Hasil untuk "Chemical industries"

Manal S. Ebaid, Hanaa Farag, Mohamed Abdelraof et al.

Since the discovery of penicillin in the 1930s, antibiotics have been the primary treatment for bacterial infections. However, antimicrobial resistance (AMR) has escalated due to antibiotics overuse and misuse. To address this concern, a new series of coumarin-thiazole derivatives was synthesized and evaluated against Serratia fonticola, Campylobacter jejuni, Enterococcus faecalis, and Achromobacter xylosoxidans. Most compounds showed selective activity, with compounds 6a and 6c exhibiting potent effects against E. faecalis (MICs: 25, 12.5 μg/mL) and A. xylosoxidans (MICs: 50, 25 μg/mL), comparable to ciprofloxacin. Further studies revealed that 6a and 6c effectively disrupted bacterial biofilms with a low resistance risk. Mechanistically, they induced ROS production, thereby impairing redox homeostasis and reducing lipid peroxidation. Additionally, compound 6a inhibited E. coli DNA gyrase (IC50 = 23.75 μg/mL). Molecular docking studies (PDB ID: 4duh) and dynamics simulations confirmed the stable binding of these compounds to DNA gyrase, suggesting their potential as novel antibacterial agents. These findings highlight promising avenues for the development of new therapeutic agents to combat AMR.

Qihang Ren, Yang Zhang, Haoliang Tao et al.

Achieving thermal cycle stability is an imperative challenge for the successful commercialization of solid oxide cell (SOC) technology. Ruddlesden‒Popper (R‒P) oxides, whose thermal expansion coefficient (TEC) is compatible with common electrolytes, are promising candidates for SOC applications. However, the two-dimensional conduction characteristic of R‒P oxides leads to insufficient catalytic activity, which hinders their performance. Here, we propose a win‒win strategy for self-assembly decoration by employing a one-pot method to address this issue. By using a single perovskite oxide (La0.4Sr0.6FeO3) to modify R‒P oxide (La0.8Sr1.2FeO4+δ), we enhanced the electrochemical performance without compromising the stability of the composite electrode. The strategic incorporation of a 10 mol% perovskite phase at 800 °C resulted in a significant 49% reduction in the polarization resistance (Rp), an impressive 86% increase in the maximum power density under power generation mode, and a notable 33% increase in the electrolysis current density under electrolysis mode. Furthermore, the perovskite-decorated R‒P oxide composite also exhibited high thermal and chemical stability, with negligible performance degradation observed under both thermal cycling and charge/discharge cycling conditions. Our results demonstrate that such dual-phase composites, which are simultaneously produced by a one-step process with outstanding catalytic activity and stability, can be considered an effective strategy for the advancement of SOCs.

Yu Zhang, Ruijie Yu, Kaipeng Zeng et al.

Identifying reaction conditions that are broadly applicable across diverse substrates is a longstanding challenge in chemical and pharmaceutical research. While many methods are available to generate conditions with acceptable performance, a universal approach for reliably discovering effective conditions during reaction exploration is rare. Consequently, current reaction optimization processes are often labor-intensive, time-consuming, and costly, relying heavily on trial-and-error experimentation. Nowadays, large language models (LLMs) are capable of tackling chemistry-related problems, such as molecule design and chemical reasoning tasks. Here, we report the design, implementation and application of Chemma-RC, a text-augmented multimodal LLM to identify effective conditions through task-specific dialogue and condition generation. Chemma-RC learns a unified representation of chemical reactions by aligning multiple modalities-including text corpus, reaction SMILES, and reaction graphs-within a shared embedding module. Performance benchmarking on datasets showed high precision in identifying optimal conditions, with up to 17% improvement over the current state-of-the-art methods. A palladium-catalysed imidazole C-H arylation reaction was investigated experimentally to evaluate the functionalities of the Chemma-RC in practice. Our findings suggest that Chemma-RC holds significant potential to accelerate high-throughput condition screening in chemical synthesis.

David Wichner, Jeffrey Wishart, Jason Sergent et al.

Safety Management Systems (SMSs) have been used in many safety-critical industries and are now being developed and deployed in the automated driving system (ADS)-equipped vehicle (AV) sector. Industries with decades of SMS deployment have established frameworks tailored to their specific context. Several frameworks for an AV industry SMS have been proposed or are currently under development. These frameworks borrow heavily from the aviation industry although the AV and aviation industries differ in many significant ways. In this context, there is a need to review the approach to develop an SMS that is tailored to the AV industry, building on generalized lessons learned from other safety-sensitive industries. A harmonized AV-industry SMS framework would establish a single set of SMS practices to address management of broad safety risks in an integrated manner and advance the establishment of a more mature regulatory framework. This paper outlines a proposed SMS framework for the AV industry based on robust taxonomy development and validation criteria and provides rationale for such an approach. Keywords: Safety Management System (SMS), Automated Driving System (ADS), ADS-Equipped Vehicle, Autonomous Vehicles (AV)

James D. Serna, Alexander Yu. Sokolov

Theoretical simulations of electron detachment processes are vital for understanding chemical redox reactions, semiconductor and electrochemical properties, and high-energy radiation damage. However, accurate calculations of ionized electronic states are very challenging due to their open-shell nature, importance of electron correlation effects, and strong interactions with chemical environment. In this work, we present an efficient approach based on algebraic diagrammatic construction theory with polarizable embedding that allows to accurately simulate ionized electronic states in condensed-phase or biochemical environments (PE-IP-ADC). We showcase the capabilities of PE-IP-ADC by computing the vertical ionization energy (VIE) of thymine molecule solvated in bulk water. Our results show that the second- and third-order PE-IP-ADC methods combined with the basis of set of triple-zeta quality yield a solvent-induced shift in VIE of -0.92 and -0.93 eV, respectively, in an excellent agreement with experimental estimate of -0.9 eV. This work demonstrates the power of PE-IP-ADC approach for simulating charged electronic states in realistic chemical environments and motivates its further development.

Pavlo Golub, Chao Yang, Vojtěch Vlček et al.

Accurate electronic structure calculations are essential in modern materials science, but strongly correlated systems pose a significant challenge due to their computational cost. Traditional methods, such as complete active space self-consistent field (CASSCF), scale exponentially with system size, while alternative methods like the density matrix renormalization group (DMRG) scale more favorably, yet remain limited for large systems. In this work, we demonstrate how a simple machine learning model can enhance quantum chemical DMRG calculations, improving their accuracy to chemical precision, even for systems that would otherwise require considerably higher computational resources. The systems under study are polycyclic aromatic hydrocarbons, which are typical candidates for DMRG calculations and are highly relevant for advanced technological applications.

Tilman Richter, Paolo Malgaretti, Thomas M. Koller et al.

Catalyst particles or complexes suspended in liquid films can trigger chemical reactions leading to inhomogeneous concentrations of reactants and products in the film. We demonstrate that the sensitivity of the liquid film's gas-liquid surface tension to these inhomogeneous concentrations strongly impacts the film stability. Using linear stability analysis, we identify novel scenarios in which the film can be either stabilized or destabilized by the reactions. Furthermore, we find so far unrevealed rupture mechanisms which are absent in the chemically inactive case. The linear stability predictions are confirmed by numerical simulations, which also demonstrate that the shape of chemically active droplets can depart from the spherical cap and that unsteady states such as traveling and standing waves might appear. Finally, we critically discuss the relevance of our predictions by showing that the range of our selected parameters is well accessible by typical experiments.

Khadijeh Shirani Bidabadi, Shilla Safaeian, Rezvan Mousavi Nadushan et al.

IntroductionSargassum and Padina are two genera of brown algae that are widely scattered in temperate regions. Sargassum species are categorized as tropical and sub-tropical brown seaweed which are valuable sources of bioactive compounds including dietary fibers, carotenoids, vitamins, and minerals. These brown algae demonstrate diverse biological activities such as antioxidant, antimicrobial, and anti‑Alzheimer, due to the presence of flavonoids, triterpenoids, flavonoids, sterols, polyphenols, and pheophytine. The genus Padina is scattered in many environmental conditions, mainly in the tropical marine waters, and belongs to the family Dictyotaceae. Some bioactive components isolated from Padina species have been demonstrated hypoglycemic, hypolipidemic, anti-obesity, hepatoprotective, cardioprotective, immunostimulatory, and antimicrobial activities., The aim of this study was to prepare an extract from two species of algae Padina and Sargsum by massaging and ultrasound assisted-methods  as well as analyzing their compounds and investigating the antioxidant, antimicrobial and enzymatic properties of the extracts. According to the obtained results, ultrasound assisted method was a suitable method for extraction. This extract can be used as a combination of antioxidant, antimicrobial, anti-Alzheimer's and nitrate reducing agent in food additives. Materials and MethodsChemical materials were supplied by Sigma-Aldrich GmbH (Sternheim, Germany). The algal species utilized in the current investigation; namely, Padina distromatic and Sargassum angustifolium were collected from the coastal region of Chabahar bandar, Sistan and Baluchistan Province, Iran. To eliminate all the impurities and extraneous materials, they were washed by using distilled water and then dried at ambient temperature (24-48 h) until the constant weight. Extraction by maceration was compared with the extraction using ultrasonic assisted method. Determination of chemical compounds was parformed using GC-MS device. Investigation of antioxidant properties and total polyphenol and flavonoid content were also performed. The degree of free radical scavenging was done according to DPPH method. Evaluation of antimicrobial effect of algae extracts were the main challenges in our research. S. aureus ATCC25923, Listeria innocua ATCC 33090, E. coli ATCC 25922 and S. typhi ATCC 6539 were used for antimicrobial test. Determination of minimum growth inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) were performed using wells in agar.The enzymatic activity was also determined. In this study, the activity of acetylcholinesterase was investigated using the method introduced by Ellman et al. (1961) and also the activity of nitric oxidase was determined using a kit protocol (Nvand-Iran). Factorial experiment in the form of a completely randomized design was used to analyze the data. Duncan's multiple range test was used to determine the difference between the means at the 95% confidence level, and SAS software version 2.9 will used for statistical analysis. Results and DiscussionThe current study investigated the antioxidant, antibacterial, anti-inflammatory, and anti-Alzheimer’s attributes of two brown algae namely Padina distromatic and Sargassum angustifolium which were collected from the coastal region of Chabahar Bandar, Iran. The results clearly indicated that the type of algae and extraction techniques used in this investigation highly affected phytochemical compositions, antioxidant, AChE inhibitory, scavenging, and antimicrobial activities. Considering both extraction yield and phytochemical components, extraction by ultrasound assisted method provided better results. Among all algal extracts, UPE presented the highest AChE inhibitory activity, and antibacterial activity and USE presented the highest antioxidant activities, total phenols and flavonoids, reflecting the presence of various bioactive components. The extracts of two various seaweeds utilized in the current study highlighted considerable inhibitory action against four pathogenic bacteria. According to the observations of the antibacterial assay, S. aureus was the most sensitive microorganism, while L. innocua was revealed as the most resistant bacteria to the extracts of P. distromatic and S. angustifolium. Further, the chemical components responsible for the antioxidant, AChE inhibitory, and antibacterial power were confirmed by GC-MS analysis. The findings of the current investigation confirmed the potential of the health benefits and therapeutic effect of brown marine algae. Thus, the extract of P. distromatic and S. latifolium could be an effective supplement to be incorporated into the products’ formulation in the food and pharmaceutical industries as well as in medication to alleviate several disorders such as Alzheimer.

Kuei-Ping Liu, Jhu-Lin You, Shun-Yi Jian et al.

In this study, an improved technique is proposed to obtain bare metal surfaces for implants, stents, and medical devices. The aim is to enhance the corrosion resistance and biocompatibility of the WE43 magnesium alloy by modifying its surface characteristics through electropolishing. This is achieved using an electrolytic mixture with varying concentrations of HNO3 and C2H5NO3. The morphology, microstructure, chemical composition, and phase structures of the coating are analyzed by SEM, XPS, and XRD. The corrosion resistance of the surface was analyzed by polarization and bio-corrosion behavior tests. During the electropolishing process, unstable Mg(NO3)2 is easily formed by Mg and HNO3. However, the addition of C2H5OH helps release C2H5NO3 and HNO3 ions from the electrolyte, leading to the formation of a thin and dense layer of MgO on the alloy surface. The results revealed that surface roughness significantly affected the corrosion resistance of the alloy. Specifically, the oxide layer thickness gradually decreased with increasing voltage during electropolishing. However, it was observed that higher electropolishing voltages (beyond 0.5 V) caused surface cracking and reduced the corrosion resistance of the alloy. Therefore, it is necessary to investigate the optimal electrolytic polishing parameters to enhance the corrosion resistance of WE43 magnesium alloy. According to the experimental results, the optimal electrolytic polishing parameters for WE43 magnesium alloy were determined as follows: 2.0 wt% HNO3 and C2 H5OH, a voltage of 0.45 V, and a time of 300 s. These parameters also exhibited the best biocompatibility characteristics.

Hong-Zhou Ye, Timothy C. Berkelbach

First-principles calculations are a cornerstone of modern surface science and heterogeneous catalysis. However, accurate reaction energies and barrier heights are frequently inaccessible due to the approximations demanded by the large number of atoms. Here we combine developments in local correlation and periodic correlated wavefunction theory to solve the many-electron Schrödinger equation for molecules on surfaces with chemical accuracy, commonly defined as 1~kcal/mol. As a demonstration, we study water on the surface of \ce{Al2O3} and \ce{TiO2}, two prototypical and industrially important metal oxides for which we obtain converged energies at the level of coupled-cluster theory with single, double, and perturbative triple excitations [CCSD(T)], commonly known as the "gold-standard" in molecular quantum chemistry. We definitively resolve the energetics associated with water adsorption and dissociation, enabling us to address recent experiments and to analyze the errors of more commonly used approximate theories.

Liangrong Peng, Liu Hong

Partial equilibrium approximation (PEA) and quasi-steady-state approximation (QSSA) are two classical methods for reducing complex macroscopic chemical reactions into simple computable ones. Previous studies mainly focus on the accuracy of solutions before and after applying model reduction. While, in this paper we start from a thermodynamic view, and try to establish a quantitative connection on the essential thermodynamic quantities, like entropy production rate, free energy dissipation rate and entropy flow rate, between the original reversible chemical mass-action equations and the reduced models by either PEA or QSSA. Our results reveal that the PEA and QSSA do not necessarily preserve the nice thermodynamic structure of the original full model during the reduction procedure (e.g. the loss of non-negativity of free energy dissipation rate), especially when adopting the algebraic relations in replace of differential equations. These results are further validated though the application to Michaelis-Menten reactions analytically and numerically as a prototype. We expect our study would motivate a re-examination on the effectiveness of various model reduction or approximation methods from a new perspective of non-equilibrium thermodynamics.

William R. Cannon, Samuel Britton, Mikahl Banwarth-Kuhn et al.

We demonstrate and characterize a first-principles approach to modeling the mass action dynamics of metabolism. Starting from a basic definition of entropy expressed as a multinomial probability density using Boltzmann probabilities with standard chemical potentials, we derive and compare the free energy dissipation and the entropy production rates. We express the relation between the entropy production and the chemical master equation for modeling metabolism, which unifies chemical kinetics and chemical thermodynamics. Subsequent implementation of an maximum free energy dissipation model for systems of coupled reactions is accomplished by using an approximation to the Marcelin equation for mass action kinetics that maximizes the entropy production. Because prediction uncertainty with respect to parameter variability is frequently a concern with mass action models utilizing rate constants, we compare and contrast the maximum entropy production model, which has its own set of rate parameters, to a population of standard mass action models in which the rate constants are randomly chosen. We show that a maximum entropy production model is characterized by a high probability of free energy dissipation rate, and likewise entropy production rate, relative to other models. We then characterize the variability of the maximum entropy production predictions with respect to uncertainties in parameters (standard free energies of formation) and with respect to ionic strengths typically found in a cell.

Ekaterina V. Pereliaeva, Maria E. Dmitrieva, Maria M. Morgunova et al.

One of the relevant areas in microbiology and biotechnology is the study of microorganisms that induce the destruction of different materials, buildings, and machines and lead to negative effects. At the same time, the positive ecological effects of degradation can be explained by the detoxication of industrial and agricultural wastes, chemical substances, petroleum products, xenobiotics, pesticides, and other chemical pollutants. Many of these industrial wastes include hard-to-degrade components, such as lignocellulose or plastics. The biosynthesis of natural products based on the transformation of lignocellulosic wastes is of particular interest. One of the world’s unique ecosystems is presented by Lake Baikal. This ecosystem is characterized by the highest level of biodiversity, low temperatures, and a high purity of the water. Here, we studied the ability of several psychrophilic representatives of Baikal Actinobacteria to grow on sawdust wastes and transform them into bioactive natural products. Different strains of both widely spread genus of Actinobacteria and rare genera of Actinobacteria were tested. We used the LC-MS methods to show that Actinobacteria living in sawmill wastes can produce both known and novel natural products with antibiotic activity. We demonstrated that the type of sawmill wastes and their concentration influence the Actinobacteria biosynthetic potential. We have shown for the first time that the use of Baikal psychrophilic microorganisms as a factory for biodegradation is applicable for the transformation of lignocellulosic wastes. Thus, the development of techniques for screening novel natural products leads to an elaboration on the active ingredients for novel drugs.

Maria Dimopoulou, Elli Goulioti, Vicky Troianou et al.

Enhancing the sensory profile of wines by exposing the aromas of the grape variety through the involvement of microorganisms has always been a challenge in winemaking. The aim of our work was to evaluate the impact of different fermentation schemes by using mixed and pure cultures of different <i>Saccharomyces</i> species to Sauvignon blanc wine chemical composition and sensory profile. The Sauvignon blanc must has been inoculated with mixed and pure cultures of <i>S. pastorianus</i> and <i>S. cerevisiae</i> strains. For the mixed fermentation schemes, one strain of <i>S. pastorianus</i> has been inoculated with different proportions of <i>S. cerevisiae</i> (<i>S. pastorianus</i> to <i>S. cerevisiae</i>: 99%–1%, 95%–5%, 90%–10%, 80%–20% and 70%–30% <i>w</i>/<i>w</i>) in co-inoculation with two commercial strains of <i>S. cerevisiae</i>. A total of 13 fermentations trials, three monocultures and 10 mixed cultures were performed in biological triplicate. The fermentation kinetics have been controlled by density measurement and classical oenological analyses were performed based on the International Organisation of Vine and Wine (OIV) analytical methods. The population dynamics were evaluated by the specific interdelta PCR reaction of the <i>Saccharomyces</i> species at the beginning and at the end of the fermentation process. The volatile compounds of the wine aroma, such as the esters, higher alcohols and thiols were analyzed by GC/MS. Sensory assessment by trained panel was carried out for all produced wines. Complete depletion of the sugars was achieved between 10 and 13 days for all the fermentation trials. The population dynamics analysis revealed that the <i>S. cerevisiae</i> strain was the most predominant at the end of the fermentation process in all inoculation ratios that were tested. The wines that were fermented with <i>S. pastorianus</i>, either in pure or mixed cultures, were characterized by significantly lower acetic acid production and higher malic acid degradation when compared to the wines that were fermented only with <i>S. cerevisiae</i> strains. The aroma profile of the produced wines was highly affected by both inoculation ratio and the <i>S. cerevisiae</i> strain that was used. The presence of <i>S. pastorianus</i> strain enhanced the production of the varietal thiols when compared to the samples that were fermented with the <i>S. cerevisiae</i> pure cultures. The mixed inoculation cultures of <i>Saccharomyces</i> species could lead to wines with unique character which can nicely express the varietal character of the grape variety.

Xinjun Yu, Zengchao Jiang, Xiaodan Xu et al.

Chitin, the second richest polymer in nature, is composed of the monomer N-acetylglucosamine (GlcNAc), which has numerous functions and is widely applied in the medical, food, and chemical industries. However, due to the highly crystalline configuration and low accessibility in water of the chitin resources, such as shrimp and crab shells, the chitin is difficult utilize, and the traditional chemical method causes serious environment pollution and a waste of resources. In the present study, three genes encoding chitinolytic enzymes, including the N-acetylglucosaminidase from <i>Ostrinia furnacalis</i> (<i>OfHex1</i>), endo-chitinase from <i>Trichoderma viride</i> (<i>TvChi1</i>), and multifunctional chitinase from <i>Chitinolyticbacter meiyuanensis</i> (<i>CmChi1</i>), were expressed in the <i>Pichia pastoris</i> system, and the positive transformants with multiple copies were isolated by the PTVA (post-transformational vector amplification) method, respectively. The three recombinants OfHex1, TvChi1, and CmChi1 were induced by methanol and purified by the chitin affinity adsorption method. The purified recombinants OfHex1 and TvChi1 were characterized, and they were further used together for degrading chitin from shrimp and crab shells to produce GlcNAc through liquid-assisted grinding (LAG) under a water-less condition. The substrate chitin concentration reached up to 300 g/L, and the highest yield of the product GlcNAc reached up to 61.3 g/L using the mechano-enzymatic method. A yield rate of up to 102.2 g GlcNAc per 1 g enzyme was obtained.

R. Hinterding, M. Wolf, M. Jakob et al.

The oxide materials Ca3Co4O9 and Na2Ca2Nb4O13 were combined in a new ceramic composite with promising synergistic thermoelectric properties. Both compounds show a plate-like crystal shape and similar aspect ratios but the matrix material Ca3Co4O9 with lateral sizes of less than 500 nm is about two orders of magnitude smaller. Uniaxial pressing of the mixed compound powders was used to produce porous ceramics after conventional sintering. Reactions between both compounds and their compositions were thoroughly investigated. In comparison to pure Ca3Co4O9, mixing with low amounts of Na2Ca2Nb4O13 proved to be beneficial for the overall thermoelectric properties. A maximum figure-of-merit of zT = 0.32 at 1073 K and therefore an improvement of about 19% was achieved by the ceramic composites.

Shrabani Mondal, Jonah S. Greenberg, Jason R. Green

Physical kinetic roughening processes are well known to exhibit universal scaling of observables that fluctuate in space and time. Are there analogous dynamic scaling laws that are unique to the chemical reaction mechanisms available synthetically and occurring naturally? Here, we formulate two complementary approaches to the dynamic scaling of stochastic fluctuations in thermodynamic observables at and away from equilibrium. Both analytical expressions and numerical simulations confirm our dynamic scaling ans{ä}tze with their associated exponents, functions, and laws. A survey of common chemical mechanisms reveals classes that organize according to the molecularity of the reactions involved, the nature of the reaction vessel and external reservoirs, (non)equilibrium conditions, and the extent of autocatalysis in the reaction network. Coupled reactions capable of chemical feedback can transition, sometimes sharply, between these classes with the variation of experimental parameters such as temperature. While path observables like the dynamical activity have scaling exponents that are time-independent, fluctuations in the entropy production and flow can have time-dependent scaling exponents and self-averaging properties as a result of temporal correlations that emerge during thermodynamically irreversible processes. Altogether, these results establish dynamic universality in the nonequilibrium fluctuations of thermodynamic observables for well-mixed chemical reactions.

Naruo Ohga, Sosuke Ito

We construct an information-geometric structure for chemical thermodynamics, applicable to a wide range of chemical reaction systems including non-ideal and open systems. For this purpose, we explicitly construct dual affine coordinate systems, which completely designate an information-geometric structure, using the extent of reactions and the affinities of reactions as coordinates on a linearly-constrained space of amounts of substances. The resulting structure induces a metric and a divergence (a function of two distributions of amounts), both expressed with chemical potentials. These quantities have been partially known for ideal-dilute solutions, but their extensions for non-ideal solutions and the complete underlying structure are novel. The constructed geometry is a generalization of dual affine coordinates for stochastic thermodynamics. For example, the metric and the divergence are generalizations of the Fisher information and the Kullback-Leibler divergence. As an application, we identify the chemical-thermodynamic analog of the Hatano-Sasa excess entropy production using our divergence.

Diomi Mamma

Food is a precious commodity, and its production can be resource-intensive [...]

Mikołaj Sacha, Mikołaj Błaż, Piotr Byrski et al.

The central challenge in automated synthesis planning is to be able to generate and predict outcomes of a diverse set of chemical reactions. In particular, in many cases, the most likely synthesis pathway cannot be applied due to additional constraints, which requires proposing alternative chemical reactions. With this in mind, we present Molecule Edit Graph Attention Network (MEGAN), an end-to-end encoder-decoder neural model. MEGAN is inspired by models that express a chemical reaction as a sequence of graph edits, akin to the arrow pushing formalism. We extend this model to retrosynthesis prediction (predicting substrates given the product of a chemical reaction) and scale it up to large datasets. We argue that representing the reaction as a sequence of edits enables MEGAN to efficiently explore the space of plausible chemical reactions, maintaining the flexibility of modeling the reaction in an end-to-end fashion, and achieving state-of-the-art accuracy in standard benchmarks. Code and trained models are made available online at https://github.com/molecule-one/megan.