jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Tuan Le | Julian Cremer | Frank Noé | Djork-Arné Clevert | Kristof T. Schütt
Source: arXiv (Cornell University) (preprint, 2023-09-29)
Field: Materials Science — Materials Chemistry

Navigating the Design Space of Equivariant Diffusion-Based Generative Models for De Novo 3D Molecule Generation Deep generative diffusion models are a promising avenue for 3D de novo molecular design in materials science and drug discovery. However, their utility is still limited by suboptimal performance on large molecular structures and limited training data. To address this gap, we explore the design space of E(3)-equivariant diffusion models, focusing on previously unexplored areas. Our extensive comparative analysis evaluates the interplay between continuous and discrete state spaces. From this investigation, we present the EQGAT-diff model, which consistently outperforms established models for the QM9 and GEOM-Drugs datasets. Significantly, EQGAT-diff takes continuous atom positions, while chemical elements and bond types are categorical and uses time-dependent loss weighting, substantially increasing training convergence, the quality of generated samples, and inference time. We also showcase that including chemically motivated additional features like hybridization states in the diffusion process enhances the validity of generated molecules. To further strengthen the applicability of diffusion models to limited training data, we investigate the transferability of EQGAT-diff trained on the large PubChem3D dataset with implicit hydrogen atoms to target different data distributions. Fine-tuning EQGAT-diff for just a few iterations shows an efficient distribution shift, further improving performance throughout data sets. Finally, we test our model on the Crossdocked data set for structure-based de novo ligand generation, underlining the importance of our findings showing state-of-the-art performance on Vina docking scores. Computer science ; Chemical space ; Categorical variable ; Generative grammar ; Weighting ; Data mining ; Artificial intelligence ; Algorithm ; Theoretical computer science ; Machine learning ; Drug discovery ; Physics ; Chemistry Machine Learning in Materials Science ; Protein Structure and Dynamics ; Computational Drug Discovery Methods
Authors: Tzu‐Jung Huang | Adheesh Ankolekar | Aníbal Pacheco-Sánchez | Ivan Puchades
Source: Applied Sciences (article, 2023-06-16)
Field: Materials Science — Materials Chemistry

Investigating the Device Performance Variation of a Buried Locally Gated Al/Al2O3 Graphene Field-Effect Transistor Process In this study, a process is developed for the fabrication of buried top-gated graphene transistors with Al2O3 as a gate dielectric, yielding devices that can be suitable for not only flexible electronics but also laser-induced graphene (LIG)-based technology implementations. A new processing option is presented with the use of tetraethyl-orthosilicate (TEOS) as an etch stop for contact via etching of Al2O3. Buried locally gated Al/Al2O3 graphene field-effect transistors (GFETs) are fabricated with Dirac points as low as 4 V, with a metal-to-graphene contact resistance as low as ∼1.7 kΩ·µm, and an average hole mobility of 457.97 cm2/V·s with a non-uniformity of 93%. Large device variation and non-uniformity in electrical performance are not uncommon for graphene-based devices, as process-induced defects play a major role in such variation. AFM, SEM, Raman spectroscopy, and model fitting indicated that the rough Al/Al2O3 surface was the main factor for the observed device variation. AFM analysis indicated a graphene surface roughness Ra of 16.19 nm on top of the buried Al/Al2O3 gate in contrast to a Ra of 4.06 nm over Al2O3/SiO2. The results presented indicate the need to reduce device variability and non-uniformity by improving transfer methods, as well as the use of smoother surfaces and compatible materials. The presented analyses provide a framework with which other researchers can analyze and correlate device variation and non-uniformities while methods to reduce variability are investigated. Graphene ; Materials science ; Transistor ; Raman spectroscopy ; Field-effect transistor ; Optoelectronics ; Etching (microfabrication) ; Contact resistance ; Nanotechnology ; Surface roughness ; Surface finish ; Composite material ; Optics ; Electrical engineering ; Layer (electronics) ; Voltage Graphene research and applications ; Diamond and Carbon-based Materials Research ; Nanowire Synthesis and Applications
Authors: Jack B. Greisman | Kevin M. Dalton | Dennis E. Brookner | Margaret A. Klureza | Candice J. Sheehan | In‐Sik Kim | Robert Henning | Silvia Russi | Doeke R. Hekstra
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2023-06-03)
Field: Materials Science — Materials Chemistry

Resolving conformational changes that mediate a two-step catalytic mechanism in a model enzyme Enzymes catalyze biochemical reactions through precise positioning of substrates, cofactors, and amino acids to modulate the transition-state free energy. However, the role of conformational dynamics remains poorly understood due to lack of experimental access. This shortcoming is evident with <i>E. coli</i> dihydrofolate reductase (DHFR), a model system for the role of protein dynamics in catalysis, for which it is unknown how the enzyme regulates the different active site environments required to facilitate proton and hydride transfer. Here, we present ligand-, temperature-, and electric-field-based perturbations during X-ray diffraction experiments that enable identification of coupled conformational changes in DHFR. We identify a global hinge motion and local networks of structural rearrangements that are engaged by substrate protonation to regulate solvent access and promote efficient catalysis. The resulting mechanism shows that DHFR's two-step catalytic mechanism is guided by a dynamic free energy landscape responsive to the state of the substrate. Mechanism (biology) ; Enzyme ; Chemistry ; Conformational change ; Catalysis ; Biophysics ; Stereochemistry ; Biochemistry ; Biology ; Physics Enzyme Structure and Function ; Protein Structure and Dynamics ; Photosynthetic Processes and Mechanisms
Authors: Fu Liu | Qingqing Wang | Yuchao Tang | Wan Du | Weiwei Chang | Zewei Fu | Xinluo Zhao | Yi Liu
Source: Nanoscale (article, 2023-01-01)
Field: Materials Science — Materials Chemistry

Carbon nanowires made by the insertion-and-fusion method toward carbon–hydrogen nanoelectronics Carbon nanowires can be made via the insertion-and-fusion of short carbon chains inside carbon nanotubes, and carry H adatoms that can tune the electronic and magnetic properties of carbon chains upon the varied H positions in C–H nanoelectronics. Nanoelectronics ; Materials science ; Carbon nanotube ; Nanowire ; Carbon fibers ; Nanotechnology ; Hydrogen ; Fusion ; Chemistry ; Organic chemistry ; Composite material Graphene research and applications ; Carbon Nanotubes in Composites ; Advancements in Battery Materials
Authors: Mehrnaz Ebrahimi | Parviz Norouzi | Jahan B. Ghasemi | Ali Akbar Moosavi‐Movahedi | Meissam Noroozifar | Razieh Salahandish
Source: Scientific Reports (article, 2023-10-05)
Field: Chemistry — Spectroscopy

Advancing chirality analysis through enhanced enantiomer characterization and quantification via fast Fourier transform capacitance voltammetry The exploration of the chiral configurations of enantiomers represents a highly intriguing realm of scientific inquiry due to the distinct roles played by each enantiomer (D and L) in chemical reactions and their practical utilities. This study introduces a pioneering analytical methodology, termed fast Fourier transform capacitance voltammetry (FFT-CPV), in conjunction with principal component analysis (PCA), for the identification and quantification of the chiral forms of tartaric acid (TA), serving as a representative model system for materials exhibiting pronounced chiral characteristics. The proposed methodology relies on the principle of chirality, wherein the capacitance signal generated by the adsorption of D-TA and L-TA onto the surface of a platinum electrode (Pt-electrode) in an acidic solution is harnessed. The capacitance voltammograms were meticulously recorded under optimized experimental conditions. To compile the final dataset for the analyte, the average of the FFT capacitance voltammograms of the acidic solution (without the presence of the analyte) was subtracted from those containing the analyte. A distinct arrangement was obtained by employing PCA as a linear data transformation method, representing D-TA and L-TA in a two/three-dimensional space. The outcomes of the study reveal the successful detection of the two chiral forms of TA with a considerable degree of precision and reproducibility. Moreover, the proposed method facilitated the establishment of two linear response ranges for the concentration values of each enantiomer, spanning from 1 to 20 µM, and 50 to 500 µM. The respective detection limits were also determined to be 0.4 µM for L-TA and 1.3 µM for D-TA. These findings underscore the satisfactory sensitivity and efficiency of the proposed method in both qualitative and quantitative assessments of the chiral forms of TA. Fourier transform ; Cyclic voltammetry ; Capacitance ; Characterization (materials science) ; Enantiomer ; Voltammetry ; Chirality (physics) ; Analytical Chemistry (journal) ; Fourier analysis ; Materials science ; Chemistry ; Nanotechnology ; Chromatography ; Physics ; Physical chemistry ; Stereochemistry ; Electrode ; Electrochemistry Molecular spectroscopy and chirality ; Electrochemical Analysis and Applications ; Advanced Chemical Sensor Technologies
Authors: S. Chandra Shekar | Frédéric A. Perras
Source: The Journal of Physical Chemistry C (article, 2023-04-07)
Field: Chemistry — Spectroscopy

Multiplex Detection of Multiple-Quantum/Single-Quantum NMR Correlation Spectra High-ordered multiple-quantum coherences have been used to gauge the size of coupled networks of nuclear spins but are seldom used in modern high-resolution solid-state NMR spectroscopy due to the low resolution of earlier techniques. Herein, we extend this work to the third dimension by designing an MQ spin counting experiment with full chemical resolution of the nuclei involved in the coherences. The technique uses multiplex processing to simultaneously acquire MQ/1Q correlation 2D spectra, with all even-ordered values of M, in the same amount of time it would take to acquire the 2Q/1Q spectrum alone. We apply this multiplexed MQ/1Q correlation method to probe site clustering on functionalized silica surfaces and find the first evidence of clusters involving three or more functionalities. When applied to a supported zirconium metallocene, the observation of a 6Q coherence between six cyclopentadienyl proton nuclei confirms the colocation of two cyclopentadienyl ligands on a single metal center. Spectral line ; Spins ; Cyclopentadienyl complex ; Resolution (logic) ; Two-dimensional nuclear magnetic resonance spectroscopy ; Spectroscopy ; Multiplex ; Nuclear magnetic resonance spectroscopy ; Chemistry ; Materials science ; Analytical Chemistry (journal) ; Physics ; Nuclear magnetic resonance ; Quantum mechanics ; Condensed matter physics ; Computer science ; Organic chemistry ; Bioinformatics Advanced NMR Techniques and Applications ; Solid-state spectroscopy and crystallography ; Atomic and Subatomic Physics Research
Authors: Naoyuki Shoji | Takefumi Yamashita
Source: The Journal of Physical Chemistry B (article, 2023-10-16)
Field: Materials Science — Materials Chemistry

Tensile Stress Reduction and Strain Concentration of Epoxy Resin Caused by Heterogeneity: A Multiscale Approach Combining Molecular Dynamics Simulation and Finite Element Method In this study, we investigated the effect of heterogeneity on the mechanical properties of epoxy resin by combining coarse-grained molecular dynamics (CG-MD) and finite element method (FEM) simulations. To evaluate the heterogeneity effect in the uniaxial elongation, heterogeneous and homogeneous FEM models of micrometer-scale cubic epoxy resin were constructed. For the heterogeneous FEM model, parameters of nanometer-scale elements were determined by CG-MD simulations, where nanometer-scale blocks have different cross-linked structures. For the homogeneous FEM model, the averaged parameters were used for all elements. The calculated stress-strain (S-S) curves of the heterogeneous model exhibit similar tensile stress values when compared to the experimental data, whereas the homogeneous model yields notably higher values. Moreover, a clear strain concentration associated with the formation of the shear band-like structure was observed in the heterogeneous model and not in the homogeneous model. Finite element method ; Epoxy ; Materials science ; Molecular dynamics ; Ultimate tensile strength ; Composite material ; Homogeneous ; Nanometre ; Elongation ; Stress (linguistics) ; Micrometer ; Thermodynamics ; Chemistry ; Computational chemistry ; Physics Carbon Nanotubes in Composites ; Force Microscopy Techniques and Applications ; Composite Material Mechanics
Authors: Chen Xiangxun | Shehzahdi S. Moonshi | Nam‐Trung Nguyen | Hang T. Ta
Source: Nanotechnology (article, 2023-10-20)
Field: Materials Science — Biomaterials

Preparation of protein-loaded nanoparticles based on poly(succinimide)-oleylamine for sustained protein release: a two-step nanoprecipitation method Currently, the treatment for acute disease encompasses the use of various biological drugs (BDs). However, the utilisation of BDs is limited due to their rapid clearance and non-specific accumulation in unwanted sites, resulting in a lack of therapeutic efficacy together with adverse effects. While nanoparticles are considered good candidates to resolve this problem, some available polymeric carriers for BDs were mainly designed for long-term sustained release. Thus, there is a need to explore new polymeric carriers for the acute disease phase that requires sustained release of BDs over a short period, for example for thrombolysis and infection. Poly(succinimide)-oleylamine (PSI-OA), a biocompatible polymer with a tuneable dissolution profile, represents a promising strategy for loading BDs for sustained release within a 48-h period. In this work, we developed a two-step nanoprecipitation method to load the model protein (e.g. bovine serum albumin and lipase) on PSI-OA. The characteristics of the nanoparticles were assessed based on various loading parameters, such as concentration, stirring rate, flow rate, volume ratio, dissolution and release of the protein. The optimised NPs displayed a size within 200 nm that is suitable for vasculature delivery to the target sites. These findings suggest that PSI-OA can be employed as a carrier for BDs for applications that require sustained release over a short period. Succinimide ; Oleylamine ; Materials science ; Nanoparticle ; Chemical engineering ; Nanotechnology ; Organic chemistry ; Chemistry Nanoparticle-Based Drug Delivery ; Advanced Drug Delivery Systems ; Polymer Surface Interaction Studies
Authors: S M Shakil | Muhammad Sanaullah
Source:  (article, 2023-06-15)
Field: Materials Science — Materials Chemistry

Analyzing the Operational Parameters of a Single Walled Carbon Nanotube Field Effect Transistor (SWCNT-FET) Gordon Moore, the co-founder of Intel, predicted that the number of transistors would quadruple every two years. As a result, device scaling had to happen. Scientists and researchers quickly learned that silicon MOSFETs had a scaling issue with technology. Carbon nanotube field effect transistors (CNTFET) are now replacing silicon metal oxide semiconductor field effect transistors (MOSFET) as an alternative. However, whereas we have access to precise circuit-level equations for MOSFETs, all we have for carbon nanotubes are model equations. In this research, we seek to model the behavior of the SWCNT-FET under varying conditions of diameter and gate insulator thickness. This would allow for more accurate performance predictions from the device, paving the way for more complicated CNTFET based circuit designs. Variations in mobile charges, drain currents, and gate insulator thickness are among the variables investigated. Simulation results demonstrate that the size of CNT diameter has direct influence on drain current which could be potential replacement of silicon technology for digital applications. Carbon nanotube ; Carbon nanotube field-effect transistor ; Materials science ; Field-effect transistor ; Transistor ; Nanotechnology ; Optoelectronics ; Electrical engineering ; Engineering ; Voltage Carbon Nanotubes in Composites
Authors: Md Abdur Rahman Bin Abdus Salam | Md Ashiqur Rahman | M. Humaun Kabir | Elmmer Vera Alvarado | Tousif Sadman | Rajib Mahamud | Lawrence Cano | Ali Ashraf
Source: MRS Advances (article, 2023-07-13)
Field: Materials Science — Polymers and Plastics

Testing and modeling of an in situ shear exfoliated 2D nanocomposite coating casing material for the suppression of Li-ion battery fires in electric vehicles Materials science ; Composite material ; Coating ; Casing ; Nanocomposite ; Polycarbonate ; Curing (chemistry) ; Silicone ; Flammability ; Polymer Flame retardant materials and properties ; Fire dynamics and safety research ; Combustion and Detonation Processes
Authors: Jiawei Xie | Jinhui Zou | Liangcheng Tong | Syie Luing Wong | Xin Guo | Hang Qin | Pengzhao Gao | Wenming Guo | Hanning Xiao
Source: Journal of Materiomics (article, 2023-08-11)
Field: Materials Science — Ceramics and Composites

Fabrication and evaluation of high-performance 3D interpenetrated network structures SiC/Al composites with high-purity plate-like α-SiC framework To reinforce compatibility with the thermophysical and mechanical properties of SiC/Al composites for electronic packaging to improve the stability and reduce fatigue failure of electronic integrated devices, a novel 3D SiC reinforced framework with interpenetrated plate-like α-SiC grains was synthesized. A small amount of doped α-SiC was seeded to induce the transformation of β-SiC to plate-like α-SiC at 2300 °C, forming a high-purity α-SiC strongly bonded framework. Vacuum/gas pressure infiltration of Al alloy was subsequently used to manufacture the 3D interpenetrated network structure SiC/Al (SiC3D/Al) composite. Characterization results showed that 15 % (in mass) seeds provided the composite with the optimal comprehensive performance, including a low coefficient of thermal expansion (CTE) of 5.54 × 10−6 K−1, a high thermal conductivity (λ) of 239.08 W m−1 K−1, the highest flexural strength of 326.84 MPa, and a low thermal deformation parameter (TDP) of 0.023. High-purity plate-like grains enhanced the purity of the framework promoting a significant improvement in λ. As the seed content increased to 20 % (in mass), both λ and CTE reached optimal values of 5.22 × 10−6 K−1 and 243.14 W m−1 K−1, but the mechanical properties declined by 10.30 %. The synergistic effect of the well-bonded interface and the high-purity 3D SiC framework balanced excellent mechanical properties and multiple thermal functions. Materials science ; Flexural strength ; Composite material ; Fabrication ; Thermal expansion ; Composite number ; Thermal conductivity ; Thermal stability ; Alloy ; Compatibility (geochemistry) ; Doping ; Optoelectronics Advanced ceramic materials synthesis ; Aluminum Alloys Composites Properties ; Thermal properties of materials
Authors: François Duprat | Jean-Luc Ploix | Jean‐Marie Aubry | Théophile Gaudin
Source: Molecules (article, 2023-09-26)
Field: Chemistry — Physical and Theoretical Chemistry

Fast and Accurate Prediction of Refractive Index of Organic Liquids with Graph Machines The refractive index (RI) of liquids is a key physical property of molecular compounds and materials. In addition to its ubiquitous role in physics, it is also exploited to impart specific optical properties (transparency, opacity, and gloss) to materials and various end-use products. Since few methods exist to accurately estimate this property, we have designed a graph machine model (GMM) capable of predicting the RI of liquid organic compounds containing up to 16 different types of atoms and effective in discriminating between stereoisomers. Using 8267 carefully checked RI values from the literature and the corresponding 2D organic structures, the GMM provides a training root mean square relative error of less than 0.5%, i.e., an RMSE of 0.004 for the estimation of the refractive index of the 8267 compounds. The GMM predictive ability is also compared to that obtained by several fragment-based approaches. Finally, a Docker-based tool is proposed to predict the RI of organic compounds solely from their SMILES code. The GMM developed is easy to apply, as shown by the video tutorials provided on YouTube. Gloss (optics) ; Refractive index ; Opacity ; Mean squared error ; Physical property ; Computer science ; Graph ; Biological system ; Algorithm ; Artificial intelligence ; Materials science ; Mathematics ; Optics ; Chemistry ; Theoretical computer science ; Statistics ; Organic chemistry ; Physics ; Nanotechnology ; Optoelectronics Various Chemistry Research Topics ; Computational Drug Discovery Methods ; Molecular spectroscopy and chirality
Authors: Antonios-Dimitrios Stefanou | Xanthippi Zianni
Source: Nanoscale (article, 2023-01-01)
Field: Materials Science — Materials Chemistry

A physics rule to design aperiodic width-modulated waveguides for minimum phonon transmission with Bayesian optimization Aperiodic nano-waveguides (nWVGs) and superlattices (SLs) limit phonon transmission and heat conduction much more efficiently than periodic ones. They could block parasitic heat conduction that restricts heat management and energy conversion at the nanoscale. Aperiodicity can be realized in multiple ways and with variable degrees of complexity. Machine learning optimization of hetero-SLs for minimum coherent phonon conduction showed optimal aperiodicity for moderate disorder against physics intuition. Here, we report on optimal aperiodicity in width-modulated nWVGS for maximum disorder as expected by physics. Optimizing aperiodic geometry modulation is particularly challenging due to the enormous possible configurations. We set up a feasible optimization problem removing unnecessary complexity and we demonstrate efficient Bayesian optimization. Our results confirm the predicted physics rule that minimum thermal conductance occurs for the most disordered arrays of modulation units; the degree of disorder being quantified by the number of non-identical modulation units. Our work opens a route to design geometrical aperiodicity and control transmission across metamaterials. Aperiodic graph ; Bayesian optimization ; Phonon ; Thermal conduction ; Modulation (music) ; Transmission (telecommunications) ; Physics ; Condensed matter physics ; Materials science ; Statistical physics ; Mathematics ; Computer science ; Quantum mechanics ; Mathematical optimization ; Combinatorics ; Acoustics Thermal properties of materials ; Thermal Radiation and Cooling Technologies ; Advanced Thermoelectric Materials and Devices