Advanced Theory and Simulations最新文献_第3页

Machine Learning Meets Molecular Dynamics: Accurate Prediction of Polymer Solubility Parameters 机器学习满足分子动力学：聚合物溶解度参数的准确预测

IF 3.3 4区工程技术

Advanced Theory and Simulations Pub Date : 2026-03-25 DOI: 10.1002/adts.202501865

Alan George, Marek Sierka

{"title":"Machine Learning Meets Molecular Dynamics: Accurate Prediction of Polymer Solubility Parameters","authors":"Alan George, Marek Sierka","doi":"10.1002/adts.202501865","DOIUrl":"https://doi.org/10.1002/adts.202501865","url":null,"abstract":"The Hildebrand solubility parameter is a cornerstone descriptor for predicting thermodynamic compatibility in polymer‐solvent systems, yet its determination for polymers remains experimentally challenging, and traditional group contribution estimates lack accuracy and transferability. Here, we present an integrated framework that combines atomistic molecular dynamics (MD) simulations with machine learning (ML) to predict solubility parameter values across diverse molecular and polymeric systems. Solubility parameter values derived from MD simulations provide training targets for ML models built on molecular, quantum‐chemical, and chain‐specific descriptors. By systematically applying feature‐selection strategies, Pearson correlation filtering, principal component analysis, and recursive feature elimination, we construct optimized descriptor subsets tailored to each learning algorithm. Benchmarking across regression methods reveals that Gaussian process regression with recursive feature elimination achieves the best performance, with R 2 = 0.94, MAE = 0.54, and RMSE = 0.96 MPa 1/2 on the test set, consistently outperforming both empirical group‐contribution methods and conventional regressors. Our results highlight the critical role of descriptor curation and nonlinear models in capturing the complexity of polymer thermodynamics. This hybrid MD‐ML strategy establishes a generalizable and computationally efficient pathway for predicting solubility parameters, enabling rapid screening of solubility and miscibility for both known and novel molecules and polymers.","PeriodicalId":7219,"journal":{"name":"Advanced Theory and Simulations","volume":"16 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147519266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

DNA Base Pair Mediated Vibrational Coupling: An Adenine‐Thymine Base Pair Study DNA碱基对介导的振动偶联：腺嘌呤-胸腺嘧啶碱基对研究

IF 3.3 4区工程技术

Advanced Theory and Simulations Pub Date : 2026-03-25 DOI: 10.1002/adts.202501802

Suranjana Chakrabarty, Basudha Deb, Shreya Raha, Sudipta Saha, Amit Kumar Paul, Anup Ghosh

{"title":"DNA Base Pair Mediated Vibrational Coupling: An Adenine‐Thymine Base Pair Study","authors":"Suranjana Chakrabarty, Basudha Deb, Shreya Raha, Sudipta Saha, Amit Kumar Paul, Anup Ghosh","doi":"10.1002/adts.202501802","DOIUrl":"https://doi.org/10.1002/adts.202501802","url":null,"abstract":"Hydrogen bonding and vibrational coupling in nucleobases are central to the structural stability and spectroscopic behavior of DNA. In this study, we combine density functional theory (DFT) calculations and molecular dynamics simulations to investigate the vibrational interactions between the carbonyl (C═O) mode of thymine and the C═C modes of adenine in isolated nucleobases as well as in Watson–Crick and Hoogsteen base pairs across solvents of varying polarity. DFT results reveal that while the C═O stretching frequency of thymine is highly solvent‐sensitive, the C═C remains largely invariant. Base pairing markedly enhances vibrational coupling between the C═O group of thymine and the C═C bond of adenine, particularly in Hoogsteen configurations, as increasing solvent polarity gradually narrows the frequency gap. Coupling constants, calculated based on the second‐order derivative of DFT‐based potential energy, are consistent with this observation. Mode‐resolved molecular dynamics analyses further demonstrate that Hoogsteen pairs exhibit stronger intramolecular and intermolecular couplings, with periodic energy exchange within 10 ps timescale. In contrast, isolated thymine exhibits weak C═C and C═O coupling because increasing solvent polarity widens the frequency gap. These findings reveal how hydrogen bonding, base‐pair geometry, and solvent environment govern vibrational energy flow in DNA, clarifying its spectroscopic signatures.","PeriodicalId":7219,"journal":{"name":"Advanced Theory and Simulations","volume":"26 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147519267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Photochemical Transformation of 1,3‐Cycloheptadiene to a Bicyclic Product: A Multireference State‐Averaged CASSCF Surface Hopping Dynamics Study 1,3 -环庚二烯光化学转化为双环产物：多参考状态平均CASSCF表面跳跃动力学研究

IF 3.3 4区工程技术

Advanced Theory and Simulations Pub Date : 2026-03-24 DOI: 10.1002/adts.202501821

Madhab Morang, Biman Medhi, Manabendra Sarma

{"title":"Photochemical Transformation of 1,3‐Cycloheptadiene to a Bicyclic Product: A Multireference State‐Averaged CASSCF Surface Hopping Dynamics Study","authors":"Madhab Morang, Biman Medhi, Manabendra Sarma","doi":"10.1002/adts.202501821","DOIUrl":"https://doi.org/10.1002/adts.202501821","url":null,"abstract":"Conical intersections (CIs) are key features of electronic states that govern ultrafast photochemical processes, and efficient nonradiative transitions can occur through them. In this study, the photochemical electrocyclic ring‐closure reaction of 1,3‐cycloheptadiene conformers with Cs and C 2 point groups that yields bicyclo[3.2.0]heptene is analysed. The reaction pathways are mapped by optimizing reactants, products, transition states, and conical intersections. A disrotatory transition state (TS) was identified, connecting the Cs‐reactant to the Cs‐product, while a conrotatory TS links the Cs‐product to the transient cis, trans‐cyclohepta‐1,3‐diene intermediate. Interpolation studies indicate that only the Cs‐product pathway is viable as the route from CI‐S 1 /S 0 to the C 2 ‐product has a high activation barrier, whereas the Cs‐product pathway proceeds without such an obstacle. Surface hopping simulations is employed from the S 1 state for both Cs and C 2 conformers. The simulations consistently yielded the Cs photoproduct, with quantum yields of 7% and 2% from Cs and C 2 ‐conformer, respectively, which can be attributed to differences in S 1 ‐S 0 hopping near the CI‐S 1 /S 0 region. Overall, these results emphasize the decisive role of conical intersections in dictating product formations in photochemical reactions, providing mechanistic insights relevant to the development of molecular electronics, photopharmacology, and solar energy conversion.","PeriodicalId":7219,"journal":{"name":"Advanced Theory and Simulations","volume":"15 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147518740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

DFT and TD‐DFT Study of Al‐Based Fluoro‐Perovskites AlMF 3 (M = Ca, Zn, Ge) for Photovoltaic Applications 光伏应用Al基氟钙钛矿AlMF 3 （M = Ca, Zn, Ge）的DFT和TD - DFT研究

IF 3.3 4区工程技术

Advanced Theory and Simulations Pub Date : 2026-03-23 DOI: 10.1002/adts.202501992

Pooja Sharma, Prabhat Ranjan, Tanmoy Chakraborty

{"title":"DFT and TD‐DFT Study of Al‐Based Fluoro‐Perovskites AlMF 3 (M = Ca, Zn, Ge) for Photovoltaic Applications","authors":"Pooja Sharma, Prabhat Ranjan, Tanmoy Chakraborty","doi":"10.1002/adts.202501992","DOIUrl":"https://doi.org/10.1002/adts.202501992","url":null,"abstract":"Perovskite materials have emerged as a focal point for scientific research, owing to their ability for plausible applications in optoelectronic and photovoltaic systems. We have explored Al‐based fluoro‐perovskite compounds AlMF 3 (M = Ca, Zn, Ge) studied through Density Functional theory (DFT) and Time‐Dependent (TD)‐DFT methodology. Functional CAM‐B3LYP/ LanL2MB and CAM‐B3LYP/LANL2DZ are employed for geometry optimization. This study examined the structural, optoelectronic, and thermochemical properties of these materials. The tolerance factors of AlCaF 3 , AlZnF 3, and AlGeF 3 are found as 0.85, 0.93, and 0.96. The negative formation energy of AlMF 3 compounds indicates thermodynamic stability. The HOMO–LUMO gap of AlCaF 3 , AlZnF 3 , and AlGeF 3 using LANL2MB is obtained as 2.82, 2.44, and 2.40 eV, respectively, whereas using LANL2DZ it is found in the range of 1.90–2.40 eV. AlGeF 3 and AlCaF 3 exhibit a minimum and maximum energy gap, respectively. CDFT‐based descriptors of AlMF 3 are analyzed and discussed. Among the examined fluoro‐perovskites, AlCaF 3 exhibits high stability. AlGeF 3 shows the maximum value of electronegativity, which indicates that it has high electron‐accepting capability. The refractive index and dielectric constant of these fluoro‐perovskite increase as the replacement of the M‐site cation, Ca to Zn to Ge, takes place. The thermochemical properties of these materials are also calculated. The estimated findings show a pattern consistent with earlier reports on perovskite materials.","PeriodicalId":7219,"journal":{"name":"Advanced Theory and Simulations","volume":"148 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147518741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Integrated Machine Learning Model and Induced‐Fit Docking for Identifying EGFR Inhibitors from Marine Natural Products 从海洋天然产物中识别EGFR抑制剂的集成机器学习模型和诱导拟合对接

IF 3.3 4区工程技术

Advanced Theory and Simulations Pub Date : 2026-03-19 DOI: 10.1002/adts.70371

Dwi Syah Fitra Ramadhan

{"title":"An Integrated Machine Learning Model and Induced‐Fit Docking for Identifying EGFR Inhibitors from Marine Natural Products","authors":"Dwi Syah Fitra Ramadhan","doi":"10.1002/adts.70371","DOIUrl":"https://doi.org/10.1002/adts.70371","url":null,"abstract":"This study aimed to develop machine learning models to predict epidermal growth factor receptor (EGFR) inhibitory activity and apply the best models to screen marine natural products, followed by induced‐fit molecular docking analysis. A total final dataset 13 700 classified as active (IC 50 ≤ 50 n m ) and inactive (IC 50 > 1000 n m ). Molecular fingerprints and RDKit descriptors were used as features, and the dataset was split into 80% training and 20% testing using stratified sampling, with normalization applied. Five algorithms i.e. Random Forest, Logistic Regression, Gradient Boosted Trees, kNN, and Naïve Bayes were evaluated, with Random Forest and kNN achieved highest AUC and statistical evaluation values. Subsequently, these two models were applied in a sequential consensus strategy to screen 31 561 marine compounds from CMNPD database. Compounds predicted as active by all two models were prioritized and subjected to induced‐fit docking in MOE 2014 against EGFR (PDB ID: 1M17). The docking protocol was validated by re‐docking the native ligand (RMSD < 2 Å), and the best hits were analyzed based on binding energy and interaction patterns. CMNPD28093, CMNPD28092, and CMNPD16800 demonstrated strong potential as a candidates compound of EGFR. This integrated approach successfully identified promising marine‐derived candidates for EGFR inhibitor discovery.","PeriodicalId":7219,"journal":{"name":"Advanced Theory and Simulations","volume":"30 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147492795","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Protein Spectral Fingerprinting Using a Tunable Black Phosphorus Metasurfaces Platform 使用可调黑磷超表面平台的蛋白质光谱指纹识别

IF 3.3 4区工程技术

Advanced Theory and Simulations Pub Date : 2026-03-19 DOI: 10.1002/adts.202502149

Narendra Kumar Yadav, Vivek Kumar Gupta, Govind Dayal, Vivek Singh

{"title":"Protein Spectral Fingerprinting Using a Tunable Black Phosphorus Metasurfaces Platform","authors":"Narendra Kumar Yadav, Vivek Kumar Gupta, Govind Dayal, Vivek Singh","doi":"10.1002/adts.202502149","DOIUrl":"https://doi.org/10.1002/adts.202502149","url":null,"abstract":"A black phosphorus nanoribbon‐based plasmonic metasurface is proposed for tunable and enhanced surface‐enhanced infrared absorption targeting protein vibrational modes. The metasurface consists of monolayer black phosphorus resonators placed on a dielectric spacer above a metallic ground plane, where the anisotropic optical properties of black phosphorus are exploited to engineer the plasmonic response. The plasmonic resonances are aligned with the characteristic protein vibrational bands, namely Amide‐I (∼6025 nm), Amide‐II (∼6562 nm), and Amide‐III (∼6905 nm) through systematic variation of the nanoribbon width and carrier density. The proposed structure exhibits highly enhanced and strongly localized electromagnetic fields at the nanoribbon edges, with electric‐field enhancement factors approaching ∼6000. Numerical simulations demonstrate strong surface‐enhanced infrared absorption enhancement for protein A/G and IgG, indicating significant enhancement of their vibrational signatures. Furthermore, the coupled harmonic oscillator analysis reveals a maximum light–matter coupling when the plasmonic and molecular vibrational modes are spectrally aligned. This reconfigurable, label‐free metasurface enables highly sensitive protein detection and provides a versatile platform for biochemical sensing and medical diagnostics.","PeriodicalId":7219,"journal":{"name":"Advanced Theory and Simulations","volume":"12 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147478413","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Machine Learning Prediction of Henry Coefficients of Polar and Nonpolar Gases in Covalent Organic Frameworks: Effects of Interlayer Shifts and Functionalization 共价有机骨架中极性和非极性气体亨利系数的机器学习预测：层间移位和功能化的影响

IF 3.3 4区工程技术

Advanced Theory and Simulations Pub Date : 2026-03-19 DOI: 10.1002/adts.202600003

Maryam Nurhuda, Tiong Wei Teh, Daniel M. Packwood, Niels Hansen

{"title":"Machine Learning Prediction of Henry Coefficients of Polar and Nonpolar Gases in Covalent Organic Frameworks: Effects of Interlayer Shifts and Functionalization","authors":"Maryam Nurhuda, Tiong Wei Teh, Daniel M. Packwood, Niels Hansen","doi":"10.1002/adts.202600003","DOIUrl":"https://doi.org/10.1002/adts.202600003","url":null,"abstract":"Covalent organic frameworks (COFs) are promising materials for gas separation and carbon capture, however, the vast chemical and structural space of possible COFs makes conventional molecular simulation‐based screening of adsorption properties such as Henry coefficients computationally infeasible. Here, we systematically investigate the performance of several physically motivated descriptors, the sine matrix, Ewald sum matrix, smooth overlap of atomic positions (SOAP), many‐body tensor representation (MBTR), and a custom Lennard Jones‐based descriptor for predicting Henry coefficients of small gas molecules (both polar and nonpolar) in COFs using machine learning. To account for realistic variability, we construct datasets including both chemically functionalized frameworks and interlayer displaced stacking configurations, and train relatively simple models (random forests, neural networks, and gaussian process regression) on these data. By comparing predictive performance across descriptor–model combinations, we demonstrate how various physical representations capture the key factors governing gas adsorption, including electrostatics, local atomic environments, and van der Waals interactions. Our results highlight the critical role of descriptor choice and provide physically interpretable guidance for designing efficient machine learning models, providing a foundation for scalable high throughput computational screening of COFs for gas separation applications.","PeriodicalId":7219,"journal":{"name":"Advanced Theory and Simulations","volume":"33 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147478414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

How Do Initial Spins Affect Density Functional Theory Convergence for Magnetic High Entropy Alloys? 初始自旋如何影响磁性高熵合金的密度泛函理论收敛？

IF 3.3 4区工程技术

Advanced Theory and Simulations Pub Date : 2026-03-19 DOI: 10.1002/adts.202502165

Zicong Marvin Wong, Teck Leong Tan, Shi Jun Ang

{"title":"How Do Initial Spins Affect Density Functional Theory Convergence for Magnetic High Entropy Alloys?","authors":"Zicong Marvin Wong, Teck Leong Tan, Shi Jun Ang","doi":"10.1002/adts.202502165","DOIUrl":"https://doi.org/10.1002/adts.202502165","url":null,"abstract":"Machine‐learned interatomic potentials (MLIPs) have proven to be effective in accelerating catalytic simulations, achieving density functional theory (DFT) accuracy at a small fraction of the computational cost. To streamline the acquisition of representative DFT data, autonomous active learning workflows have been integrated with unmanned DFT calculations. As a result, DFT settings are typically standardized across various geometries selected for computation. However, magnetic systems often require more human intervention to determine the correct final magnetizations—the ones that correspond to the lowest electronic energy—leading to MLIPs being predominantly developed for non‐magnetic systems. Despite this, magnetic high‐entropy alloys (HEAs) are recognized for their promising catalytic properties, including CO 2 reduction, NH 3 decomposition and transport, as well as their desirable physical attributes such as high‐temperature strength and corrosion resistance. Given their importance, it is crucial to optimize the modeling of these materials. This study proposes a methodology for selecting appropriate initial atomic spin states for DFT optimization and single‐point calculations of representative HEA bulk, slab, and nanoparticle structures. The goal is to resolve a critical bottleneck in the development of magnetic HEA MLIPs with the automated and reliable generation of consistent DFT training data. By establishing a robust protocol for magnetic systems, this work enables the creation of high‐quality potential energy surfaces necessary for training next generation interatomic potentials.","PeriodicalId":7219,"journal":{"name":"Advanced Theory and Simulations","volume":"10 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147478699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Internal Analysis and Parameter Optimization of Bilayer Organic Solar Cell 双层有机太阳能电池的内部分析与参数优化

IF 3.3 4区工程技术

Advanced Theory and Simulations Pub Date : 2026-03-19 DOI: 10.1002/adts.202501789

Paritosh Chamola, Poornima Mittal

{"title":"Internal Analysis and Parameter Optimization of Bilayer Organic Solar Cell","authors":"Paritosh Chamola, Poornima Mittal","doi":"10.1002/adts.202501789","DOIUrl":"https://doi.org/10.1002/adts.202501789","url":null,"abstract":"In this research paper, a bilayer heterojunction organic photovoltaic cell consisting Poly (3‐hexylthiophene) (P3HT) and Fullerene derivative [6,6]‐Phenyl C61 butyric acid methyl ester (PCBM) is modelled and analyzed. The device physics is investigated through internal vertical cut‐line analysis followed by a systematic variation of the donor and acceptor layer thickness to study the resulting variations in performance parameters independently. The variation in the donor layer thickness from 0.01 to 0.07 µm showed the current density to vary with maximum at 4.0 mA/cm 2 at 0.04 µm similarly for acceptor layer maximum was attained as 3.8 mA/cm 2 at 0.05 µm thickness. The obtained results reveal the notable significance of donor acceptor interface in performance of bilayer photovoltaic cell via displaying the arrangement of field and current at the interface. The results further confirm that photovoltaic performance of a bilayer solar cell is strongly dependent on the thickness of both the donor and acceptor layers. Most importantly the obtained results also verify that the concept of increasing thickness to enhance performance parameters is counterintuitive as larger thickness leads to significant recombination and thickness can only be increased as far as the transit time of carriers is maintained.","PeriodicalId":7219,"journal":{"name":"Advanced Theory and Simulations","volume":"6 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147478415","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Agent‐Based Discrete Element Modeling of Microbial‐Induced Carbonate Precipitation 微生物诱导碳酸盐沉淀的离散元模型

IF 3.3 4区工程技术

Advanced Theory and Simulations Pub Date : 2026-03-16 DOI: 10.1002/adts.202502233

Liming Zhao, Brooke Filanoski, Ruohong Chen, David Erickson, Jingjie Yeo

{"title":"Agent‐Based Discrete Element Modeling of Microbial‐Induced Carbonate Precipitation","authors":"Liming Zhao, Brooke Filanoski, Ruohong Chen, David Erickson, Jingjie Yeo","doi":"10.1002/adts.202502233","DOIUrl":"https://doi.org/10.1002/adts.202502233","url":null,"abstract":"Biomineralization is a promising approach for producing composite materials that contain living organisms, biopolymers, and minerals. Brittle biomineralized materials can be potentially toughened by more deformable microorganisms and biopolymers. Microbially‐induced carbonate precipitation (MICP) is a common type of biomineralization that occurs when urease‐producing bacteria hydrolyze urea to form calcium carbonate (). MICP is often used in porous materials to improve their mechanical properties. The morphology of the precipitation is strongly influenced by the bacteria and the morphology and porosity of the host medium. To explore their effects on MICP, we constructed an agent‐based discrete element model to investigate clustering and morphology in tandem with the growth of bacterial cells and the secretion of extracellular polymers. The model parameters are validated and optimized via our experimental measurements. We further addressed parametric uncertainties and quantitatively evaluated the relative importance of enzyme secretion, catalytic kinetics, and diffusion dynamics parameters by employing Monte Carlo simulations combined with data‐driven variogram analysis. Based on this model, we also examine the influence of bacterial concentration, bacterial distribution, urea concentration, and the geometry of porous media on the morphology. Unlike prior field‐scale or particle‐based methods that primarily focus on structures, our model will pave the way toward the study of the kinetics of urease‐producing bacteria and the mechanically relevant microstructural features of MICP‐treated composite materials.","PeriodicalId":7219,"journal":{"name":"Advanced Theory and Simulations","volume":"14 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147471160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0