Viewpoint: Atomic-Scale Design Protocols toward Energy, Electronic, Catalysis, and Sensing Applications

First-principles guidelines to select promising van der Waals materials for hybrid photovoltaic-triboelectric nanogenerators

Photovoltaic (PV) devices play a key role in solar-to-electricity energy conversion at small and large scales; unfortunately, their efficiency heavily depends on optimal weather and environmental conditions. The optimal scenario would be to extend the capabilities of PV devices so that they are also able to harvest energy from environmental sources other than light. An optimal solution is represented by hybrid photovoltaic-triboelectric (PV-TENG) devices which have both photovoltaic and triboelectric capabilities for electric power generation. Two-dimensional transition metal dichalcogenides (TMDs) are highly promising candidates for such PV-TENG devices, thanks to the easy tunability of their electrical, optical, mechanical, and chemical properties. In this respect, we here propose a quantum mechanical study to identify suitable TMD-based chemical compositions with optimal photovoltaic and triboelectric generation properties. Among the considered materials, we identify MoTe2/WS2, MoS2/WSe2, WS2/TiO2, WS2/IrO2, and MoS2/WTe2 as the most promising bilayer compositions; under operative conditions, the band gap varies in the range 0.51-1.61 eV, ensuring the photovoltaic activity, while the relative motion of the layers may produce an electromotive force between 1.21 and 3.21 V (triboelectric generation) with a TMD/TMD interface area equal to about 200 Å2. The results constitute theoretical guidelines on how to check if specific chemical compositions of TMD bilayers are optimal for a combined photovoltaic and triboelectric power generation. Thanks to its generality, the presented approach can be promptly extended to van der Waals heterostructures other than those here considered and implemented in automated workflows for the search of novel low-dimensional materials with target PV and TENG response.

Hydrogen adsorption on fcc metal surfaces towards the rational design of electrode materials

The successful large-scale implementation of hydrogen as an energy vector requires high performance electrodes and catalysts made of abundant materials. Rational materials design strategies are the most efficient means of reaching this goal. Here we present a study on the adsorption of H-atoms onto fcc transition metal surfaces and propose descriptors for the rational design of electrodes and catalysts by means of correlations between fundamental properties of the materials and among other properties, their experimentally measured performance as hydrogen evolution electrodes (HEE). A large set of quantum mechanical modelling data at the DFT level was produced, covering the adsorption of H-atoms onto the most stable surfaces (100), (110) and (111) of: Ag, Au, Co, Cu, Ir, Ni, Pd, Pt and Rh. For each material and surface, a coverage dependent set of minimum energy structures was produced and chemical potentials for adsorption of H-atoms were obtained. Averaging procedures are here proposed to approach modelling to the experiments. Several correlations between the computed data and experimentally measured quantities are done to validate our methodology: surface plane dependent adsorption energies, chemical potentials and experimentally determined surface energies and work functions. We search for descriptors of catalytic activity by testing correlations between the DFT data obtained from our averaging procedures and experimental data on HEE performance. Our methodology allows us to obtain linear correlations between the adsorption energy of H-atoms and the exchange current density (i0) in a HEE, avoiding the volcano-like plots. We show that the chemical potential has limitations as a descriptor of i0 because it reaches an early plateau in terms of i0. Simple quantities obtained from database data such as the first stage electronegativity (χ) as devised by Mulliken has a strong linear correlation i0. With a quantity we denominate modified second-stage electronegativity (χ2m) we can reproduce the typical volcano plot in a correlation with i0. A theoretical and conceptual framework is presented. It shows that both χ and χ2m, that depend on the first ionization potential, second ionization potential and electron affinity of the elements can be used as descriptors in rational design of electrodes or of catalysts for hydrogen systems.

Integrating Newton's equations of motion in the reciprocal space

We here present the normal dynamics technique, which recasts the Newton's equations of motion in terms of phonon normal modes by exploiting a proper sampling of the reciprocal space. After introducing the theoretical background, we discuss how the reciprocal space sampling enables us to (i) obtain a computational speedup by selecting which and how many wave vectors of the Brillouin zone will be considered and (ii) account for distortions realized across large atomic distances without the use of large simulation cells. We implemented the approach into an open-source code, which we used to present three case studies: in the first one, we elucidate the general strategy for the sampling of the reciprocal space; in the second one, we illustrate the potential of the approach by studying the stabilization effect of temperature in α-uranium; and in the last one, we investigate the characterization of Raman spectra at different temperatures in MoS2/MX2 transition metal dichalcogenide heterostructures. Finally, we discuss how the procedure is general and can be used to simulate periodic, semiperiodic, and finite systems such as crystals, slabs, nanoclusters, or molecules.

Modeling Polyzwitterion-Based Drug Delivery Platforms: A Perspective of the Current State-of-the-Art and Beyond

Drug delivery platforms are anticipated to have biocompatible and bioinert surfaces. PEGylation of drug carriers is the most approved method since it improves water solubility and colloid stability and decreases the drug vehicles' interactions with blood components. Although this approach extends their biocompatibility, biorecognition mechanisms prevent them from biodistribution and thus efficient drug transfer. Recent studies have shown (poly)zwitterions to be alternatives for PEG with superior biocompatibility. (Poly)zwitterions are super hydrophilic, mainly stimuli-responsive, easy to functionalize and they display an extremely low protein adsorption and long biodistribution time. These unique characteristics make them already promising candidates as drug delivery carriers. Furthermore, since they have highly dense charged groups with opposite signs, (poly)zwitterions are intensely hydrated under physiological conditions. This exceptional hydration potential makes them ideal for the design of therapeutic vehicles with antifouling capability, i.e., preventing undesired sorption of biologics from the human body in the drug delivery vehicle. Therefore, (poly)zwitterionic materials have been broadly applied in stimuli-responsive "intelligent" drug delivery systems as well as tumor-targeting carriers because of their excellent biocompatibility, low cytotoxicity, insignificant immunogenicity, high stability, and long circulation time. To tailor (poly)zwitterionic drug vehicles, an interpretation of the structural and stimuli-responsive behavior of this type of polymer is essential. To this end, a direct study of molecular-level interactions, orientations, configurations, and physicochemical properties of (poly)zwitterions is required, which can be achieved via molecular modeling, which has become an influential tool for discovering new materials and understanding diverse material phenomena. As the essential bridge between science and engineering, molecular simulations enable the fundamental understanding of the encapsulation and release behavior of intelligent drug-loaded (poly)zwitterion nanoparticles and can help us to systematically design their next generations. When combined with experiments, modeling can make quantitative predictions. This perspective article aims to illustrate key recent developments in (poly)zwitterion-based drug delivery systems. We summarize how to use predictive multiscale molecular modeling techniques to successfully boost the development of intelligent multifunctional (poly)zwitterions-based systems.

Quantifying transfer learning synergies in infinite-layer and perovskite nitrides, oxides, and fluorides

We combine density functional theory simulations and active learning (AL) of element-embedding neural networks (NNs) to explore the sample efficiency for the prediction of vacancy layer formation energies and lattice parameters inABX_ninfinite-layer (n= 2) versus perovskite (n= 3) nitrides, oxides, and fluorides in the spirit of transfer learning. Following a comprehensive data analysis from different thermodynamic, structural, and statistical perspectives, we show that NNs model these observables with high precision, using merely∼30%of the data for training and exclusively theA-,B-, andX-site element names as minimal input devoid of any physicala prioriinformation. Element embedding autonomously arranges the chemical elements with a characteristic recurrent topology, such that their relations are consistent with human knowledge. We compare two different embedding strategies and show that these techniques render additional input such as atomic properties negligible. Simultaneously, we demonstrate that AL is largely independent of the initial training set, and exemplify its superiority over randomly composed training sets. Despite their highly distinct chemistry, the present approach successfully identifies fundamental quantum-mechanical universalities between nitrides, oxides, and fluorides that enhance the combined prediction accuracy by up to 16% with respect to three specialized NNs at equivalent numerical effort. This quantification of synergistic effects provides an impression of the transfer learning improvements one may expect for similarly complex materials. Finally, by embedding the tensor product of theBandXsites and subsequent quantitative cluster analysis, we establish from an unbiased artificial-intelligence perspective that oxides and nitrides exhibit significant parallels, whereas fluorides constitute a rather distinct materials class.

Analysis of an all-solid state nanobattery using molecular dynamics simulations under an external electric field

Present Li-ion battery (LIB) technology requires strong improvements in performance, energy capacity, charging-time, and cost to expand their application to e-mobility and grid storage. Li-metal is one of the most promising materials to replace commercial anodes such as graphite because of its 10 times higher specific capacity. However, Li-metal has high reactivity with commercial liquid electrolytes; thus, new solid materials are proposed to replace liquid electrolytes when Li-metal anodes are used. We present a theoretical analysis of the charging process in a full nanobattery, containing a LiCoO2 cathode, a Li7P2S8I solid-state electrolyte (SSE), a Li-metal anode as well as Al and Cu collectors for the cathode and anode, respectively. In addition, we added a Li3P/Li2S film as a solid electrolyte interphase (SEI) layer between the Li-anode and SSE. Thus, we focus this study on the SEI and SSE. We simulated the charging of the nanobattery with an external voltage by applying an electric field. We estimated temperature profiles within the nanobattery and analyzed Li-ion transport through the SSE and SEI. We observed a slight temperature rise at the SEI due to reactions forming PS3- and P2S74- fragments at the interfaces; however, this temperature profile changes due to the charging current under the presence of the external electric field ε = 0.75 V Å-1. Without the external field, the calculated open-circuit voltage (OCV) was 3.86 V for the battery, which is within the range of values of commercial cobalt-based LIBs. This voltage implies a spontaneous fall of available Li-ions from the anode to the cathode (during discharge). The charge of this nanobattery requires overcoming the OCV plus an additional voltage that determines the charging current. Thus, we applied an external potential able to neutralize the OCV, plus an additional 1.6 V to induce the transport of Li+ from the cathode up to the anode. Several interesting details about Li+ transport paths through the SSE and SEI are discussed.

Visible-light driven photodegradation on Ag nanoparticle-embedded fullerene (C60) heterostructural microcubes

Three-dimensional Ag(I)-fullerene hybrid microcrystal is fabricated by AgNO₃ assisted liquid-liquid interfacial precipitation, containing the abundant sp²-π-electron system. With a mild chemical reduction, it produces the massive Ag nanocluster/fullerene junctions, on which fullerene doubles role as the excellent electron acceptor and photon scavenger, enabling the Plasmon-driven catalytic reaction. Ag nanocluster employed alone could not perform this photocatalytic reaction, neither of fullerene (C₆₀) crystal. It implicates that Ag-fullerene interface is a key to drive catalytic process. Relative to conventional TiO₂ nanostructures, fullerene expands light absorption to most solar wavelength and possesses a tightened bandgap which intrinsically expedites the charge transfer and charge separation from coinage metals. Demonstrated by photodegradation of organic molecules, this Ag(I)-fullerene (C₆₀) composite, consisted of a plethora of electron donor-acceptor dyads renders an additional member to photocatalyst family, potentially implemented for photo-electron conversion, water remedy and beyond.