We investigate the interplay between functional-driven and density-driven errors in different density functional approximations within theory (DFT) implications of these for simulations water with DFT-based data-driven potentials. Specifically, we quantify two widely used dispersion-corrected functionals derived generalized gradient approximation (GGA), namely BLYP-D3 revPBE-D3, modern meta-GGA functionals, strongly constrained appropriately normed (SCAN) B97M-rV. The effects on interaction...

We present a detailed assessment of deep neural network potentials developed within the Deep Potential Molecular Dynamics (DeePMD) framework and trained on MB-pol data-driven many-body potential energy function. Specific focus is directed at ability DeePMD-based to correctly reproduce accuracy across various water systems. Analyses bulk interfacial properties as well interactions characteristic elucidate inherent limitations in transferability predictive potentials. These can be traced back...

Density functional theory (DFT) has been applied to modeling molecular interactions in water for over three decades. The ubiquity of chemical and biological processes demands a unified understanding its physics, from the single molecule thermodynamic limit everything between. Recent advances development data-driven machine-learning potentials have accelerated simulation aqueous systems with DFT accuracy. However, anomalous properties condensed phase, where rigorous treatment both local...

We present a general framework for the development of data-driven many-body (MB) potential energy functions (MB-QM PEFs) that represent interactions between small molecules at an arbitrary quantum-mechanical (QM) level theory. As demonstration, family MB-QM PEFs water is rigorously derived from density functionals belonging to different rungs across Jacob's ladder approximations within functional theory (MB-DFT) and Møller–Plesset perturbation (MB-MP2). Through systematic analysis individual...

Delocalization error constrains the accuracy of density functional theory in describing molecular interactions ion-water systems. Using Na+ and Cl- water as model systems, we calculate effects delocalization SCAN for water-water hydrated ions, demonstrate that density-corrected (DC-SCAN) predicts n-body interaction energies with an approaching coupled cluster theory. The performance DC-SCAN is size-consistent, maintaining accurate description well beyond first solvation shell. Molecular...

We assess the performance of different dispersion models for several popular density functionals across a diverse set noncovalent systems, ranging from benzene dimer to molecular crystals. By analyzing interaction energies and their individual components, we demonstrate that there exists variability systems empirical models, which are calibrated reproducing specific systems. Thus, parameter fitting may undermine underlying physics, as rely on error compensation among components energy....

Møller–Plesset adiabatic connection (MPAC) theory provides a powerful framework for constructing approximations to wavefunction-based correlation energy, enabling modeling of non- covalent interactions (NCIs) with near-CCSD(T) accuracy. We show that approximate MPAC functionals consistently outperform MP2 and dispersion-corrected DFT (DFT+DISP) across diverse systems, including charged charge-transfer complexes. oper- ate holistically at the electronic level, require no heuristic dispersion...

We present a general framework for the development of data-driven many-body (MB) potential energy functions (MB-QM PEFs) that represent interactions between small molecules at an arbitrary quantum-mechanical (QM) level theory. As demonstration, family MB-QM PEFs water are rigorously derived from density functionals belonging to differ- ent rungs across Jacob’s ladder approximations within functional theory (MB-DFT) as well Møller-Plesset perturbation (MB-MP2). Through systematic analysis...

We present a detailed assessment of deep neural network potentials developed within the DeePMD framework and trained on MB-pol data-driven many-body potential energy function. Specific focus is directed at ability DeePMD-based to correctly reproduce accuracy across various water systems. Analyses bulk interfacial properties as well interactions characteristic elucidate inherent limitations in transferability predictive potentials. These can be traced back an incomplete implementation...

The delicate interplay between functional-driven and density-driven errors in density functional theory (DFT) has hindered traditional approximations (DFAs) from providing an accurate description of water for over 30 years. Recently, the deep-learned DeepMind 21 (DM21) been shown to overcome limitations DFAs as it is free delocalization error. To determine if DM21 can enable a molecular-level physical properties aqueous systems within Kohn-Sham DFT, we assess accuracy neutral, protonated,...

The delicate interplay between functional-driven and density-driven errors in density functional theory (DFT) has hindered traditional approximations (DFAs) from providing an accurate description of water for over 30 years. Recently, the deep-learned DeepMind 21 (DM21) been shown to overcome limitations DFAs as it is free delocalization error. To determine if DM21 can enable a molecular-level physical properties aqueous systems within Kohn-Sham DFT, we assess accuracy neutral, protonated,...

Developing a molecular-level understanding of the properties water is central to numerous scientific and technological applications. However, accurately modeling through computer simulations has been significant challenge due complex nature hydrogen- bonding network that molecules form under different thermodynamic conditions. This complexity led over five decades research many attempts. The introduction MB-pol data-driven many-body potential energy function marked advancement toward...

We assess the performance of different dispersion models for several popular density functionals across a diverse set non-covalent systems, ranging from benzene dimer to molecular crystals. By analyzing interaction energies and their individual components, we demonstrate that there exists variability systems empirical models, which are calibrated reproducing specific systems. Thus, parameter fitting may undermine underlying physics, as rely on error compensation among components energy....

Delocalization error constrains the accuracy of density functional theory (DFT) in describing molecular interactions ion–water systems. Using Na+ and Cl− water as model systems, we calculate effects delocalization SCAN for water–water hydrated ions, demonstrate that density-corrected (DC-SCAN) predicts n-body interaction energies with an approaching coupled cluster theory. The performance DC-SCAN is size-consistent, maintaining accurate description in- teractions well beyond first solvation...

Delocalization error constrains the accuracy of density functional theory (DFT) in describing molecular interactions ion–water systems. Using Na+ and Cl− water as model systems, we calculate effects delocalization SCAN for water–water hydrated ions, demonstrate that density-corrected (DC-SCAN) predicts n-body interaction energies with an approaching coupled cluster theory. The performance DC-SCAN is size-consistent, maintaining accurate description in- teractions well beyond first solvation...

Delocalization error constrains the accuracy of density functional theory (DFT) in describing molecular interactions ion–water systems. Using Na+ and Cl− water as model systems, we calculate effects delocalization SCAN for water–water hydrated ions, demonstrate that density-corrected (DC-SCAN) predicts n-body interaction energies with an approaching coupled cluster theory. The performance DC-SCAN is size-consistent, maintaining accurate description in- teractions well beyond first solvation...

Developing a molecular-level understanding of the properties water is central to numerous scientific and technological applications. However, accurately modeling through computer simulations has been significant challenge due complex nature hydrogen- bonding network that molecules form under different thermodynamic conditions. This complexity led over five decades research many attempts. The introduction MB-pol data-driven many-body potential energy function marked advancement toward...

We investigate the interplay between functional-driven and density-driven errors in different density functional theory (DFT) approximations, implications of these for simulations water with DFT-based data-driven many-body potentials. Specifically, we quantify two widely used dispersion-corrected functionals derived within generalized gradient approximation (GGA), namely BLYP-D3 revPBE-D3, modern meta-GGA functionals, SCAN B97M-rV. The effects on interaction energies are assessed clusters...

In the ongoing pursuit of inorganic compounds suitable for solid-state devices, transition metal chalcogenides have received heightened attention due to their physical and chemical properties. Recently, alkali-ion been explored as promising candidates be applied in optoelectronics, photovoltaics energy storage devices. this work, we present a theoretical study sodium molybdenum selenide (Na2MoSe4). First-principles computations were performed on set hypothetical crystal structures determine...

<div> <p> </p><div> <p>We present a general framework for the development of data-driven many-body (MB) potential energy functions (MB-QM PEFs) that represent interactions between small molecules at an arbitrary quantum-mechanical (QM) level theory. As demonstration, family MB-QM PEFs water are rigorously derived from density functionals belonging to differ- ent rungs across Jacob’s ladder approximations within functional theory (MB-DFT) as well Møller-Plesset...

Density functional theory (DFT) has been applied to modeling molecular interactions in water for over three decades. The ubiquity of chemical and biological processes demands a unified understanding its physics, from the single-molecule thermodynamic limit everything between. Recent advances development data-driven machine-learning potentials have accelerated simulation aqueous systems with DFT accuracy. However, anomalous properties condensed phase, where rigorous treatment both local...

In the ongoing pursuit of inorganic compounds suitable for solid-state devices, transition metal chalcogenides have received heightened attention due to their physical and chemical properties. Recently, alkali-ion been explored as promising candidates be applied in optoelectronics, photovoltaics energy storage devices. this work, we present a comprehensive theoretical study sodium molybdenum selenide (Na 2 MoSe 4 ). First-principles computations were performed on set hypothetical crystal...

In the ongoing pursuit of inorganic compounds suitable for solid-state devices, transition metal chalcogenides have received heightened attention due to their physical and chemical properties. Recently, alkali-ion been explored as promising candidates be applied in optoelectronics, photovoltaics energy storage devices. this work, we present a comprehensive theoretical study sodium molybdenum selenide (Na 2 MoSe 4 ). First-principles computations were performed on set hypothetical crystal...

In the ongoing pursuit of inorganic compounds suitable for solid-state devices, transition metal chalcogenides have received heightened attention due to their physical and chemical properties. Recently, alkali-ion been explored as promising candidates be applied in optoelectronics, photovoltaics energy storage devices. this work, we present a comprehensive theoretical study sodium molybdenum selenide (Na<sub>2</sub>MoSe<sub>4</sub>). First-principles computations were...