jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Zheyu Luo | Xueyu Hu | Yucun Zhou | Yong Ding | Weilin Zhang | Tongtong Li | Meilin Liu
Source: Advanced Materials (article, 2024-01-22)
Field: Materials Science — Materials Chemistry

Harnessing High‐Throughput Computational Methods to Accelerate the Discovery of Optimal Proton Conductors for High‐Performance and Durable Protonic Ceramic Electrochemical Cells The pursuit of high-performance and long-lasting protonic ceramic electrochemical cells (PCECs) is impeded by the lack of efficient and enduring proton conductors. Conventional research approaches, predominantly based on a trial-and-error methodology, have proven to be demanding of resources and time-consuming. Here, this work reports the findings in harnessing high-throughput computational methods to expedite the discovery of optimal electrolytes for PCECs. This work methodically computes the oxygen vacancy formation energy (E<sub>V</sub>), hydration energy (E<sub>H</sub>), and the adsorption energies of H<sub>2</sub>O and CO<sub>2</sub> for a set of 932 oxide candidates. Notably, these findings highlight BaSn<sub>x</sub>Ce<sub>0.8-x</sub>Yb<sub>0.2</sub>O<sub>3-δ</sub> (BSCYb) as a prospective game-changing contender, displaying superior proton conductivity and chemical resilience when compared to the well-regarded BaZr<sub>x</sub>Ce<sub>0.8-x</sub>Y<sub>0.1</sub>Yb<sub>0.1</sub>O<sub>3-δ</sub> (BZCYYb) series. Experimental validations substantiate the computational predictions; PCECs incorporating BSCYb as the electrolyte achieved extraordinary peak power densities in the fuel cell mode (0.52 and 1.57 W cm<sup>-2</sup> at 450 and 600 °C, respectively), a current density of 2.62 A cm<sup>-2</sup> at 1.3 V and 600 °C in the electrolysis mode while demonstrating exceptional durability for over 1000-h when exposed to 50% H<sub>2</sub>O. This research underscores the transformative potential of high-throughput computational techniques in advancing the field of proton-conducting oxides for sustainable power generation and hydrogen production. Materials science ; Electrolyte ; Ceramic ; Mesoporous material ; Electrochemistry ; Proton ; Power density ; Oxide ; Electrical conductor ; Conductivity ; Work (physics) ; Nanotechnology ; Chemical engineering ; Power (physics) ; Physical chemistry ; Thermodynamics ; Electrode ; Catalysis ; Composite material ; Metallurgy ; Organic chemistry ; Chemistry Advancements in Solid Oxide Fuel Cells ; Electronic and Structural Properties of Oxides ; Magnetic and transport properties of perovskites and related materials
Authors: Lu Wang | Zhijun Jin | Xiaowei Huang | Runchao Liu | Yutong Su | Qian Zhang
Source: Sustainability (review, 2024-02-27)
Field: Materials Science — Materials Chemistry

Hydrogen Adsorption in Porous Geological Materials: A Review The paper adopts an interdisciplinary approach to comprehensively review the current knowledge in the field of porous geological materials for hydrogen adsorption. It focuses on detailed analyses of the adsorption characteristics of hydrogen in clay minerals, shale, and coal, considering the effect of factors such as pore structure and competitive adsorption with multiple gases. The fundamental principles underlying physically controlled hydrogen storage mechanisms in these porous matrices are explored. The findings show that the adsorption of hydrogen in clay minerals, shale, and coal is predominantly governed by physical adsorption that follows the Langmuir adsorption equation. The adsorption capacity decreases with increasing temperature and increases with increasing pressure. The presence of carbon dioxide and methane affects the adsorption of hydrogen. Pore characteristics—including specific surface area, micropore volume, and pore size—in clay minerals, shale, and coal are crucial factors that influence the adsorption capacity of hydrogen. Micropores play a significant role, allowing hydrogen molecules to interact with multiple pore walls, leading to increased adsorption enthalpy. This comprehensive review provides insights into the hydrogen storage potential of porous geological materials, laying the groundwork for further research and the development of efficient and sustainable hydrogen storage solutions. Adsorption ; Hydrogen storage ; Oil shale ; Hydrogen ; Porosity ; Langmuir ; Microporous material ; Chemical engineering ; Materials science ; Coal ; Methane ; Clay minerals ; Chemistry ; Mineralogy ; Geology ; Composite material ; Organic chemistry Hydrogen Storage and Materials ; Covalent Organic Framework Applications ; Methane Hydrates and Related Phenomena
Authors: Yuwen Qin | Qi Zhao | Dan Zhou | Yabo Shi | Haiyan Shou | Mingxuan Li | Wei Zhang | Chengxi Jiang
Source: Food Chemistry X (article, 2024-02-12)
Field: Chemistry — Analytical Chemistry

Application of flash GC e-nose and FT-NIR combined with deep learning algorithm in preventing age fraud and quality evaluation of pericarpium citri reticulatae Pericarpium citri reticulatae (PCR) is the dried mature fruit peel of <i>Citrus reticulata</i> Blanco and its cultivated varieties in the Brassicaceae family. It can be used as both food and medicine, and has the effect of relieving cough and phlegm, and promoting digestion. The smell and medicinal properties of PCR are aged over the years; only varieties with aging value can be called "Chenpi". That is to say, the storage year of PCR has a great influence on its quality. As the color and smell of PCR of different storage years are similar, some unscrupulous merchants often use PCRs of low years to pretend to be PCRs of high years, and make huge profits. Therefore, we did this study with the aim of establishing a rapid and nondestructive method to identify the counterfeiting of PCR storage year, so as to protect the legitimate rights and interests of consumers. In this study, a classification model of PCR was established by e-eye, flash GC e-nose, and Fourier transform near-infrared (FT-NIR) combined with machine learning algorithms, which can quickly and accurately distinguish PCRs of different storage years. DFA and PLS-DA models were established by flash GC e-nose to distinguish PCRs of different ages, and 8 odor components were identified, among which (+)-limonene and γ-terpinene were the key components to distinguish PCRs of different ages. In addition, the classification and calibration model of PCRs were established by the combination of FT-NIR and machine learning algorithms. The classification models included SVM, KNN, LSTM, and CNN-LSTM, while the calibration models included PLSR, LSTM, and CNN-LSTM. Among them, the CNN-LSTM model built by internal capsule had significantly better classification and calibration performance than the other models. The accuracy of the classification model was 98.21 %. The R<sup>2</sup><sub>P</sub> of age, (+)-limonene and γ-terpinene was 0.9912, 0.9875 and 0.9891, respectively. These results showed that the combination of flash GC e-nose and FT-NIR combined with deep learning algorithm could quickly and accurately distinguish PCRs of different ages. It also provided an effective and reliable method to monitor the quality of PCR in the market. Flash (photography) ; Electronic nose ; Quality (philosophy) ; Computer science ; Artificial intelligence ; Algorithm ; Mathematics ; Machine learning ; Pattern recognition (psychology) ; Physics Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Identification and Quantification in Food
Authors: Hui Feng | Yongqi Chen | Jingyan Song | Bingjie Lu | Caixia Shu | Jiajun Qiao | Yitao Liao | Wanneng Yang
Source: Plant Phenomics (article, 2024-01-01)
Field: Chemistry — Analytical Chemistry

Maturity Classification of Rapeseed Using Hyperspectral Image Combined with Machine Learning Oilseed rape is an important oilseed crop planted worldwide. Maturity classification plays a crucial role in enhancing yield and expediting breeding research. Conventional methods of maturity classification are laborious and destructive in nature. In this study, a nondestructive classification model was established on the basis of hyperspectral imaging combined with machine learning algorithms. Initially, hyperspectral images were captured for 3 distinct ripeness stages of rapeseed, and raw spectral data were extracted from the hyperspectral images. The raw spectral data underwent preprocessing using 5 pretreatment methods, namely, Savitzky-Golay, first derivative, second derivative (D2nd), standard normal variate, and detrend, as well as various combinations of these methods. Subsequently, the feature wavelengths were extracted from the processed spectra using competitive adaptive reweighted sampling, successive projection algorithm (SPA), iterative spatial shrinkage of interval variables (IVISSA), and their combination algorithms, respectively. The classification models were constructed using the following algorithms: extreme learning machine, <i>k</i>-nearest neighbor, random forest, partial least-squares discriminant analysis, and support vector machine (SVM) algorithms, applied separately to the full wavelength and the feature wavelengths. A comparative analysis was conducted to evaluate the performance of diverse preprocessing methods, feature wavelength selection algorithms, and classification models, and the results showed that the model based on preprocessing-feature wavelength selection-machine learning could effectively predict the maturity of rapeseed. The D2nd-IVISSA-SPA-SVM model exhibited the highest modeling performance, attaining an accuracy rate of 97.86%. The findings suggest that rapeseed maturity can be rapidly and nondestructively ascertained through hyperspectral imaging. Hyperspectral imaging ; Artificial intelligence ; Support vector machine ; Pattern recognition (psychology) ; Feature selection ; Feature (linguistics) ; Extreme learning machine ; Computer science ; Linear discriminant analysis ; Random forest ; Mathematics ; Artificial neural network Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Water Quality Monitoring and Analysis
Authors: Aamir Iqbal | Jisung Kwon | Tufail Hassan | Sang Woon Park | Wonhee Lee | Jung‐Min Oh | Junpyo Hong | Juyun Lee | Shabbir Madad Naqvi | Ujala Zafar | Seon Joon Kim | Jong Hyuk Park | Myung‐Ki Kim | Chong Min Koo
Source: Advanced Functional Materials (article, 2024-07-10)
Field: Materials Science — Materials Chemistry

Environmentally Stable and Highly Crystalline MXenes for Multispectral Electromagnetic Shielding up to Millimeter Waves Abstract Advanced electronics and telecommunication devices rely on electromagnetic (EM) waves of a wide frequency range during their operation, thereby necessitating the development of efficient and ultrathin materials for electromagnetic interference (EMI) shielding across multispectral EM waves, particularly those exceeding 100 GHz, equivalent to millimeter wavelengths. Here, this study reveals that highly crystalline Ti 3 C 2 T x MXene exhibits excellent EMI shielding performance across a multispectral frequency range from 100 kHz to 110 GHz, along with outstanding environmental stability and processability for solution coating and film fabrication. Notably, the highly crystalline Ti 3 C 2 T x MXene films exhibit the highest electrical conductivity (18,000 S cm −1 ) and remarkable environmental stability (maintaining &gt;95% electrical conductivity over one year), coupled with effective EMI shielding (up to 106 dB at 110 GHz with an ultrathin thickness of 10 µm), surpassing five other MXenes, including Nb 2 CT x , V 2 CT x , conv.‐Ti 3 C 2 T x , Ti 3 CNT x , and Mo 2 Ti 2 C 3 T x , and different synthetic materials. Furthermore, increasing the thickness, electrical conductivity, and frequency enhances the shielding performance. These results demonstrate the potential of applying MXenes to next‐generation portable electronics, radar systems, and autonomous vehicles. This study also provides insight into the fundamental shielding mechanisms related to material thickness, electrical conductivity, and frequency of EM waves. MXenes ; Materials science ; Electromagnetic shielding ; Multispectral image ; Millimeter ; Extremely high frequency ; Optoelectronics ; Nanotechnology ; Optics ; Remote sensing ; Composite material ; Physics MXene and MAX Phase Materials ; Electromagnetic wave absorption materials ; Antenna Design and Analysis
Authors: Shuifu Liu | Liyi Li | Xinghui Qin | Rongkai Du | Yifan Sun | Shixing Xie | J. Wang | Мaxim S. Моlokeev | Shibo Xi | Jean‐Claude G. Bünzli | Lei Zhou | Mingmei Wu
Source: Advanced Materials (article, 2024-06-25)
Field: Materials Science — Materials Chemistry

Achieving Ultra‐Broadband Sunlight‐Like Emission in Single‐Phase Phosphors: The Interplay of Structure and Luminescence The quest for artificial light sources mimicking sunlight has been a long-standing endeavor, particularly for applications in anticounterfeiting, agriculture, and color hue detection. Conventional sunlight simulators are often cost-prohibitive and bulky. Therefore, the development of a series of single-phase phosphors Ca<sub>9</sub>LiMg<sub>1-x</sub>Al<sub>2x/3</sub>(PO<sub>4</sub>)<sub>7</sub>:0.1Eu<sup>2+</sup> (x = 0-0.75) with sunlight-like emission represents a welcome step towards compact and economical light source alternatives. The phosphors are obtained by an original heterovalent substitution method and emit a broad spectrum spanning from violet to deep red. Notably, the phosphor with x = 0.5 exhibits an impressive full width at half-maximum of 330 nm. A synergistic interplay of experimental investigations and theory unveils the mechanism behind sunlight-like emission due to the local structural perturbations introduced by the heterovalent substitution of Al<sup>3+</sup> for Mg<sup>2+</sup>, leading to a varied distribution of Eu<sup>2+</sup> within the lattice. Subsequent characterization of a series of organic dyes combining absorption spectroscopy with convolutional neural network analysis convincingly demonstrates the potential of this phosphor in portable photodetection devices. Broad-spectrum light source testing empowers the model to precisely differentiate dye patterns. This points to the phosphor being ideal for mimicking sunlight. Beyond this demonstrated application, the phosphor's utility is envisioned in other relevant domains, including visible light communication and smart agriculture. Phosphor ; Sunlight ; Materials science ; Optoelectronics ; Visible spectrum ; Luminescence ; Optics ; Absorption (acoustics) ; Physics Luminescence Properties of Advanced Materials ; Ammonia Synthesis and Nitrogen Reduction ; Advanced Photocatalysis Techniques
Authors: Zhedong Wang | Chao Qian | Pujing Lin | Bin Zheng | Gyeongtae Kim | Jaebum Noh | Er‐Ping Li | Junsuk Rho | Hongsheng Chen
Source: Advanced Materials (article, 2024-05-27)
Field: Materials Science — Electronic, Optical and Magnetic Materials

3D Intelligent Cloaked Vehicle Equipped with Thousand‐Level Reconfigurable Full‐Polarization Metasurfaces A crucial aspect in shielding a variety of advanced electronic devices from electromagnetic detection involves controlling the flow of electromagnetic waves, akin to invisibility cloaks. Decades ago, the exploration of transformation optics heralded the dawn of modern invisibility cloaks, which has stimulated immense interest across various physical scenarios. However, most prior research is simplified to low-dimensional and stationary hidden objects, limiting their practical applicability in a dynamically changing world. This study develops a 3D large-scale intelligent cloak capable of remaining undetectable even in non-stationary conditions. By employing thousand-level reconfigurable full-polarization metasurfaces, this work has achieved an exceptionally high degree of freedom in sculpting the scattering waves as desired. Serving as the core computational unit, a hybrid inverse design enables the cloaked vehicle to respond in real-time, with a rapid reaction time of just 70 ms. These experiments integrate the cloaked vehicle with a perception-decision-control-execution system and evaluate its performance under random static positions and dynamic travelling trajectories, achieving a background scattering matching degree of up to 93.3%. These findings establish a general paradigm for the next generation of intelligent meta-devices in real-world settings, potentially paving the way for an era of "Electromagnetic Internet of Things." Computer science ; Metamaterial ; Cloak ; Invisibility ; Cloaking ; Polarization (electrochemistry) ; Electromagnetic radiation ; Personalization ; Physics ; Optics ; Artificial intelligence Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Antenna Design and Analysis
Authors: Amin Zadehnazari | Florian Auras | Ataf Ali Altaf | Amin Zarei | Ahmad Reza Khosropour | Saeed Amirjalayer | Alireza Abbaspourrad
Source: Nature Communications (article, 2024-12-30)
Field: Materials Science — Materials Chemistry

Recycling e-waste into gold-loaded covalent organic framework catalysts for terminal alkyne carboxylation The rising demand for gold requires innovative methods for its recovery from e-waste. Here we present the synthesis of two tetrazine-based vinyl-linked covalent organic frameworks: TTF-COF and TPE-COF that adsorb gold ions and nanoparticles and catalyze the carboxylation of terminal alkynes. These covalent organic frameworks have low band gaps and high photocurrent responses. TTF-COF has an adsorption capacity toward aqueous Au(III) of 2440 mg g<sup>-1</sup>, and TPE-COF's Au(III) adsorption capacity is 1639 mg g<sup>-1</sup>. The gold source is metal flakes isolated from waste computer processing units. Of the gold present, > 99% is selectively captured by TTF-COF whereas only 5% of the Ni and 2% of the Cu in the solution is adsorbed. The Au-loaded covalent organic frameworks catalyze the carboxylation of terminal alkynes and are stable and reusable for six reuse cycles. Our covalent organic frameworks convert e-waste into a valuable catalyst for a useful green organic transformation. Alkyne ; Carboxylation ; Catalysis ; Terminal (telecommunication) ; Covalent bond ; Chemistry ; Organic chemistry ; Combinatorial chemistry ; Computer science Covalent Organic Framework Applications ; Advanced Photocatalysis Techniques ; Nanomaterials for catalytic reactions
Authors: Hongyuan Li | Ziyu Xiang | Aidan P. Reddy | Trithep Devakul | Renee Sailus | Rounak Banerjee | Takashi Taniguchi | Kenji Watanabe | Sefaattin Tongay | Alex Zettl | Liang Fu | Michael F. Crommie | Feng Wang
Source: Science (article, 2024-07-04)
Field: Materials Science — Materials Chemistry

Wigner molecular crystals from multielectron moiré artificial atoms Semiconductor moiré superlattices provide a versatile platform to engineer quantum solids composed of artificial atoms on moiré sites. Previous studies have mostly focused on the simplest correlated quantum solid-the Fermi-Hubbard model-in which intra-atom interactions are simplified to a single onsite repulsion energy <i>U</i>. Here we report the experimental observation of Wigner molecular crystals emerging from multielectron artificial atoms in twisted bilayer tungsten disulfide moiré superlattices. Using scanning tunneling microscopy, we demonstrate that Wigner molecules appear in multielectron artificial atoms when Coulomb interactions dominate. The array of Wigner molecules observed in a moiré superlattice comprises a crystalline phase of electrons: the Wigner molecular crystal, which is shown to be highly tunable through mechanical strain, moiré period, and carrier charge type. Wigner crystal ; Superlattice ; Moiré pattern ; Scanning tunneling microscope ; Quantum tunnelling ; Condensed matter physics ; Crystal (programming language) ; Electron ; Semiconductor ; Materials science ; Atomic physics ; Quantum ; Molecular physics ; Physics ; Quantum mechanics ; Optics ; Optoelectronics Electronic and Structural Properties of Oxides ; Topological Materials and Phenomena ; 2D Materials and Applications
Authors: Nanasaheb M. Shinde | Martin Pumera
Source: ACS Applied Electronic Materials (article, 2024-09-19)
Field: Materials Science — Materials Chemistry

High Performance MXene/MnCo<sub>2</sub>O<sub>4</sub> Supercapacitor Device for Powering Small Robotics The development of advanced energy storage devices is critical for various applications including robotics and portable electronics. The energy storage field faces significant challenges in designing devices that can operate effectively for extended periods while maintaining exceptional electrochemical performance. Supercapacitors, which bridge the gap between batteries and conventional capacitors, offer a promising solution due to their high power density and rapid charge-discharge capabilities. This study focuses on the fabrication and evaluation of a MXene/MnCo<sub>2</sub>O<sub>4</sub> nanocomposite supercapacitor electrode using a simple and cost-effective electrodeposition method on a copper substrate. The MXene/MnCo<sub>2</sub>O<sub>4</sub> nanocomposite exhibits superior electrochemical properties, including a specific capacitance of 668 F g<sup>-1</sup>, high energy density (35 Wh kg<sup>-1</sup>), and excellent cycling stability (94.6% retention over 5000 cycles). The combination of MXene and MnCo<sub>2</sub>O<sub>4</sub> enhances the redox activity, electronic conductivity, and structural integrity of the electrode. An asymmetric supercapacitor device, incorporating MXene/MnCo<sub>2</sub>O<sub>4</sub> as the positive electrode and Bi<sub>2</sub>O<sub>3</sub> as the negative electrode, demonstrates remarkable performance in powering small robotics and small electronics. This work underscores the potential of MXene-based nanocomposites for high-performance supercapacitor applications, paving the way for future advancements in energy storage technologies. Supercapacitor ; Robotics ; Artificial intelligence ; Materials science ; Computer science ; Robot ; Physics ; Capacitance ; Electrode MXene and MAX Phase Materials ; Advanced Memory and Neural Computing ; Wireless Power Transfer Systems
Authors: Weigao Han | Weitong Ling | Peng Gao | Fang Dong | Zhicheng Tang
Source: Applied Catalysis B: Environmental (article, 2024-01-03)
Field: Materials Science — Materials Chemistry

Engineering Pt single atom catalyst with abundant lattice oxygen by dual nanospace confinement strategy for the efficient catalytic elimination of VOCs Nanocages ; Catalysis ; Calcination ; Oxygen atom ; Atom (system on chip) ; Oxygen ; Oxygen storage ; Chemical engineering ; Molecule ; Materials science ; Lattice (music) ; Heterogeneous catalysis ; Economies of agglomeration ; Nanotechnology ; Chemistry ; Physical chemistry ; Organic chemistry ; Physics Catalytic Processes in Materials Science ; Electrocatalysts for Energy Conversion ; Catalysis and Oxidation Reactions