmental science ; Composite material ; Engineering Natural Fiber Reinforced Composites ; Geotechnical and construction materials studies ; Asphalt Pavement Performance Evaluation
Authors: Vicente Amirpasha Tirado-Kulieva | Ernesto Hernández | Jukka‐Pekka Suomela
Source: European Food Research and Technology (review, 2022-04-21)
Field: Chemistry — Analytical Chemistry

Non-destructive assessment of vitamin C in foods: a review of the main findings and limitations of vibrational spectroscopic techniques Abstract The constant increase in the demand for safe and high-quality food has generated the need to develop efficient methods to evaluate food composition, vitamin C being one of the main quality indicators. However, its heterogeneity and susceptibility to degradation makes the analysis of vitamin C difficult by conventional techniques, but as a result of technological advances, vibrational spectroscopy techniques have been developed that are more efficient, economical, fast, and non-destructive. This review focuses on main findings on the evaluation of vitamin C in foods by using vibrational spectroscopic techniques. First, the fundamentals of ultraviolet–visible, infrared and Raman spectroscopy are detailed. Also, chemometric methods, whose use is essential for a correct processing and evaluation of the spectral information, are described. The use and importance of vibrational spectroscopy in the evaluation of vitamin C through qualitative characterization and quantitative analysis is reported. Finally, some limitations of the techniques and potential solutions are described, as well as future trends related to the utilization of vibrational spectroscopic techniques. Raman spectroscopy ; Infrared spectroscopy ; Analytical technique ; Infrared ; Characterization (materials science) ; Quality (philosophy) ; Spectroscopy ; Food products ; Chemistry ; Analytical Chemistry (journal) ; Biochemical engineering ; Computer science ; Materials science ; Food science ; Nanotechnology ; Environmental chemistry ; Organic chemistry ; Engineering ; Optics ; Physics Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Pesticide Residue Analysis and Safety
Authors: Timothy M. Allison | Matteo T. Degiacomi | Erik G. Marklund | Luca Jovine | Arne Elofsson | Justin L. P. Benesch | Michael Landreh
Source: Protein Science (article, 2022-05-21)
Field: Chemistry — Spectroscopy

Complementing machine learning‐based structure predictions with native mass spectrometry Abstract The advent of machine learning‐based structure prediction algorithms such as AlphaFold2 (AF2) and RoseTTa Fold have moved the generation of accurate structural models for the entire cellular protein machinery into the reach of the scientific community. However, structure predictions of protein complexes are based on user‐provided input and may require experimental validation. Mass spectrometry (MS) is a versatile, time‐effective tool that provides information on post‐translational modifications, ligand interactions, conformational changes, and higher‐order oligomerization. Using three protein systems, we show that native MS experiments can uncover structural features of ligand interactions, homology models, and point mutations that are undetectable by AF2 alone. We conclude that machine learning can be complemented with MS to yield more accurate structural models on a small and large scale. Homology modeling ; Mass spectrometry ; Computer science ; Computational biology ; Protein structure ; Chemistry ; Structural biology ; Biological system ; Artificial intelligence ; Machine learning ; Biology ; Biochemistry ; Chromatography Mass Spectrometry Techniques and Applications ; Protein Structure and Dynamics ; Enzyme Structure and Function
Authors: Beatriz Quintanilla‐Casas | Åsmund Rinnan | A. Romero | Francesc Guardiola | Alba Tres | Stefania Vichi | Rasmus Bro
Source: Food Chemistry (article, 2022-06-29)
Field: Chemistry — Analytical Chemistry

Using fluorescence excitation-emission matrices to predict bitterness and pungency of virgin olive oil: A feasibility study Unlike other food products, virgin olive oil must undergo an organoleptic assessment that is currently based on a trained human panel, which presents drawbacks that might affect the efficiency and robustness. Therefore, disposing of instrumental methods that could serve as screening tools to support sensory panels is of paramount importance. The present work aimed to explore excitation-emission fluorescence spectroscopy (EEFS) to predict bitterness and pungency, since both attributes are related with fluorophore compounds, such as polar phenols. Bitterness and pungency intensities of 250 samples were provided by an official sensory panel and used to build and compare partial least squares regressions (PLSR) with the excitation-emission matrix. Both PARAFAC scores and two-way unfolded data led to successful PLSR. The most relevant PARAFAC scores agreed with virgin olive oil phenolic spectra, evidencing that EEFS would be the fit-for-purpose screening tool to support the sensory panel. Pungency ; Partial least squares regression ; Organoleptic ; Chemistry ; Olive oil ; Fluorophore ; Odor ; Food science ; Biological system ; Sensory system ; Fluorescence spectroscopy ; Fluorescence ; Analytical Chemistry (journal) ; Computer science ; Chromatography ; Organic chemistry ; Machine learning ; Psychology ; Optics ; Biology ; Cognitive psychology Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Meat and Animal Product Quality
Authors: Aditya Narayan | Yvain Thonnart | Pascal Vivet | Ayse K. Coskun | Ajay Joshi
Source: ACM Transactions on Architecture and Code Optimization (article, 2022-10-28)
Field: Materials Science — Materials Chemistry

Architecting Optically Controlled Phase Change Memory Phase Change Memory (PCM) is an attractive candidate for main memory, as it offers non-volatility and zero leakage power while providing higher cell densities, longer data retention time, and higher capacity scaling compared to DRAM. In PCM, data is stored in the crystalline or amorphous state of the phase change material. The typical electrically controlled PCM (EPCM), however, suffers from longer write latency and higher write energy compared to DRAM and limited multi-level cell (MLC) capacities. These challenges limit the performance of data-intensive applications running on computing systems with EPCMs. Recently, researchers demonstrated optically controlled PCM (OPCM) cells with support for 5 bits / cell in contrast to 2 bits / cell in EPCM. These OPCM cells can be accessed directly with optical signals that are multiplexed in high-bandwidth-density silicon-photonic links. The higher MLC capacity in OPCM and the direct cell access using optical signals enable an increased read/write throughput and lower energy per access than EPCM. However, due to the direct cell access using optical signals, OPCM systems cannot be designed using conventional memory architecture. We need a complete redesign of the memory architecture that is tailored to the properties of OPCM technology. This article presents the design of a unified network and main memory system called COSMOS that combines OPCM and silicon-photonic links to achieve high memory throughput. COSMOS is composed of a hierarchical multi-banked OPCM array with novel read and write access protocols. COSMOS uses an Electrical-Optical-Electrical (E-O-E) control unit to map standard DRAM read/write commands (sent in electrical domain) from the memory controller on to optical signals that access the OPCM cells. Our evaluation of a 2.5D-integrated system containing a processor and COSMOS demonstrates 2.14 × average speedup across graph and HPC workloads compared to an EPCM system. COSMOS consumes 3.8× lower read energy-per-bit and 5.97× lower write energy-per-bit compared to EPCM. COSMOS is the first non-volatile memory that provides comparable performance and energy consumption as DDR5 in addition to increased bit density, higher area efficiency, and improved scalability. Computer science ; Dram ; Dynamic random-access memory ; Phase-change memory ; Throughput ; Flash memory ; Photonics ; Semiconductor memory ; Computer hardware ; Embedded system ; Computer architecture ; Optoelectronics ; Materials science ; Nanotechnology ; Telecommunications Phase-change materials and chalcogenides ; Advanced Memory and Neural Computing ; Neural Networks and Reservoir Computing
Authors: Chengjie Luo | Joshua F. Robinson | Ilian Pihlajamaa | Vincent E. Debets | C. Patrick Royall | Liesbeth M. C. Janssen
Source: Physical Review Letters (article, 2022-09-28)
Field: Materials Science — Materials Chemistry

Many-Body Correlations Are Non-negligible in Both Fragile and Strong Glassformers It is widely believed that the emergence of slow glassy dynamics is encoded in a material's microstructure. First-principles theory [mode-coupling theory (MCT)] is able to predict the dramatic slowdown of the dynamics from only static two-point correlations as input, yet it cannot capture all of the observed dynamical behavior. Here we go beyond two-point spatial correlation functions by extending MCT systematically to include higher-order static and dynamic correlations. We demonstrate that only adding the static triplet direct correlations already qualitatively changes the predicted glass-transition diagram of binary hard spheres and silica. Moreover, we find a nontrivial competition between static triplet correlations that work to stabilize the glass state and dynamic higher-order correlations that destabilize it for both materials. We conclude that the conventionally neglected static triplet direct correlations as well as higher-order dynamic correlations are, in fact, non-negligible in both fragile and strong glassformers. Physics ; Statistical physics ; Slowdown ; Work (physics) ; Coupling (piping) ; Hard spheres ; Binary number ; Condensed matter physics ; Materials science ; Quantum mechanics ; Mathematics Material Dynamics and Properties ; Theoretical and Computational Physics ; Liquid Crystal Research Advancements
Authors: Tawfiqur Rakib | Pascal Pochet | Elif Ertekin | Harley T. Johnson
Source: Communications Physics (article, 2022-10-02)
Field: Materials Science — Materials Chemistry

Corrugation-driven symmetry breaking in magic-angle twisted bilayer graphene Abstract The discovery of unconventional superconductivity in magic-angle twisted bilayer graphene (tBLG) supported the twist-angle-induced flat band structure predictions made a decade earlier. Numerous physical properties have since been linked to the interlayer twist angle using the flat band prediction as a guideline. However, some key observations like the nematic phase and striped charge order behind the superconductivity are missing in this initial model. Here we show that a thermodynamically stable large out-of-plane displacement, or corrugation of the bilayer, induced by the interlayer twist, demonstrates partially filled states of the flat band structure, accompanied by a broken symmetry, in the magic-angle regime and the presence of symmetry breaking associated with the superconductivity in tBLG. The distinction between low and high corrugation can also explain the observed evolution of the vibrational spectra of tBLG as a function of twist angle. Our observation that large out-of-plane deformation modes enable partial filling of states near the Fermi energy may lead to a strategy for offsetting the effects of disorder in the local twist angle, which suppresses unconventional superconductivity and correlated insulator behavior in magic-angle tBLG. Bilayer graphene ; Magic angle ; Condensed matter physics ; Superconductivity ; Twist ; Electronic band structure ; Symmetry breaking ; Symmetry (geometry) ; Physics ; Materials science ; Geometry ; Graphene ; Spectral line ; Quantum mechanics Graphene research and applications ; Quantum and electron transport phenomena ; Diamond and Carbon-based Materials Research
Authors: Abdul Jabbar | Alma V Palacios-Marín | Ali Ghanbarzadeh | Dongmin Yang | Muhammad Tausif
Source: Textile Research Journal (article, 2022-10-07)
Field: Materials Science — Polymers and Plastics

Impact of conventional and modified ring-spun yarn structures on the generation and release of fragmented fibers (microfibers) during abrasive wear and laundering The abrasive wear of textiles during ordinary use and laundering results in fiber damage, which leads to the generation and release of fragmented fibers (FFs). Ring-spun yarn has a dominant share of about 70% of global spun yarn production. The effect of conventional and modified ring yarn structures (compact, SIRO and SIRO-compact) on FF release from cotton textiles during repeated abrasion and laundering was studied. All prepared cotton yarns and textiles are industrially and commercially relevant. The FFs formed during each abrasion and washing cycle were collected from textiles and quantified. The yarn tensile properties and fabric frictional characteristics were employed to explain the release of FFs. For the first time, the morphology of collected FF ends was associated with the fiber damage nature (granulated and fibrillated) induced by different types of stresses and experimental exposure conditions. The results demonstrated that modified ring yarn structures released a significantly lower FF mass as compared to conventional ring yarn structures. The tensile strength was decreased, and breaking elongation increased after repeated abrasion and washing. The fabric surface properties were also affected by abrasion and laundering. The yarn structure choices impact the amount of released FFs, which are dispersed into the environment as a pollutant or a carrier of pollutants with potential hazards to the health of the environment and living organisms. Materials science ; Abrasion (mechanical) ; Composite material ; Yarn ; Abrasive ; Ultimate tensile strength ; Fiber ; Microfiber ; Elongation ; Ring (chemistry) ; Chemistry Textile materials and evaluations ; Microplastics and Plastic Pollution ; Additive Manufacturing and 3D Printing Technologies
Authors: Zhonglei Cai | Wenqian Huang | Qingyan Wang | Jiangbo Li
Source: Frontiers in Plant Science (article, 2022-08-10)
Field: Chemistry — Analytical Chemistry

Detection of early decayed oranges by structured-illumination reflectance imaging coupling with texture feature classification models Citrus fruits are susceptible to fungal infection after harvest. To reduce the economic loss, it is necessary to reject the infected citrus fruit before storage and transportation. However, the infected area in the early stage of decay is almost invisible on the fruit surface, so the detection of early decayed citrus is very challenging. In this study, a structured-illumination reflectance imaging (SIRI) system combined with a visible light-emitting diode (LED) lamp and a monochrome camera was developed to detect early fungal infection in oranges. Under sinusoidal modulation illumination with spatial frequencies of 0.05, 0.15, and 0.25 cycles mm<sup>-1</sup>, three-phase-shifted images with phase offsets of - 2π/3, 0, and 2π/3 were acquired for each spatial frequency. The direct component (DC) and alternating component (AC) images were then recovered by image demodulation using a three-phase-shifting approach. Compared with the DC image, the decayed area can be clearly identified in the AC image and RT image (AC/DC). The optimal spatial frequency was determined by analyzing the AC image and pixel intensity distribution. Based on the texture features extracted from DC, AC, and RT images, four kinds of classification models including partial least square discriminant analysis (PLS-DA), support vector machine (SVM), least squares-support vector machine (LS-SVM), and k-nearest neighbor (KNN) were established to detect the infected oranges, respectively. Model optimization was also performed by extracting important texture features. Compared to all models, the PLS-DA model developed based on eight texture features of RT images achieved the optimal classification accuracy of 96.4%. This study showed for the first time that the proposed SIRI system combined with appropriate texture features and classification model can realize the early detection of decayed oranges. Artificial intelligence ; Support vector machine ; Feature (linguistics) ; Pattern recognition (psychology) ; Texture (cosmology) ; Computer science ; Spatial frequency ; Linear discriminant analysis ; Computer vision ; Mathematics ; Optics ; Image (mathematics) ; Physics Spectroscopy and Chemometric Analyses ; Industrial Vision Systems and Defect Detection ; Water Quality Monitoring and Analysis