jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Song Lv | Zuoqin Qian | Dengyun Hu | Xiaoyuan Li | Wei He
Source: Energies (review, 2020-06-17)
Field: Materials Science — Materials Chemistry

A Comprehensive Review of Strategies and Approaches for Enhancing the Performance of Thermoelectric Module In recent years, thermoelectric (TE) technology has been emerging as a promising alternative and environmentally friendly technology for power generators or cooling devices due to the increasingly serious energy shortage and environmental pollution problems. However, although TE technology has been found for a long time and applied in many professional fields, its low energy conversion efficiency and high cost also hinder its wide application. Thus, it is still urgent to improve the thermoelectric modules. This work comprehensively reviews the status of strategies and approaches for enhancing the performance of thermoelectrics, including material development, structure and geometry improvement, the optimization of a thermal management system, and the thermal structure design. In particular, the influence of contact thermal resistance and the improved optimization methods are discussed. This work covers many fields related to the enhancement of thermoelectrics. It is found that the main challenge of TE technology remains the improvement of materials’ properties, the decrease in costs and commercialization. Therefore, a lot of research needs to be carried out to overcome this challenge and further improve the performance of TE modules. Finally, the future research direction of TE technology is discussed. These discussions provide some practical guidance for the improvement of thermoelectric performance and the promotion of thermoelectric applications. Commercialization ; Thermoelectric materials ; Thermoelectric effect ; Environmentally friendly ; Thermoelectric generator ; Efficient energy use ; Thermoelectric cooling ; Work (physics) ; Environmental pollution ; Systems engineering ; Computer science ; Process engineering ; Mechanical engineering ; Manufacturing engineering ; Engineering ; Business ; Environmental science ; Electrical engineering Advanced Thermoelectric Materials and Devices ; Thermal Radiation and Cooling Technologies ; Thermal properties of materials
Authors: Zhenghua Deng | Haiqing Yin | Xue Jiang | Cong Zhang | Guofei Zhang | Bin Xu | Guoqiang Yang | Tong Zhang | Mao Wu | Xuanhui Qu
Source: International Journal of Minerals Metallurgy and Materials (article, 2020-03-01)
Field: Materials Science — Materials Chemistry

Machine-learning-assisted prediction of the mechanical properties of Cu-Al alloy Ultimate tensile strength ; Alloy ; Porosity ; Materials science ; Kernel (algebra) ; Correlation coefficient ; Support vector machine ; Metallurgy ; Computer science ; Mathematics ; Artificial intelligence ; Composite material ; Machine learning Metallurgy and Material Science ; Advanced materials and composites ; Aluminum Alloy Microstructure Properties
Authors: Christian Devereux | Justin S. Smith | Kate Davis | Kipton Barros | R.I. Zubatyuk | Olexandr Isayev | Adrián E. Roitberg
Source: ChemRxiv (preprint, 2020-02-07)
Field: Chemistry — Physical and Theoretical Chemistry

Extending the Applicability of the ANI Deep Learning Molecular Potential to Sulfur and Halogens &lt;p&gt;Machine learning (ML) methods have become powerful, predictive tools in a wide range of applications, such as facial recognition and autonomous vehicles. In the sciences, computational chemists and physicists have been using ML for the prediction of physical phenomena, such as atomistic potential energy surfaces and reaction pathways. Transferable ML potentials, such as ANI-1x, have been developed with the goal of accurately simulating organic molecules containing the chemical elements H, C, N, and O. Here we provide an extension of the ANI-1x model. The new model, dubbed ANI-2x, is trained to three additional chemical elements: S, F, and Cl. Additionally, ANI-2x underwent torsional refinement training to better predict molecular torsion profiles. These new features open a wide range of new applications within organic chemistry and drug development. These seven elements (H, C, N, O, F, Cl, S) make up ~90% of drug like molecules. To show that these additions do not sacrifice accuracy, we have tested this model across a range of organic molecules and applications, including the COMP6 benchmark, dihedral rotations, conformer scoring, and non-bonded interactions. ANI-2x is shown to accurately predict molecular energies compared to DFT with a ~10&lt;sup&gt;6&lt;/sup&gt; factor speedup and a negligible slowdown compared to ANI-1x. The resulting model is a valuable tool for drug development that can potentially replace both quantum calculations and classical force fields for myriad applications.&lt;/p&gt; Dihedral angle ; Benchmark (surveying) ; Halogen ; Molecule ; Computer science ; Speedup ; Computational chemistry ; Chemistry ; Computational science ; Parallel computing ; Organic chemistry Various Chemistry Research Topics ; Computational Drug Discovery Methods ; Machine Learning in Materials Science
Authors: Julia Westermayr | Felix A Faber | Anders S Christensen | O Anatole von Lilienfeld | Philipp Marquetand
Source: Machine Learning Science and Technology (article, 2020-04-14)
Field: Materials Science — Materials Chemistry

Neural networks and kernel ridge regression for excited states dynamics of CH<sub>2</sub>NH 2+ : From single-state to multi-state representations and multi-property machine learning models Abstract Excited-state dynamics simulations are a powerful tool to investigate photo-induced reactions of molecules and materials and provide complementary information to experiments. Since the applicability of these simulation techniques is limited by the costs of the underlying electronic structure calculations, we develop and assess different machine learning models for this task. The machine learning models are trained on ab initio calculations for excited electronic states, using the methylenimmonium cation (CH 2 NH <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"><mml:msubsup><mml:mi/><mml:mn>2</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:math> ) as a model system. Two distinct strategies for modeling excited state properties are tested in this work. The first strategy is to treat each state separately in a kernel ridge regression model and all states together in a multiclass neural network. The second strategy is to instead encode the state as input into the model, which is tested with both models. Numerical evidence suggests that using the state as input yields the best performance. An important goal for excited-state machine learning models is their use in dynamics simulations, which needs not only state-specific information but also couplings, i.e. properties involving pairs of states. Accordingly, we investigate how well machine learning models can predict the couplings. Furthermore, we explore how combining all properties in a single neural network affects the accuracy. Finally, machine learning predicted energies, forces, and couplings are used to carry out excited-state dynamics simulations. Results demonstrate the scopes and possibilities of machine learning to model excited-state properties. Artificial neural network ; Kernel (algebra) ; Regression ; Online machine learning ; Computational learning theory ; Reservoir computing ; Dynamics (music) ; Kernel method Machine Learning in Materials Science ; Advanced Chemical Physics Studies ; Gaussian Processes and Bayesian Inference
Authors: Kenry Kenry | Ben Zhong Tang | Bin Liu
Source: Chem (article, 2020-06-01)
Field: Materials Science — Materials Chemistry

Catalyst: Aggregation-Induced Emission—How Far Have We Come, and Where Are We Going Next? Aggregation-induced emission ; Business ; Chemistry ; Nanotechnology ; Physics ; Materials science ; Optics Luminescence and Fluorescent Materials ; Organic Light-Emitting Diodes Research ; Carbon and Quantum Dots Applications
Authors: Jakob Timmermann | Florian Kraushofer | Nikolaus Resch | Peigang Li | Yu Wang | Zhiqiang Mao | Michele Riva | Yonghyuk Lee | Carsten G. Staacke | Michael Schmid | Christoph Scheurer | Gareth S. Parkinson | Ulrike Diebold | Karsten Reuter
Source: Physical Review Letters (article, 2020-11-10)
Field: Materials Science — Materials Chemistry

<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:msub><mml:mrow><mml:mi>IrO</mml:mi></mml:mrow><mml:mrow><mml:mn>2</mml:mn></mml:mrow></mml:msub></mml:mrow></mml:math> Surface Complexions Identified through Machine Learning and Surface Investigations A Gaussian approximation potential was trained using density-functional theory data to enable a global geometry optimization of low-index rutile IrO_{2} facets through simulated annealing. Ab initio thermodynamics identifies (101) and (111) (1×1) terminations competitive with (110) in reducing environments. Experiments on single crystals find that (101) facets dominate and exhibit the theoretically predicted (1×1) periodicity and x-ray photoelectron spectroscopy core-level shifts. The obtained structures are analogous to the complexions discussed in the context of ceramic battery materials. X-ray photoelectron spectroscopy ; Rutile ; Ab initio ; Materials science ; Context (archaeology) ; Algorithm ; Physics ; Computer science ; Nuclear magnetic resonance ; Chemistry ; Geology ; Quantum mechanics Machine Learning in Materials Science ; X-ray Diffraction in Crystallography ; Electronic and Structural Properties of Oxides
Authors: Mohsen Taheri Andani | Aaditya Lakshmanan | Veera Sundararaghavan | John E. Allison | Amit Misra
Source: Acta Materialia (article, 2020-09-03)
Field: Materials Science — Biomaterials

Quantitative study of the effect of grain boundary parameters on the slip system level Hall-Petch slope for basal slip system in Mg-4Al Materials science ; Electron backscatter diffraction ; Grain boundary strengthening ; Grain boundary ; Slip (aerodynamics) ; Condensed matter physics ; Grain size ; Crystallite ; Dislocation ; Plasticity ; Crystal plasticity ; Geometry ; Composite material ; Crystallography ; Metallurgy ; Microstructure ; Physics ; Thermodynamics ; Mathematics Magnesium Alloys: Properties and Applications ; Microstructure and mechanical properties ; Metal and Thin Film Mechanics
Authors: M. Rosario Cervellere | Xianghong Qian | David M. Ford | Christina Carbrello | Sal Giglia | Paul C. Millett
Source: Journal of Membrane Science (article, 2020-09-25)
Field: Materials Science — Materials Chemistry

Phase-field modeling of non-solvent induced phase separation (NIPS) for PES/NMP/Water with comparison to experiments Solvent ; Membrane ; Coagulation ; Phase (matter) ; Chemical engineering ; Diffusion ; Porosity ; Volume fraction ; Polymer ; Polymer chemistry ; Materials science ; Chemistry ; Analytical Chemistry (journal) ; Chromatography ; Thermodynamics ; Physical chemistry ; Organic chemistry ; Physics Block Copolymer Self-Assembly ; Membrane Separation and Gas Transport ; Membrane Separation Technologies
Authors: Georg Sperl | Rahul Narain | Chris Wojtan
Source: ACM Transactions on Graphics (article, 2020-08-12)
Field: Materials Science — Polymers and Plastics

Homogenized yarn-level cloth We present a method for animating yarn-level cloth effects using a thin-shell solver. We accomplish this through numerical homogenization: we first use a large number of yarn-level simulations to build a model of the potential energy density of the cloth, and then use this energy density function to compute forces in a thin shell simulator. We model several yarn-based materials, including both woven and knitted fabrics. Our model faithfully reproduces expected effects like the stiffness of woven fabrics, and the highly deformable nature and anisotropy of knitted fabrics. Our approach does not require any real-world experiments nor measurements; because the method is based entirely on simulations, it can generate entirely new material models quickly, without the need for testing apparatuses or human intervention. We provide data-driven models of several woven and knitted fabrics, which can be used for efficient simulation with an off-the-shelf cloth solver. Yarn ; Solver ; Homogenization (climate) ; Stiffness ; Anisotropy ; Computer science ; Woven fabric ; Materials science ; Composite material ; Physics Textile materials and evaluations ; 3D Shape Modeling and Analysis ; Composite Material Mechanics
Authors: Taoyu Weng | Glib Baryshnikov | Chao Deng | Xuping Li | Bin Wu | Hongwei Wu | Hans Ågren | Qi Zou | Tao Zeng | Liangliang Zhu
Source: Small (article, 2020-01-29)
Field: Materials Science — Materials Chemistry

A Fluorescence–Phosphorescence–Phosphorescence Triple‐Channel Emission Strategy for Full‐Color Luminescence Organic luminogens constitute promising prototypes for various optoelectronic applications. Since gaining distinct color emissions normally requires the alternation of the conjugated backbone, big issues remain in material synthetic cost and skeleton compatibility while pursuing full-color luminescence. Upon a facile one-step coupling, three simple but smart perchalcogenated (O, S, and Se) arenes are synthesized. They exhibit strong luminescent tricolor primaries (i.e., blue, green, and red, respectively) in the solid state with a superior quantum yield up to >40% (5-10 times higher than that in corresponding solutions). The properties originate from a fluorescence-phosphorescence-phosphorescence triple-channel emission effect, which is regulated by S and Se heavy atoms-dependent intersystem crossing upon molecular packing, as well as Se-Se atom interaction-caused energy splittings. Consequently, full-color luminescence, including a typical white-light luminescence with a Commission Internationale de I'Eclairage coordinate of (0.30, 0.35), is realized by complementarily incorporating these tricolor luminescent materials in the film. Moreover, mechanochromic luminescent color conversions are also observed to achieve the fine-tuning of the luminescent tints. This strategy can be smart to address full-color luminescence on the same molecular skeleton, showing better material compatibility as an alternative to the traditional multiple-luminophore engineering. Phosphorescence ; Luminescence ; Fluorescence ; Persistent luminescence ; Photochemistry ; Materials science ; Luminescent Measurements ; Optoelectronics ; Chemistry ; Optics ; Physics Luminescence and Fluorescent Materials ; Organic Light-Emitting Diodes Research ; Molecular Sensors and Ion Detection
Authors: Zhaoqiang Zhang | Qi Ding | Xili Cui | Xiao‐Ming Jiang | Huabin Xing
Source: ACS Applied Materials & Interfaces (article, 2020-08-10)
Field: Chemistry — Inorganic Chemistry

Fine-Tuning and Selective-Binding within an Anion-Functionalized Ultramicroporous Metal–Organic Framework for Efficient Olefin/Paraffin Separation Olefin/paraffin separation is one of the intrinsically challenging tasks, mainly realized through the energy-intensive cryogenic distillation techniques. Here, we report the efficient separation of both propylene/propane (C<sub>3</sub>H<sub>6</sub>/C<sub>3</sub>H<sub>8</sub>) and ethylene/ethane (C<sub>2</sub>H<sub>4</sub>/C<sub>2</sub>H<sub>6</sub>) mixtures for the first time by a cheap and customized anion-functionalized metal-organic framework, ZU-36 (also termed as GeFSIX-3-M, M = Ni<sup>2+</sup>, Co<sup>2+</sup>), through molecular recognition and cross-section matching mechanism. Specifically, the pore window size of the fine-tuned ZU-36-Ni (4.42 × 4.42 Å<sup>2</sup>) decorated with high density of electronegative anions matches well with the cross section of C<sub>3</sub>H<sub>6</sub> (4.16 × 4.65 Å<sup>2</sup>) and C<sub>2</sub>H<sub>4</sub> (3.28 × 4.18 Å<sup>2</sup>), leading to efficient separation of C<sub>3</sub>H<sub>6</sub>/C<sub>3</sub>H<sub>8</sub> and C<sub>2</sub>H<sub>4</sub>/C<sub>2</sub>H<sub>6</sub>. The high uptake capacity and separation selectivity of ZU-36-Ni were confirmed by adsorption isotherms and breakthrough tests. Binary dynamic breakthrough results showed that ZU-36-Ni can trap 1.35 mmol g<sup>-1</sup> C<sub>3</sub>H<sub>6</sub> and 1.08 mmol g<sup>-1</sup> C<sub>2</sub>H<sub>4</sub> from C<sub>3</sub>H<sub>6</sub>/C<sub>3</sub>H<sub>8</sub> and C<sub>2</sub>H<sub>4</sub>/C<sub>2</sub>H<sub>6</sub> mixtures, respectively. The separation selectivity for C<sub>3</sub>H<sub>6</sub>/C<sub>3</sub>H<sub>8</sub> on ZU-36-Ni calculated from the breakthrough tests is 19, which sets a new benchmark for C<sub>3</sub>H<sub>6</sub>/C<sub>3</sub>H<sub>8</sub> separation. The proposed cross-section matching mechanism together with proper selective binding affinity may serve as a guide for the design of effective porous materials for other important gas separation. Propane ; Materials science ; Olefin fiber ; Selectivity ; Adsorption ; Air separation ; Metal-organic framework ; Chemical engineering ; Gas separation ; Metal ; Selective adsorption ; Butanol ; Physical chemistry ; Membrane ; Organic chemistry ; Catalysis ; Polymer ; Chemistry ; Composite material ; Ethanol Metal-Organic Frameworks: Synthesis and Applications ; Membrane Separation and Gas Transport ; Gas Sensing Nanomaterials and Sensors
Authors: Kening Lang | Regina J. Sánchez-Leija | Richard A. Gross | Robert J. Linhardt
Source: Polymers (review, 2020-12-12)
Field: Materials Science — Biomaterials

Review on the Impact of Polyols on the Properties of Bio-Based Polyesters Bio-based polyol polyesters are biodegradable elastomers having potential utility in soft tissue engineering. This class of polymers can serve a wide range of biomedical applications. Materials based on these polymers are inherently susceptible to degradation during the period of implantation. Factors that influence the physicochemical properties of polyol polyesters might be useful in achieving a balance between durability and biodegradability. The characterization of these polyol polyesters, together with recent comparative studies involving creative synthesis, mechanical testing, and degradation, have revealed many of their molecular-level differences. The impact of the polyol component on the properties of these bio-based polyesters and the optimal reaction conditions for their synthesis are only now beginning to be resolved. This review describes our current understanding of polyol polyester structural properties as well as a discussion of the more commonly used polyol monomers. Polyol ; Polyester ; Materials science ; Biodegradation ; Polymer ; Elastomer ; Monomer ; Degradation (telecommunications) ; Polymer science ; Organic chemistry ; Chemistry ; Polyurethane ; Composite material ; Computer science biodegradable polymer synthesis and properties ; Electrospun Nanofibers in Biomedical Applications ; Polymer composites and self-healing
Authors: James R. Wester | Jacob A. Lewis | Ronit Freeman | Hiroaki Sai | Liam C. Palmer | Stephen E. Henrich | Samuel I. Stupp
Source: Journal of the American Chemical Society (article, 2020-06-29)
Field: Materials Science — Biomaterials

Supramolecular Exchange among Assemblies of Opposite Charge Leads to Hierarchical Structures Hierarchical assemblies of proteins into fibrillar structures occur in both physiologic and pathologic extracellular spaces and often involve interactions between oppositely charged peptide domains. However, the interplay between tertiary structure dynamics and quaternary hierarchical structure formation remains unclear. In this work, we investigate supramolecular mimics of these systems by mixing one-dimensional assemblies of small alkylated peptides bearing opposite charge and varying in peptide sequence. We found that assemblies with weak cohesive interactions readily create fibrous superstructures of bundled filaments as molecules redistribute upon mixing. Low cohesion allows molecules to escape from the original assemblies and exchange dynamics help them reassemble into electrostatically stable bundles. However, we also found that kinetic barriers can be encountered in these systems and limit formation of the hierarchical structures at pH values where charge densities are high. Increasing intermolecular cohesion using longer peptide sequences that form stable β-sheets was found to suppress superstructure formation. Our findings suggest that low internal cohesion in protein systems could facilitate the conformational rearrangements required to create hierarchical structures. Chemistry ; Chemical physics ; Supramolecular chemistry ; Intermolecular force ; Molecule ; Cohesion (chemistry) ; Superstructure ; Peptide ; Crystallography ; Nanotechnology ; Biophysics ; Crystal structure ; Materials science Supramolecular Self-Assembly in Materials ; Polydiacetylene-based materials and applications ; Luminescence and Fluorescent Materials
Authors: Carla Jiménez‐Jiménez | Miguel Manzano | María Vallet‐Regí
Source: Biology (review, 2020-11-18)
Field: Materials Science — Biomaterials

Nanoparticles Coated with Cell Membranes for Biomedical Applications Nanoparticles designed for diagnosing and treating different diseases have impacted the scientific research in biomedicine, and are expected to revolutionize the clinic in the near future through a new area called nanomedicine. In the last few years, a new approach in this field has emerged: the use of cell membranes for coating nanoparticles in an attempt to mimic the ability of cells to interface and interact with physiological environments. Although such functions have been replicated through synthetic techniques, many research groups are now employing naturally derived cell membranes to coat different types of nanoparticles in an attempt to improve their performance for a wide range of applications. This review summarizes the literature on nanoparticles coated with cell membranes and, more importantly, aims at inspiring and encouraging new developments to this technology in the biomedical area. Nanomedicine ; Biomedicine ; Nanotechnology ; Membrane ; Nanoparticle ; Biology ; Materials science ; Bioinformatics ; Biochemistry Nanoparticle-Based Drug Delivery ; Nanoplatforms for cancer theranostics ; RNA Interference and Gene Delivery
Authors: Jeongmin Hwang | Millicent O. Sullivan | Kristi L. Kiick
Source: Frontiers in Bioengineering and Biotechnology (review, 2020-02-18)
Field: Materials Science — Biomaterials

Targeted Drug Delivery via the Use of ECM-Mimetic Materials The use of drug delivery vehicles to improve the efficacy of drugs and to target their action at effective concentrations over desired periods of time has been an active topic of research and clinical investigation for decades. Both synthetic and natural drug delivery materials have facilitated locally controlled as well as targeted drug delivery. Extracellular matrix (ECM) molecules have generated widespread interest as drug delivery materials owing to the various biological functions of ECM. Hydrogels created using ECM molecules can provide not only biochemical and structural support to cells, but also spatial and temporal control over the release of therapeutic agents, including small molecules, biomacromolecules, and cells. In addition, the modification of drug delivery carriers with ECM fragments used as cell-binding ligands has facilitated cell-targeted delivery and improved the therapeutic efficiency of drugs through interaction with highly expressed cellular receptors for ECM. The combination of ECM-derived hydrogels and ECM-derived ligand approaches shows synergistic effects, leading to a great promise for the delivery of intracellular drugs, which require specific endocytic pathways for maximal effectiveness. In this review, we provide an overview of cellular receptors that interact with ECM molecules and discuss examples of selected ECM components that have been applied for drug delivery in both local and systemic platforms. Finally, we highlight the potential impacts of utilizing the interaction between ECM components and cellular receptors for intracellular delivery, particularly in tissue regeneration applications. Drug ; Drug delivery ; Pharmacology ; Chemistry ; Medicine ; Nanotechnology ; Materials science Nanoparticle-Based Drug Delivery ; Electrospun Nanofibers in Biomedical Applications ; Electrohydrodynamics and Fluid Dynamics