jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Volker Haag | Kilian Dremel | Simon Zabler
Source: IAWA Journal - KU Leuven/IAWA Journal (article, 2022-12-01)
Field: Chemistry — Organic Chemistry

Volumetric imaging by micro computed tomography: a suitable tool for wood identification of charcoal Summary The present study focuses on the application of state-of-the-art μ CT, by using a sub-micrometre CT scanner as a tool for wood identification. Charcoal was chosen as a subject for this case study. The reason for choosing charcoal is based on economic as well as technical issues. Parallel to conventional wood anatomy, various promising approaches to identification are currently being developed worldwide in order to simplify the identification of processed wood. However, due to the carbonization process, such approaches are not applicable to charcoal. In view of the rapid development of μ CT technology, it was decided to examine the extent to which wood anatomical studies can be supported and improved by modern μ CT technology. About 17% of the annually harvested wood worldwide is converted to charcoal (FAO 2017), and the charcoal trade is one of the least controlled/monitored segments of the European timber market. Although charcoal has a significant market share of wood-based products, it is still not yet covered by any trade regulation, e.g. the European Timber Regulations (EUTR), (EU) No995/2010. For the present study, different wood types and the anatomical fine structural features were measured and displayed at different magnifications to visualize the performance of state-of-the-art μ CT standards. Three different charcoal assortments were examined, and the results were checked against the given declarations of contents. The aim of this work is to evaluate the potential of the μ CT technique in the field of wood identification and to assess its use for the regulatory control of charcoal and other wood products in the international timber trade. The results are encouraging and lead to the conclusion that the application of the μ CT technique in the field of wood identification can be classified as very promising for the future. Charcoal ; Identification (biology) ; Carbonization ; Process (computing) ; Computer science ; Pulp and paper industry ; Environmental science ; Engineering ; Materials science ; Botany ; Biology ; Composite material Wood and Agarwood Research ; Cultural Heritage Materials Analysis ; Image Processing and 3D Reconstruction
Authors: M. Sakano | Yuma Tanaka | Satoru Masubuchi | Shota Okazaki | Takuya Nomoto | Atsushi Oshima | Kenji Watanabe | Takashi Taniguchi | Ryotaro Arita | T. Sasagawa | Tomoki Machida | K. Ishizaka
Source: Physical Review Research (article, 2022-06-27)
Field: Materials Science — Materials Chemistry

Odd-even layer-number effect of valence-band spin splitting in <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mi>WTe</mml:mi><mml:mn>2</mml:mn></mml:msub></mml:math> When a crystal becomes thin to the atomic level, peculiar phenomena discretely depending on its layer numbers ($n$) start to appear. Here, we investigate the electronic band dispersions of multilayer ${\mathrm{WTe}}_{2}$ (2--5 layers), by performing laser-based microfocused angle-resolved photoelectron spectroscopy on exfoliated flakes sorted by $n$. We observe that the holelike valence bands start to cross the Fermi level when the number of layers is increased from 2- to 3 layers, which should be related to the insulator-semimetal transition, as well as the 30--70-meV spin splitting of valence bands manifesting in even $n$ as a signature of stronger structural asymmetry. Our result fully demonstrates the possibility of the large energy-scale band and spin manipulation through the finite-$n$ stacking procedure. Valence (chemistry) ; X-ray photoelectron spectroscopy ; Semimetal ; Asymmetry ; Valence band ; Condensed matter physics ; Fermi level ; Stacking ; Materials science ; Physics ; Nuclear magnetic resonance ; Quantum mechanics ; Band gap 2D Materials and Applications ; Topological Materials and Phenomena ; Electronic and Structural Properties of Oxides
Authors: Andrea Joseph | Elizabeth Nance
Source: Annual Review of Chemical and Biomolecular Engineering (review, 2022-03-23)
Field: Materials Science — Biomaterials

Nanotherapeutics and the Brain Brain disease remains a significant health, social, and economic burden with a high failure rate of translation of therapeutics to the clinic. Nanotherapeutics have represented a promising area of technology investment to improve drug bioavailability and delivery to the brain, with several successes for nanotherapeutic use for central nervous system disease that are currently in the clinic. However, renewed and continued research on the treatment of neurological disorders is critically needed. We explore the challenges of drug delivery to the brain and the ways in which nanotherapeutics can overcome these challenges. We provide a summary and overview of general design principles that can be applied to nanotherapeutics for uptake and penetration in the brain. We next highlight remaining questions that limit the translational potential of nanotherapeutics for application in the clinic. Lastly, we provide recommendations for ongoing preclinical research to improve the overall success of nanotherapeutics against neurological disease. Brain disease ; Disease ; Medicine ; Drug delivery ; Translational research ; Translational medicine ; Brain research ; Bench to bedside ; Neuroscience ; Risk analysis (engineering) ; Nanotechnology ; Psychology ; Medical physics ; Pathology Nanoparticle-Based Drug Delivery ; Neuroscience and Neural Engineering ; Graphene and Nanomaterials Applications
Authors: Martin R. Lea | Vasilios G. Stavros | Reinhard J. Maurer
Source: ChemPhotoChem (article, 2022-03-16)
Field: Materials Science — Materials Chemistry

Effect of Electron Donating/Withdrawing Groups on Molecular Photoswitching of Functionalized Hemithioindigo Derivatives: a Computational Multireference Study Abstract Hemithioindigos are a versatile group of molecules with the ability to undergo double bond isomerisation upon light excitation. Using electronic structure theory, a detailed description of the photoisomerisation of hemithioindigo and five of its functionalized derivatives is reported. We use a combination of Density Functional Theory (DFT), approximate second order Coupled Cluster (CC2), and multireference methods such as the complete active space self‐consistent field (CASSCF) method to probe how isomerisation capabilities of functionalized hemithioindigo derivatives are affected by functionalisation with both electron donating and withdrawing groups. We demonstrate that important properties such as the thermal barrier, electronic absorption spectra and, to an extent, the mechanism can all show pronounced differences compared to the parent hemithioindigo molecule. Our results demonstrate how the inclusion of functional groups can have important effects on its photoisomerisation capabilities, which in turn, can influence the fate of these molecules upon light excitation and their utility as molecular switches. Isomerization ; Chemistry ; Complete active space ; Density functional theory ; Molecule ; Coupled cluster ; Excitation ; Polar effect ; Computational chemistry ; Photochemistry ; Molecular switch ; Double bond ; Chemical physics ; Basis set ; Organic chemistry ; Quantum mechanics Photochromic and Fluorescence Chemistry ; Bioactive Compounds and Antitumor Agents ; Photodynamic Therapy Research Studies
Authors: Tao Zhang | Chenguang Li | Shuyu Sun
Source: Membranes (article, 2022-02-17)
Field: Materials Science — Surfaces, Coatings and Films

Effect of Temperature on Oil–Water Separations Using Membranes in Horizontal Separators The effect of temperature on oil-water separations is studied in this paper, focusing on the changed penetration velocities of water droplets on the separation membrane in a horizontal separator. A compact numerical scheme is developed based on the phase-field model, and the temperature effect is first theoretically analyzed regarding the key thermodynamic properties that may affect the separation performance. The computational scenario is designed based on practical horizontal separators in the oil field, and the droplet motions in the oil-water two-phase flow are simulated using our scheme under various operation conditions. It was found that a higher temperature may result in a faster penetration of the water droplets, and a larger density difference in the oil-water system is also preferred to accelerate the separation using membranes. Furthermore, increasing the operation temperature is proved to benefit the separation of water and heavy oil. Separator (oil production) ; Penetration (warfare) ; Membrane ; Volumetric flow rate ; Materials science ; Oil field ; Mechanics ; Petroleum engineering ; Environmental science ; Chemistry ; Thermodynamics ; Engineering ; Physics Surface Modification and Superhydrophobicity ; Fluid Dynamics and Heat Transfer ; Spacecraft and Cryogenic Technologies
Authors: Chuyi Liu | Chengrong Ling | Cheng Chen | Dongsheng Wang | Youwen Yang | Deqiao Xie | Cijun Shuai
Source: Materials Science in Additive Manufacturing (article, 2022-12-15)
Field: Materials Science — Biomaterials

Laser additive manufacturing of magnesium alloys and its biomedical applications Biomedical magnesium (Mg) alloy with unique biodegradability and excellent biocompatibility is one of the most sought after materials in medical field for orthopedics applications. Nevertheless, the high corrosion rate and inadequate mechanical properties hinder its development. Apart from that, to obtain the best surgical result, the size and shape of the fixation implant need to be adapted to the individual case. Thus, additive manufacturing (AM) processes, such as laser powder bed fusion (LPBF), are used to overcome these issues. This work reviews the recent advancements in biodegradable Mg-based alloys prepared by LPBF for biomedical applications. The influence of feedstock features and manufacturing parameters on the formability and quality is delineated in detail. The mechanical performances, degradation behaviors, and biological behavior of the LPBF-processed parts are discussed. Furthermore, we also made some suggestions for the challenges of Mg alloys in LPBF processing and applications in biomedical. Biocompatibility ; Materials science ; Formability ; Magnesium ; Corrosion ; Raw material ; Metallurgy Magnesium Alloys: Properties and Applications ; High Entropy Alloys Studies ; Additive Manufacturing Materials and Processes
Authors: Guolin Li | Zecheng Zhang | Xuena Zhang | Yunhui Wu | Kun Ma | Yue Jiao | Hao Zhao | Yimeng Song | Yajing Liu | Shenqiang Zhai
Source: Frontiers in Chemistry (article, 2022-07-14)
Field: Chemistry — Spectroscopy

Performance of a Mid-Infrared Sensor for Simultaneous Trace Detection of Atmospheric CO and N2O Based on PSO-KELM In this article, a field deployable sensor was developed using a self-developed 4.58-µm continuous wave quantum cascade laser (CW-QCL) for the simultaneous detection of carbon monoxide (CO) and nitrous oxide (N<sub>2</sub>O), both of which have strong fundamental absorption bands in this waveband. The sensor is based on tunable diode laser absorption spectroscopy (TDLAS) technology, which combined a multi-pass gas cell (MPGC) with a 41 m optical path length to achieve high-precision detection. Meanwhile, the particle swarm optimization-kernel extreme learning machine (PSO-KELM) algorithm was applied for CO and N<sub>2</sub>O concentration prediction. In addition, the self-designed board-level QCL driver circuit and harmonic signal demodulation circuit reduce the sensor cost and size. A series of validation experiments were conducted to verify the sensor performance, and experiments showed that the concentration prediction results of the PSO-KELM algorithm are better than those of the commonly used back propagation (BP) neural networks and partial least regression (PLS), with the smallest root mean square error (RMSE) and linear correlation coefficient closest to 1, which improves the detection precision of the sensor. The limit of detection (LoD) was assessed to be 0.25 parts per billion (ppb) for CO and 0.27 ppb for N<sub>2</sub>O at the averaging time of 24 and 38 s. Field deployment of the sensor was reported for simultaneous detection of CO and N<sub>2</sub>O in the air. Atmospheric Infrared Sounder ; TRACE (psycholinguistics) ; Infrared ; Trace gas ; Remote sensing ; Chemistry ; Environmental science ; Materials science ; Physics ; Organic chemistry ; Geology ; Optics Spectroscopy and Laser Applications ; Atmospheric and Environmental Gas Dynamics ; Gas Sensing Nanomaterials and Sensors
Authors: Zhiyong Zou | Qingsong Wu | Jie Chen | Long Tao | Jian Wang | Man Zhou | Yongpeng Zhao | Tingjiang YU | Yinfan WANG | Lijia Xu
Source: Food Science and Technology (article, 2022-01-01)
Field: Chemistry — Analytical Chemistry

Rapid determination of water content in potato tubers based on hyperspectral images and machine learning algorithms This study investigated the hyperspectral reflectance response of time series generated during oven drying to changes in the moisture content of potato tubers. Seventeen preprocessing methods were used to eliminate the influence of spectral noise on the spectral characteristic curve. Algorithms such as CatBoost, LightGBM, and XGBoost are used to obtain the first 40 effective characteristic spectra of hyperspectral images, which reduces the redundancy of data and improves the prediction accuracy. The water content prediction model of potato tubers was established by using the selected characteristic bands. The results showed that the combined model based on Lasso and XGBoost algorithm had the strongest prediction ability. The best model is MF-Lasso-XGBoost, which has R2 value of 0.8908, Rmse of 0.0610, Mdae of 0.0389, and R2cv of 0.8448. This research can provide reference for the detection of potato moisture content and theoretical basis for the development of crop moisture detector. Hyperspectral imaging ; Water content ; Mathematics ; Lasso (programming language) ; Content (measure theory) ; Artificial intelligence ; Preprocessor ; Algorithm ; Remote sensing ; Computer science ; Geography ; Engineering Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Advanced Chemical Sensor Technologies
Authors: Thilo Bracht | Daniel Kleefisch | Karin Schork | Kathrin E. Witzke | Weiqiang Chen | Malte Bayer | Jan Hovanec | Georg Johnen | Swetlana Meier | Yon‐Dschun Ko | Thomas Behrens | Thomas Brüning | Jana Fassunke | Reinhard Buettner | Julian Uszkoreit | Michael Adamzik | Martin Eisenacher | Barbara Sitek
Source: International Journal of Molecular Sciences (article, 2022-09-24)
Field: Chemistry — Spectroscopy

Plasma Proteomics Enable Differentiation of Lung Adenocarcinoma from Chronic Obstructive Pulmonary Disease (COPD) Chronic obstructive pulmonary disease (COPD) is a major risk factor for the development of lung adenocarcinoma (AC). AC often develops on underlying COPD; thus, the differentiation of both entities by biomarker is challenging. Although survival of AC patients strongly depends on early diagnosis, a biomarker panel for AC detection and differentiation from COPD is still missing. Plasma samples from 176 patients with AC with or without underlying COPD, COPD patients, and hospital controls were analyzed using mass-spectrometry-based proteomics. We performed univariate statistics and additionally evaluated machine learning algorithms regarding the differentiation of AC vs. COPD and AC with COPD vs. COPD. Univariate statistics revealed significantly regulated proteins that were significantly regulated between the patient groups. Furthermore, random forest classification yielded the best performance for differentiation of AC vs. COPD (area under the curve (AUC) 0.935) and AC with COPD vs. COPD (AUC 0.916). The most influential proteins were identified by permutation feature importance and compared to those identified by univariate testing. We demonstrate the great potential of machine learning for differentiation of highly similar disease entities and present a panel of biomarker candidates that should be considered for the development of a future biomarker panel. COPD ; Biomarker ; Medicine ; Internal medicine ; Univariate analysis ; Pulmonary disease ; Oncology ; Biomarker discovery ; Proteomics ; Multivariate analysis ; Biology Advanced Proteomics Techniques and Applications ; Ferroptosis and cancer prognosis ; Lung Cancer Research Studies
Authors: Lato Pezo | Biljana Lončar | Olja Šovljanski | Ana Tomić | Vanja Travičić | Milada Pezo | Milica Aćimović
Source: Life (article, 2022-10-27)
Field: Chemistry — Analytical Chemistry

Agricultural Parameters and Essential Oil Content Composition Prediction of Aniseed, Based on Growing Year, Locality and Fertilization Type—An Artificial Neural Network Approach Predicting yield is essential for producers, stakeholders and international interchange demand. The majority of the divergence in yield and essential oil content is associated with environmental aspects, including weather conditions, soil variety and cultivation techniques. Therefore, aniseed production was examined in this study. The categorical input variables for artificial neural network modelling were growing year (two successive growing years), growing locality (three different locations in Vojvodina Province, Serbia) and fertilization type (six different treatments). The output variables were morphological and quality parameters, with agricultural importance such as plant height, umbel diameter, number of umbels, number of seeds per umbel, 1000-seed weight, seed yield per plant, plant weight, harvest index, yield per ha, essential oil (EO) yield, germination energy, total germination, EO content, as well as the share of EOs compounds, including limonene, <i>cis</i>-dihydro carvone, methyl chavicol, carvone, <i>cis</i>-anethole, <i>trans</i>-anethole, β-elemene, α-himachalene, <i>trans</i>-β-farnesene, γ-himachalene, <i>trans</i>-muurola-4(14),5-diene, α-zingiberene, β-himachalene, β-bisabolene, <i>trans</i>-pseudoisoeugenyl 2-methylbutyrate and epoxy-pseudoisoeugenyl 2-methylbutyrate. The ANN model predicted agricultural parameters accurately, showing r<sup>2</sup> values between 0.555 and 0.918, while r<sup>2</sup> values for the forecasting of essential oil content were between 0.379 and 0.908. According to global sensitivity analysis, the fertilization type was a more influential variable to agricultural parameters, while the location site was more influential to essential oils content. Umbel ; Essential oil ; Carvone ; Germination ; Horticulture ; Anethole ; Mathematics ; Limonene ; Agronomy ; Botany ; Biology ; Cultivar Spectroscopy and Chemometric Analyses ; Essential Oils and Antimicrobial Activity ; Edible Oils Quality and Analysis
Authors: Angela Kruse | Jeffrey M. Spraggins
Source: Frontiers in Physiology (review, 2022-02-11)
Field: Chemistry — Spectroscopy

Uncovering Molecular Heterogeneity in the Kidney With Spatially Targeted Mass Spectrometry The kidney functions through the coordination of approximately one million multifunctional nephrons in 3-dimensional space. Molecular understanding of the kidney has relied on transcriptomic, proteomic, and metabolomic analyses of kidney homogenate, but these approaches do not resolve cellular identity and spatial context. Mass spectrometry analysis of isolated cells retains cellular identity but not information regarding its cellular neighborhood and extracellular matrix. Spatially targeted mass spectrometry is uniquely suited to molecularly characterize kidney tissue while retaining <i>in situ</i> cellular context. This review summarizes advances in methodology and technology for spatially targeted mass spectrometry analysis of kidney tissue. Profiling technologies such as laser capture microdissection (LCM) coupled to liquid chromatography tandem mass spectrometry provide deep molecular coverage of specific tissue regions, while imaging technologies such as matrix assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) molecularly profile regularly spaced tissue regions with greater spatial resolution. These technologies individually have furthered our understanding of heterogeneity in nephron regions such as glomeruli and proximal tubules, and their combination is expected to profoundly expand our knowledge of the kidney in health and disease. Mass spectrometry imaging ; Mass spectrometry ; Context (archaeology) ; Computational biology ; Kidney ; Laser capture microdissection ; Metabolomics ; MALDI imaging ; Chemistry ; Proteomics ; Capillary electrophoresis–mass spectrometry ; Biology ; Matrix-assisted laser desorption/ionization ; Chromatography ; Biochemistry ; Electrospray ionization ; Desorption ; Genetics Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Isotope Analysis in Ecology
Authors: Veronika Pilařová | Lukáš Kuda | Hana Vlčková | Lucie Nováková | Shubhpriya Gupta | Manoj G. Kulkarni | František Švec | J. Van Staden | Karel Doležal
Source: Plant Methods (article, 2022-06-23)
Field: Chemistry — Organic Chemistry

Carbon dioxide expanded liquid: an effective solvent for the extraction of quercetin from South African medicinal plants The optimized procedure enabled very fast extraction in 30 min using environmentally friendly solvents and it was successfully applied to 16 different plant samples, including 14 bulbs and 2 fruits from South Africa. The quercetin content in extracts was quantified using ultra-high performance liquid chromatography (UHPLC) with tandem mass spectrometry. UHPLC hyphenated with high-resolution mass spectrometry was used to confirm chemical identity of quercetin in the analyzed samples. We quantified quercetin in 11 samples of all 16 tested plants. The quercetin was found in Agapanthus praecox from the Amaryllidaceae family and its presence in this specie was reported for the first time. Extraction (chemistry) ; Chromatography ; Solvent ; Repeatability ; Chemistry ; Maceration (sewage) ; Yield (engineering) ; Carbon dioxide ; Materials science ; Organic chemistry Chemical synthesis and alkaloids ; Botanical Research and Applications ; Phytochemistry and Biological Activities