Scientific Computing & Modelling (Netherlands)

Abstract Carbonate reservoirs, which contain a significant portion of the world's oil reserves, present unique challenges due to their complex pore structures and oil-wet characteristics, which hinder efficient oil extraction. The utilization of nanoparticles in improved and enhanced oil recovery (IOR/EOR) has emerged as a promising approach to address these challenges. Additionally, the modeling of nanoparticle behavior in carbonate rocks remains an area with significant gaps in understanding. This paper aims to develop and validate an advanced fluid modeling framework that integrates nanoparticle transport and interaction mechanisms in carbonate rock reservoirs under reservoir conditions. The primary objective is to identify and quantify critical parameters such as adsorption, wettability alteration, and transport dynamics—that influence the efficiency of nanoparticle-assisted oil recovery. The study involves complex mechanisms to understand these parameters and unlock the potential of nanoparticles in improving oil recovery. In this study, a comprehensive experimental and numerical modeling approach was employed to evaluate the performance of nanoparticles in coreflooding experiments. Laboratory tests involved fluid and rock characterization, adsorption rate, the injection of nanoparticle-enhanced fluids into carbonate core samples, with measurements taken for differential pressure, flow rates, effluent composition, adsorption. The experimental setup involved injecting the fluids into carbonate core samples under reservoir conditions, while monitoring pressure, flow rates, and effluent volume. The developed model incorporates key physical and physic-chemical processes, including wettability and adsorption measurements. The experimental coreflooding tests, which included rocks-fluid characterization and nanofluid injection, were successfully validated through a robust modeling framework. The results demonstrate that adsorption plays a crucial role in the efficiency of the oil displacement process. Adsorption of nanofluids onto the rock surface was investigated to significantly alter the wettability of the carbonate matrix, enhancing oil displacement and recovery. The integration of experimental insights with predictive modeling enables a deeper understanding of nanoparticle transport and interaction within complex carbonate matrices. The findings provide valuable insights into the design of next-generation IOR technologies, presenting a predictive model for a cost-effective and environmentally friendly solution to maximize hydrocarbon recovery and ultimately contributing to the sustainable development of carbonate oil fields.

Climate Change and Materials Criticality challenges are driving urgent responses from global governments. These global responses drive policy to achieve sustainable, resilient, clean solutions with Advanced Materials (AdMats) for industrial supply chains and economicprosperity. The research landscape comprising industry, academe, and government identified a critical path to accelerate the Green Transition far beyond slow conventional research through Digital Technologies that harness Artificial Intelligence, Smart Automation and High Performance Computing through Materials Acceleration Platforms, MAPs. In this perspective, following the short paper, a broad overview about the challenges addressed, existing projects and building blocks of MAPs will be provided while concluding with a review of the remaining gaps and measures to overcome them.

Abstract We have investigated the stereoselectivity and reactivity of the sodium borohydride reduction of 2‐X‐cyclohexanones (X=H, Cl, Br) using a combined approach of competitive experiments and density functional theory calculations. Our results show that the hydride addition proceeds via a late transition state in which the C–H bond is nearly formed, consistent with the mild reducing power of NaBH4. The reaction barrier decreases from the 2‐halocyclohexanones to the unsubstituted cyclohexanone, in line with relative reactivities observed in the competitive experiments. Furthermore, we provide a protocol to solve the longstanding issue of properly modelling the axial–equatorial facial selectivity of hydride addition to the carbonyl group substituted with a vicinal polar group. The inclusion of implicit solvation in combination with an explicit solvent molecule is crucial to reproduce the stereoselective formation of the cis product observed experimentally.

Societal Challenges demand for Advanced Materials, which in turn promise economical potential. Material Acceleration Platforms (MAPs) will decrease their development time and cost. We comment on implications for science, industry and policy concluding with necessary steps towards establishment of MAPs.

Code review is a critical step in the software development life cycle, which assesses and boosts the code's effectiveness and correctness, pinpoints security issues, and raises its quality by adhering to best practices. Due to the increased need for personal data protection motivated by legislation, code reviewers need to understand where personal data is located in software systems and how it is handled. Although most recent work on code review focuses on security vulnerabilities, privacy-related techniques are not easy for code reviewers to implement, making their inclusion in the code review process challenging. In this paper, we present ongoing work on a new approach to identifying personal data processing, enabling developers and code reviewers in drafting privacy analyses and complying with regulations such as the General Data Protection Regulation (GDPR).

Thioamides and selenoamides are better hydrogen-bond donors than carboxamides because their amino groups are more positively charged. Quantum chemical analyses reveal that this counterintuitive phenomenon, which cannot be explained by the electronegativity, originates from the larger electronic density flow from the nitrogen lone pair of the NH2 group towards the lower-lying π* orbital on the C=S or C=Se bond. This difference can be traced back to the effective steric size of the chalcogen atoms. More information can be found in the Research Article by C. Nieuwland and C. Fonseca Guerra (DOI: 10.1002/chem.202200755).

The amino groups of thio‐ and selenoamides can act as stronger hydrogen‐bond donors than of carboxamides, despite the lower electronegativity of S and Se. This phenomenon has been experimentally explored, particularly in organocatalysis, but a sound electronic explanation is lacking. Our quantum chemical investigations show that the NH2 groups in thio‐ and selenoamides are more positively charged than in carboxamides. This originates from the larger electronic density flow from the nitrogen lone pair of the NH2 group towards the lower‐lying π*C=S and π*C=Se orbitals than to the high‐lying π*C=O orbital. The relative energies of the π* orbitals result from the overlap between the chalcogen np and carbon 2p atomic orbitals, which is set by the carbon‐chalcogen equilibrium distance, a consequence of the Pauli repulsion between the two bonded atoms. Thus, neither the electronegativity nor the often‐suggested polarizability but the steric size of the chalcogen atom determines the amide's hydrogen‐bond donor capability.

We have quantum chemically studied the iron‐mediated C—X bond activation (X = H, Cl, CH3) by d8‐FeL4 complexes using relativistic density functional theory at ZORA‐OPBE/TZ2P. We find that by either modulating the electronic effects of a generic iron‐catalyst by a set of ligands, that is, CO, BF, PH3, BN(CH3)2, or by manipulating structural effects through the introduction of bidentate ligands, that is, PH2(CH2)nPH2 with n = 6–1, one can significantly decrease the reaction barrier for the C—X bond activation. The combination of both tuning handles causes a decrease of the C—H activation barrier from 10.4 to 4.6 kcal mol−1. Our activation strain and Kohn‐Sham molecular orbital analyses reveal that the electronic tuning works via optimizing the catalyst–substrate interaction by introducing a strong second backdonation interaction (i.e., “ligand‐assisted” interaction), while the mechanism for structural tuning is mainly caused by the reduction of the required activation strain because of the pre‐distortion of the catalyst. In all, we present design principles for iron‐based catalysts that mimic the favorable behavior of their well‐known palladium analogs in the bond‐activation step of cross‐coupling reactions.

Invited for this month's cover are the groups of Célia Fonseca Guerra at the Vrije Universiteit Amsterdam and Leiden University, Giampaolo Barone from the Università degli Studi di Palermo, and F. Matthias Bickelhaupt at Vrije Universiteit Amsterdam and Radboud University Nijmegen. The cover picture shows the four primary interaction components (hydrogen bonding, cross-terms, base stacking, and solvation) that determine the stability of B-DNA duplexes. Quantum chemical analyses identify an interplay between the stabilizing hydrogen bonds between nucleotides that drive the formation of the DNA double-strand, and the destabilizing loss of stacking interactions within individual strands combined with partial desolvation. The sequence-dependence in the duplex stability originates mainly from the cross-terms, which can be attractive or repulsive. Read the full text of their Research Article at 10.1002/open.202100231.

This study presents configuration integral Monte Carlo integration (CIMCI), a new semiclassical method for handling fully coupled anharmonicity in gas-phase thermodynamics that promises to be black boxable, to be applicable to all kinds of anharmonicity, and to scale better at higher dimensionality than other methods for handling gas-phase molecular anharmonicity. The method does so using automatically and recursively stratified, simultaneous Monte Carlo (MC) integration of multiple functions, following a modified version of the standard MISER scheme that converges at a rate of about the square of naïve MC integration. For the small systems analyzed by this study where proper reference data is available (H2O and H2O2), the method's anharmonic entropy corrections match reference data better than those of other black box anharmonic methods, e.g., vibrational perturbation theory (VPT2) and the McClurg hindered rotor model used with automatic detection of rotors; for H2O2 and NH2OH, the method is also in general agreement with one-dimensional hindered rotor treatments at low temperatures. This holds even when sampling with CIMCI is done with primitive force fields, e.g., UFF, while the competing methods are used with proper, comprehensive potentials, e.g., the M06-2X metahybrid density-functional theory (DFT) functional.