jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Martí Checa | Xin Jin | Rubén Millán‐Solsona | Sabine M. Neumayer | Michael A. Susner | Michael A. McGuire | Andrew O’Hara | Gabriel Gomila | Petro Maksymovych | Sokrates T. Pantelides | Liam Collins
Source: ACS Nano (article, 2022-08-23)
Field: Materials Science — Materials Chemistry

Revealing Fast Cu-Ion Transport and Enhanced Conductivity at the CuInP<sub>2</sub>S<sub>6</sub>–In<sub>4/3</sub>P<sub>2</sub>S<sub>6</sub> Heterointerface Van der Waals layered ferroelectrics, such as CuInP<sub>2</sub>S<sub>6</sub> (CIPS), offer a versatile platform for miniaturization of ferroelectric device technologies. Control of the targeted composition and kinetics of CIPS synthesis enables the formation of stable self-assembled heterostructures of ferroelectric CIPS and nonferroelectric In<sub>4/3</sub>P<sub>2</sub>S<sub>6</sub> (IPS). Here, we use quantitative scanning probe microscopy methods combined with density functional theory (DFT) to explore in detail the nanoscale variability in dynamic functional properties of the CIPS-IPS heterostructure. We report evidence of fast ionic transport which mediates an appreciable out-of-plane electromechanical response of the CIPS surface in the paraelectric phase. Further, we map the nanoscale dielectric and ionic conductivity properties as we thermally stimulate the ferroelectric-paraelectric phase transition, recovering the local dielectric behavior during this phase transition. Finally, aided by DFT, we reveal a substantial and tunable conductivity enhancement at the CIPS/IPS interface, indicating the possibility of engineering its interfacial properties for next generation device applications. Materials science ; Ferroelectricity ; Dielectric ; van der Waals force ; Conductivity ; Phase transition ; Density functional theory ; Ionic bonding ; Nanoscopic scale ; Miniaturization ; Heterojunction ; Phase (matter) ; Nanotechnology ; Chemical physics ; Ion ; Condensed matter physics ; Optoelectronics ; Physical chemistry ; Physics ; Computational chemistry ; Chemistry ; Molecule Ferroelectric and Piezoelectric Materials ; Electronic and Structural Properties of Oxides ; Multiferroics and related materials
Authors: Martin Kubáň | Santiago Rigamonti | Markus Scheidgen | Claudia Draxl
Source: Scientific Data (article, 2022-10-22)
Field: Materials Science — Materials Chemistry

Density-of-states similarity descriptor for unsupervised learning from materials data We develop a materials descriptor based on the electronic density-of-states (DOS) and investigate the similarity of materials based on it. As an application example, we study the Computational 2D Materials Database (C2DB) that hosts thousands of two-dimensional materials with their properties calculated by density-functional theory. Combining our descriptor with a clustering algorithm, we identify groups of materials with similar electronic structure. We introduce additional descriptors to characterize these clusters in terms of crystal structures, atomic compositions, and electronic configurations of their members. This allows us to rationalize the found (dis)similarities and to perform an automated exploratory and confirmatory analysis of the C2DB data. From this analysis, we find that the majority of clusters consist of isoelectronic materials sharing crystal symmetry, but we also identify outliers, i.e., materials whose similarity cannot be explained in this way. Similarity (geometry) ; Outlier ; Cluster analysis ; Computer science ; Crystal (programming language) ; Data mining ; Pattern recognition (psychology) ; Artificial intelligence Machine Learning in Materials Science ; Computational Drug Discovery Methods ; X-ray Diffraction in Crystallography
Authors: Farooq Azam | Faheem Ahmad | Zeynep Ülker | Muhammad Sohail Zafar | Sheraz Ahmad | Abher Rasheed | Yasir Nawab | Can Erkey
Source: Advances in Materials Science and Engineering (article, 2022-09-17)
Field: Chemistry — Spectroscopy

The Role and Applications of Aerogels in Textiles Textiles have been used for clothing purposes since ancient times. However, due to their functional properties, their importance—as well as their use in various fields such as filtration, protective clothing, and medical applications—increased over time. Properties of the textile fabrics depend mostly on the fiber type, fabrication technique, and structure. Moreover, fabric porosity is one of the properties that provide comfort, increased thermal insulation, and filtration capability to the end products. The porous structure of woven, knitted, and nonwoven fabrics has been used for many years to get the desired porosity. Usually, macroporous structures are achieved using these types of textiles. Electrospinning is used to produce nanoporous textile fibrous web, but its poor mechanical properties and low production rate limit its use. Aerogels are solid materials with ultrahigh porosity at the nanoscale with low density and good thermal insulation properties, due to which they are considered potential insulation materials today. On the other hand, pure aerogels are sometimes brittle and have poor mechanical properties. Thus, they cannot be directly used in various applications. Consequently, textile reinforced aerogel composites have been developed, which could provide flexibility and strength to aerogels and impart nanoporous structure to textiles. This review summarizes conventional techniques to produce the porous structure in textiles followed by the modern techniques to develop a nanoporous structure. Further, different mechanisms to synthesize textile reinforced aerogel composites are discussed to get a nanoporous structure for filtration and thermal insulation applications. The porosity, mechanical properties, and thermal insulation of textile reinforced aerogel composites are also highlighted. In the end, we give a conclusion that not only summarizes the literature, but also includes recommendations for the researchers. Materials science ; Aerogel ; Nanoporous ; Textile ; Thermal insulation ; Porosity ; Composite material ; Fabrication ; Electrospinning ; Nanotechnology ; Polymer Aerogels and thermal insulation ; Surface Modification and Superhydrophobicity ; Advanced Sensor and Energy Harvesting Materials
Authors: Ha Young Kim | ShinYoung Kang | Ji Yeoung Lee | Tae Wook Heo | Brandon C. Wood | Jae Hyeok Shim | Young Whan Cho | Do Hyang Kim | Jin‐Yoo Suh | Young‐Su Lee
Source: Applied Surface Science (article, 2022-10-28)
Field: Materials Science — Materials Chemistry

A new perspective on the initial hydrogenation of TiFe0.9M0.1 (M = V, Cr, Fe, Co, Ni) alloys gained from surface oxide analyses and nucleation energetics Nucleation ; Energetics ; Oxide ; Materials science ; Perspective (graphical) ; Surface (topology) ; Physical chemistry ; Metallurgy ; Thermodynamics ; Chemistry ; Physics Hydrogen Storage and Materials ; Catalysis and Hydrodesulfurization Studies ; Electrocatalysts for Energy Conversion
Authors: Jie Sun | Yan HU | Yulin ZOU | Jinping Geng | Youli Wu | Rongsheng Fan | Zhiliang KANG
Source: Food Science and Technology (article, 2022-01-01)
Field: Chemistry — Analytical Chemistry

Identification of pesticide residues on black tea by fluorescence hyperspectral technology combined with machine learning Black tea has a long history in China, but in export trade, pesticide residues often exceed the standard. To obtain a rapid, accurate, and non-destructive identification method of pesticide residues on black tea, the fluorescence hyperspectral data of dry black tea sprayed with distilled water and six pesticides were collected in this study. The spectra were preprocessed by multiplicative scatter correction (MSC) and standard normal variate (SNV). Then the uninformative variable elimination (UVE), successive projections algorithm (SPA), competitive adaptive re-weighted sampling (CARS), UVE-SPA, and CARS-SPA were used to feature extraction. This study proposes a machine learning model composed of a one-dimensional convolutional neural network backbone (1D CNN backbone) and a random forest classifier (RF classifier) to identify pesticide residues on black tea, and the 1D CNN-RF model was compared with three other machine learning models (support vector machine, RF, and 1D CNN). The results show that MSC-CARS-SPA-1D CNN-RF is the best model for identifying pesticide residues on black tea in which the accuracy of the test set is 99.05%. Combined with fluorescence hyperspectral technology, the proposed 1D CNN-RF model has great potential in the non-destructive identification of pesticide residues on black tea. Hyperspectral imaging ; Convolutional neural network ; Artificial intelligence ; Support vector machine ; Pattern recognition (psychology) ; Classifier (UML) ; Random forest ; Black tea ; Computer science ; Biological system ; Chemistry ; Food science ; Biology Spectroscopy and Chemometric Analyses ; Pesticide Residue Analysis and Safety ; Water Quality Monitoring and Analysis
Authors: Mengqing Qiu | Shouguo Zheng | Le Tang | Xujin Hu | Qingshan Xu | Ling Zheng | Shizhuang Weng
Source: Foods (article, 2022-02-17)
Field: Chemistry — Analytical Chemistry

Raman Spectroscopy and Improved Inception Network for Determination of FHB-Infected Wheat Kernels Detection of infected kernels is important for Fusarium head blight (FHB) prevention and product quality assurance in wheat. In this study, Raman spectroscopy (RS) and deep learning networks were used for the determination of FHB-infected wheat kernels. First, the RS spectra of healthy, mild, and severe infection kernels were measured and spectral changes and band attribution were analyzed. Then, the Inception network was improved by residual and channel attention modules to develop the recognition models of FHB infection. The Inception-attention network produced the best determination with accuracies in training set, validation set, and prediction set of 97.13%, 91.49%, and 93.62%, among all models. The average feature map of the channel clarified the important information in feature extraction, itself required to clarify the decision-making strategy. Overall, RS and the Inception-attention network provide a noninvasive, rapid, and accurate determination of FHB-infected wheat kernels and are expected to be applied to other pathogens or diseases in various crops. Artificial intelligence ; Computer science ; Set (abstract data type) ; Feature (linguistics) ; Channel (broadcasting) ; Pattern recognition (psychology) ; Residual ; Machine learning ; Remote sensing ; Telecommunications ; Algorithm ; Geography Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Mycotoxins in Agriculture and Food
Authors: Qiang He | Wenjie He | Fangyuan Zhang | Yi-Ming Zhao | Lu Li | Xiangjun Yang | Fengwei Zhang
Source: Coatings (article, 2022-08-22)
Field: Materials Science — Materials Chemistry

Research Progress of Self-Cleaning, Anti-Icing, and Aging Test Technology of Composite Insulators Composite insulators are widely used in power systems because of their advantages of light weight, good pollution resistance, and high mechanical strength. With the increasingly serious environmental pollution problem, especially in winter at high latitudes, composite insulators are easily affected by fog, bird droppings, algae, and icing. Long-term exposure to the outdoor insulator surface will cause aging, which will then pose ae potential safety hazard to the stable operation of insulators. Therefore, the self-cleaning, anti-icing, and aging test technologies of composite insulators are particularly important. This paper introduces the research progress and current situation of self-cleaning, anti-icing surface preparation, and aging test technology of composite insulators, and looks forward to the future development of composite insulators. Icing ; Composite number ; Environmental science ; Environmental pollution ; Insulator (electricity) ; Engineering ; Materials science ; Forensic engineering ; Composite material ; Environmental protection ; Meteorology High voltage insulation and dielectric phenomena ; Smart Materials for Construction ; Surface Modification and Superhydrophobicity
Authors: Yihan Lang | Biao Zhang | Danfeng Cai | Wanjun Tu | Jingyi Zhang | Xuping Shentu | Zihong Ye | Xiaoping Yu
Source: Biosensors (review, 2022-12-31)
Field: Materials Science — Materials Chemistry

Determination Methods of the Risk Factors in Food Based on Nanozymes: A Review Food safety issues caused by foodborne pathogens, chemical pollutants, and heavy metals have aroused widespread concern because they are closely related to human health. Nanozyme-based biosensors have excellent characteristics such as high sensitivity, selectivity, and cost-effectiveness and have been used to detect the risk factors in foods. In this work, the common detection methods for pathogenic microorganisms, toxins, heavy metals, pesticide residues, veterinary drugs, and illegal additives are firstly reviewed. Then, the principles and applications of immunosensors based on various nanozymes are reviewed and explained. Applying nanozymes to the detection of pathogenic bacteria holds great potential for real-time evaluation and detection protocols for food risk factors. Human health ; Heavy metals ; Food safety ; Biochemical engineering ; Risk analysis (engineering) ; Food products ; Pollutant ; Biotechnology ; Environmental science ; Chemistry ; Environmental health ; Environmental chemistry ; Biology ; Business ; Food science ; Medicine ; Engineering Advanced Nanomaterials in Catalysis ; Biosensors and Analytical Detection ; Mercury impact and mitigation studies
Authors: Yan Zhang | Limin Yuan | Shuli He | Huilin Tao | Wenlian Xie | Xinyu Zhang | Xiaolu Ren | Tao Jiang | Lihong Li | Zhiqiang Zhu
Source: International Journal of Environmental Research and Public Health (review, 2022-02-27)
Field: Chemistry — Spectroscopy

Contemporary Research Progress on the Detection of Polycyclic Aromatic Hydrocarbons Polycyclic aromatic hydrocarbons (PAHs) are a class of the most common and widespread contaminants. The accumulation of PAHs has made a certain impact on the environment and is seriously threatening human health. Numerous general analytical methods suitable for PAHs were developed. With the development of economy, the environmental problems of PAHs in modern society are more extensive and prominent, and attract more attention from environmental scientists and analysts. Deeper understanding of the properties of PAHs depends on the advent of detection methods, which can also be more conducive to promoting the protection of the environment. Till now, more sensitive, more high-speed and more high-throughput analytical tools are being invented and have played important roles in the research of PAHs. In this short review article, we focused mainly on the contemporary analytical methods about PAHs. We started with a brief review on the hazards, migration, distribution and traditional analysis methods of PAHs in recent years, including liquid chromatography, gas chromatography, surface enhanced Raman spectroscopy and so on. We also presented the applications of the modern ambient mass spectrometry, especially microwave plasma torch mass spectrometry, in the detection of PAHs, as well as the far out novel results in our lab by using microwave plasma torch (MPT) mass spectrometry; for example, some new insights about Birch reduction, regular hydrogen addition and the robustness of molecular structure. These studies have demonstrated the versatility of MPT MS as a platform in the research of PAHs. Environmental chemistry ; Environmental analysis ; Environmental science ; Mass spectrometry ; Human health ; Chemistry ; Biochemical engineering ; Chromatography ; Engineering Mass Spectrometry Techniques and Applications ; Toxic Organic Pollutants Impact ; Analytical Chemistry and Chromatography
Authors: Hakan Demir | Seda Keskın
Source: Molecular Systems Design & Engineering (article, 2022-01-01)
Field: Chemistry — Inorganic Chemistry

Computational investigation of multifunctional MOFs for adsorption and membrane-based separation of CF<sub>4</sub>/CH<sub>4</sub>, CH<sub>4</sub>/H<sub>2</sub>, CH<sub>4</sub>/N<sub>2</sub>, and N<sub>2</sub>/H<sub>2</sub> mixtures The ease of functionalization of metal-organic frameworks (MOFs) can unlock unprecedented opportunities for gas adsorption and separation applications as the functional groups can impart favorable/unfavorable regions/interactions for the desired/undesired adsorbates. In this study, the effects of the presence of multiple functional groups in MOFs on their CF<sub>4</sub>/CH<sub>4</sub>, CH<sub>4</sub>/H<sub>2</sub>, CH<sub>4</sub>/N<sub>2</sub>, and N<sub>2</sub>/H<sub>2</sub> separation performances were computationally investigated combining grand canonical Monte Carlo (GCMC) and molecular dynamics (MD) simulations. The most promising adsorbents showing the best combinations of selectivity, working capacity, and regenerability were identified for each gas separation. 15, 13, and 16 out of the top 20 MOFs identified for the CH<sub>4</sub>/H<sub>2</sub>, CH<sub>4</sub>/N<sub>2</sub>, and N<sub>2</sub>/H<sub>2</sub> adsorption-based separation, respectively, were found to have -OCH<sub>3</sub> groups as one of the functional groups. The biggest improvements in CF<sub>4</sub>/CH<sub>4</sub>, CH<sub>4</sub>/H<sub>2</sub>, CH<sub>4</sub>/N<sub>2</sub>, and N<sub>2</sub>/H<sub>2</sub> selectivities were found to be induced by the presence of -OCH<sub>3</sub>-OCH<sub>3</sub> groups in MOFs. For CH<sub>4</sub>/H<sub>2</sub> separation, MOFs with two and three functionalized linkers were the best adsorbent candidates while for N<sub>2</sub>/H<sub>2</sub> separation, all the top 20 materials involve two functional groups. Membrane performances of the MOFs were also studied for CH<sub>4</sub>/H<sub>2</sub> and CH<sub>4</sub>/N<sub>2</sub> separation and the results showed that MOFs having -F-NH<sub>2</sub> and -F-OCH<sub>3</sub> functional groups present the highest separation performances considering both the membrane selectivity and permeability. Adsorption ; Materials science ; Membrane ; Physical chemistry ; Chemical engineering ; Chemistry ; Engineering Metal-Organic Frameworks: Synthesis and Applications ; Inorganic Fluorides and Related Compounds ; Membrane Separation and Gas Transport
Authors: Jeffrey I. Seeman | Dean J. Tantillo
Source: Chemical Science (review, 2022-01-01)
Field: Chemistry — Physical and Theoretical Chemistry

Understanding chemistry: from “heuristic (soft) explanations and reasoning by analogy” to “quantum chemistry” "Soft theories," <i>i.e.</i>, "heuristic models based on reasoning by analogy" largely drove chemistry understanding for 150 years or more. But soft theories have their limitations and with the expansion of chemistry in the mid-20<sup>th</sup> century, more and more inexplicable (by soft theory) experimental results were being obtained. In the past 50 years, quantum chemistry, most often in the guise of applied theoretical chemistry including computational chemistry, has provided (a) the underlying "hard evidence" for many soft theories and (b) the explanations for chemical phenomena that were unavailable by soft theories. In this publication, we define "hard theories" as "theories derived from quantum chemistry." Both soft and hard theories can be qualitative and quantitative, and the "Houk quadrant" is proposed as a helpful categorization tool. Furthermore, the language of soft theories is often used appropriately to describe quantum chemical results. A valid and useful way of doing science is the appropriate use and application of both soft and hard theories along with the best nomenclature available for successful communication of results and ideas. Analogy ; Heuristic ; Quantum chemistry ; Chemistry ; Quantum ; Computer science ; Cognitive science ; Epistemology ; Management science ; Artificial intelligence ; Psychology ; Engineering ; Organic chemistry ; Philosophy ; Quantum mechanics ; Molecule ; Physics ; Supramolecular chemistry History and advancements in chemistry ; Various Chemistry Research Topics ; Computational Drug Discovery Methods
Authors: Paulina Borgul | Karolina Sobczak | Karolina Sipa | Konrad Rudnicki | Sławomira Skrzypek | Anna Trynda | Łukasz Półtorak
Source: Scientific Reports (article, 2022-11-03)
Field: Chemistry — Electrochemistry

Heroin detection in a droplet hosted in a 3D printed support at the miniaturized electrified liquid-liquid interface Simple sensing protocols for the detection of illicit drugs are needed. Electrochemical sensing is especially attractive in this respect, as its cost together with the analytical accuracy aspires to replace still frequently used colorimetric tests. In this work, we have shown that the interfacial transfer of protonated heroin can be followed at the electrified water-1,2-dichloroethane interface. We have comprehensively studied the interfacial behavior of heroin alone and in the presence of its major and abundant cutting agents, caffeine and paracetamol. To maximally increase developed sensing protocol applicability we have designed and 3D printed a platform requiring only a few microliters of the aqueous and the organic phase. The proposed sensing platform was equipped with a cavity hosting a short section of Ag/AgCl electrode, up to 20 µL of the aqueous phase and the end of the micropipette tip being used as a casing of a fused silica capillary having 25 µm as the internal pore diameter. The volume of the organic phase was equal to around 5 µL and was present inside the micropipette tip. We have shown that under optimized conditions heroin can be detected in the presence of caffeine and paracetamol existing in a sample with 10,000 times excess over the analyte of interest. The calculated limit of detection equal to 1.3 µM, linear dynamic range spanning to at least 50 µM, good reproducibility, and very low volume of needed sample is fully in line with forensic demands. Interface (matter) ; Liquid liquid ; Computer science ; 3d printed ; Heroin ; Medicine ; Operating system ; Chromatography ; Chemistry ; Biomedical engineering ; Pharmacology ; Drug Electrochemical Analysis and Applications ; Neuroscience and Neural Engineering ; Advanced Chemical Sensor Technologies
Authors: W. Russ Algar | Katherine D. Krause
Source: Annual Review of Analytical Chemistry (review, 2022-03-18)
Field: Materials Science — Materials Chemistry

Developing FRET Networks for Sensing Förster resonance energy transfer (FRET) is a widely used fluorescence-based sensing mechanism. To date, most implementations of FRET sensors have relied on a discrete donor-acceptor pair for detection of each analytical target. FRET networks are an emerging concept in which target recognition perturbs a set of interconnected FRET pathways between multiple emitters. Here, we review the energy transfer topologies and scaffold materials for FRET networks, propose a general nomenclature, and qualitatively summarize the dynamics of the competitive, sequential, homoFRET, and heteroFRET pathways that constitute FRET networks. Implementations of FRET networks for sensing are also described, including concentric FRET probes, other single-vector multiplexing, and logic gates and switches. Unresolved questions and future research directions for current systems are discussed, as are potential but currently unexplored applications of FRET networks in sensing. Förster resonance energy transfer ; Computer science ; Multiplexing ; Nanotechnology ; Physics ; Fluorescence ; Materials science ; Telecommunications Luminescence and Fluorescent Materials ; Advanced biosensing and bioanalysis techniques ; Nanoplatforms for cancer theranostics