A DFT study on the role of alkoxysilanes in the polymerization of isoprene over Ziegler-Natta catalyst DOI
Ang Zhao, Jian Liu,

RunChuan Zhou

et al.

Computational and Theoretical Chemistry, Journal Year: 2024, Volume and Issue: 1237, P. 114661 - 114661

Published: May 21, 2024

Language: Английский

Catalysis in the digital age: Unlocking the power of data with machine learning DOI Creative Commons
B. Moses Abraham, M. V. Jyothirmai, Priyanka Sinha

et al.

Wiley Interdisciplinary Reviews Computational Molecular Science, Journal Year: 2024, Volume and Issue: 14(5)

Published: Sept. 1, 2024

Abstract The design and discovery of new improved catalysts are driving forces for accelerating scientific technological innovations in the fields energy conversion, environmental remediation, chemical industry. Recently, use machine learning (ML) combination with experimental and/or theoretical data has emerged as a powerful tool identifying optimal various applications. This review focuses on how ML algorithms can be used computational catalysis materials science to gain deeper understanding relationships between properties their stability, activity, selectivity. development repositories, mining techniques, tools that navigate structural optimization problems highlighted, leading highly efficient sustainable future. Several data‐driven models commonly research diverse applications reaction prediction discussed. key challenges limitations using presented, which arise from catalyst's intrinsic complex nature. Finally, we conclude by summarizing potential future directions area ML‐guided catalyst development. article is categorized under: Structure Mechanism > Reaction Mechanisms Catalysis Data Science Artificial Intelligence/Machine Learning Electronic Theory Density Functional

Language: Английский

Citations

13
Ring Opening Polymerization of Six- and Eight-Membered Racemic Cyclic Esters for Biodegradable Materials DOI Open Access
Andrea Grillo, Yolanda Rusconi, Massimo Christian D’Alterio

et al.

International Journal of Molecular Sciences, Journal Year: 2024, Volume and Issue: 25(3), P. 1647 - 1647

Published: Jan. 29, 2024

The low percentage of recyclability the polymeric materials obtained by olefin transition metal (TM) polymerization catalysis has increased interest in their substitution with more eco-friendly reliable physical and mechanical properties. Among variety known biodegradable polymers, linear aliphatic polyesters produced ring-opening (ROP) cyclic esters occupy a prominent position. polymer properties are highly dependent on macromolecule microstructure, control stereoselectivity is necessary for providing precise finely tuned In this review, we aim to outline main synthetic routes, also applications three commercially available materials: Polylactic acid (PLA), Poly(Lactic-co-Glycolic Acid) (PLGA), Poly(3-hydroxybutyrate) (P3HB), all easily accessible via ROP. framework, understanding origin enantioselectivity factors that determine it then crucial development suitable thermal

Language: Английский

Citations

12
Ligand-Based Principal Component Analysis Followed by Ridge Regression: Application to an Asymmetric Negishi Reaction DOI
H. Ray Kelly, Sanil Sreekumar, Vidhyadhar Manee

et al.

ACS Catalysis, Journal Year: 2024, Volume and Issue: 14(7), P. 5027 - 5038

Published: March 20, 2024

In this study, we introduce an approach for predicting the enantioselectivity of P-chiral monophosphorus ligands from ligand-based descriptors that can be applied to catalytic systems with small experimental datasets without reliance on mechanistic knowledge. Principal component analysis (PCA) is used map out chemical space described by steric and electronic computed dihydrobenzooxaphosphole (BOP) dihydrobenzoazaphosphole (BAP) ligands. The PCA captures trends in experimentally measured four C–C bond-forming reactions identifies "hotspots" selective provide insight into optimal balance sterics electronics each reaction. Furthermore, are train a ridge regression model quantitatively predicts Pd-catalyzed Negishi cross-coupling coefficients fundamental understanding reveal π-stacking interaction one results unexpected selectivity inversion. Overall, integrated combines qualitative quantitative (ridge regression) predictions.

Language: Английский

Citations

7
Revisiting Stereoselective Propene Polymerization Mechanisms: Insights through the Activation Strain Model DOI
Eugenio Romano, Vincenzo Barone, Peter H. M. Budzelaar

et al.

Chemistry - An Asian Journal, Journal Year: 2024, Volume and Issue: 19(9)

Published: March 18, 2024

The stereoelectronic factors responsible for stereoselectivity in propene polymerization with several metallocene and post-metallocene transition metal catalysts have been revisited using a combined approach of DFT calculations, the Activation Strain Model, Natural Energy Decomposition Analysis molecular descriptor (%V

Language: Английский

Citations

4
Tuning the steric hindrance of alkylamines: a predictive model of steric editing of planar amines DOI Creative Commons
Michele Tomasini, Maria Voccia, Lucia Caporaso

et al.

Chemical Science, Journal Year: 2024, Volume and Issue: 15(33), P. 13405 - 13414

Published: Jan. 1, 2024

Amines are one of the most prevalent functional groups in chemistry.

Language: Английский

Citations

4
Ligand coordination controlled by monomer binding: a hint from DFT for stereoselective lactide polymerization DOI Creative Commons
Massimo Christian D’Alterio, Serena Moccia, Yolanda Rusconi

et al.

Catalysis Science & Technology, Journal Year: 2024, Volume and Issue: 14(19), P. 5624 - 5633

Published: Jan. 1, 2024

Switching the preference in stereocontrolled rac -LA ROP.

Language: Английский

Citations

4
Divalent Organo‐Bimetallic Chelates of Poly‐Dentate O,N,O‐dihydrazone Ligand as Effective Agents for Antitumor and Antimicrobial Assays, Interacting Modes With DNA DOI Open Access

M. Adam,

Mostafa Y. Nassar, M. J. A. Abualreish

et al.

Applied Organometallic Chemistry, Journal Year: 2024, Volume and Issue: 39(1)

Published: Dec. 26, 2024

ABSTRACT Substituted hydrazones and dihydrazones, as polydenatate ligand, reported high coordination chemical behavior towards numerous transition metals of different oxidation states for alternated applicable interest. Therefore, with a facile condensed reaction the salicylaldehyde tartric dihydrazide, chelated tartrato‐dihydrazone ligand (H 2 Ltz) was formed. The coordinated features H Ltz versus two divalent metal ions Cu (II) Ni were assumed to form new bimetallic‐organic framework complexes, assigning triagonal bipyramidal tetrahedral geometries (CuLtz NiLtz, respectively). Their structural elucidating determined within analytical tools spectroscopically. effectiveness growth inhibition Ltz, CuLtz, NiLtz against six named bacterial fungal series, three human cancer cell lines examined discovering reactive role central M in CuLtz respectively. binding character calf thymus DNA, that is, estimated based on variation viscometric/spectrophotometric features. bimetallic‐chelates represented more distinguished inhibitive attitudes than regarded one zones (mm) half‐inhibited concentration ( IC 50 , μM) studied microbes tumor cells, examination action DNA approved according enhanced viscosity electronic spectral changes. Also, constants (14.09, 15.09, 16.12 10 7 mol −1 dm 3 ), Gibb's free energy (−42.06, −45.23, −46.41 kJ chromism (mainly hypo modes) are assigned estimate modes. Rewardingly, MLtz displayed modified regarding their hydrophobicity/lipophilicity.

Language: Английский

Citations

4
Recent advances of machine learning applications in the development of experimental homogeneous catalysis DOI Creative Commons

Nil Sanosa,

David Dalmau, Diego Sampedro

et al.

Artificial Intelligence Chemistry, Journal Year: 2024, Volume and Issue: 2(1), P. 100068 - 100068

Published: April 27, 2024

Language: Английский

Citations

3
Prediction of electronic density of states in guanine-TiO2 adsorption model based on machine learning DOI Creative Commons
Yarkın A. Çetin, Benjamí Martorell, Francesc Serratosa

et al.

Deleted Journal, Journal Year: 2024, Volume and Issue: 1, P. 100008 - 100008

Published: June 2, 2024

The electronic density of states is a property the material that extensively used in quantum systems condensed matter physics. It refers to energy level electrons solid crystal. One most current ways compute it by Density Functional Tight Binding (DFTB), given geometry material. Nevertheless, this computation could be very computationally demanding, although applied some materials with reduced number atoms. This paper presents method deduce states, which based on neural network, thus, almost linear respect atoms Specifically, we have our metal oxide structure interacting nucleic base guanine. We focused stoichiometric and O-defective anatase TiO2 (101) surfaces. data set needed train network has been obtained DFTB+ numerical solver an initial molecular model, computed track time-dependent their associated states. validated predicted deduced DFTB tends similar, opening door other computations such introducing process generating analysis.

Language: Английский

Citations

3
Pd nanoparticles supported on modified magnetic kaolin as a novel hydrogenation catalyst DOI Creative Commons
Merat Karimi, Samahe Sadjadi, Hassan Arabi

et al.

Surfaces and Interfaces, Journal Year: 2025, Volume and Issue: unknown, P. 106037 - 106037

Published: Feb. 1, 2025

Language: Английский

Citations

0