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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Novel Solar Cell Materials: Insights from First-Principles

Although silicon solar cells currently dominate the market share for photovoltaic (PV) devices, it is important to explore other materials and device configurations that could be cheaper and more environmentally friendly to produce, as well as potentially more efficient at energy conversion. Here, we review some of our recent theoretical work aimed at accurate evaluation of key materials properties associated with optimizing alternative PV materials. These include potential new light absorbers and transparent conductors in devices ranging from traditional PVs to tandem dye-sensitized solar cells and thin-film PVs to intermediate band gap PVs. We specifically focus on two materials families: transition-metal oxides (TMOs), such as NiO, CoO, FeO, and Cu 2 O, and mixed metal sulfides, such as Cu 2 ZnSnS 4 . Furthermore, both families are p-type semiconductors being explored as less expensive solar cell components.

14 SOLAR ENERGY↗
DOE OSTI2019

Machine Learning Classical Interatomic Potentials for Molecular Dynamics from First-Principles Training Data

The ever-increasing power of modern super-computers, along with the availability of highly scalable atomistic simulation codes, has begun to revolutionize predictive modeling of materials. In particular, molecular dynamics (MD) has led to breakthrough advances in diverse fields, including tribology, catalysis, sensing, and nanoparticle self-assembly. Furthermore, recent integration of MD simulations with X-ray characterization has demonstrated promise in real-time 3-D characterization of materials on the atomic scale. The popularity of MD is driven by its applicability at disparate length/time scales, ranging from ab initio MD (hundreds of atoms and tens of picoseconds) to all-atom classical MD (millions of atoms over microseconds), and coarse-grained (CG) models (micrometers and tens of microseconds). Nevertheless, a substantial gap persists between AIMD, which is highly accurate but restricted to extremely small sizes, and those based on classical force fields (atomistic and CG) with limited accuracy but access to larger length/time scales. The accuracy and predictive power of classical MD simulations is dictated by the empirical force fields, and their capability to capture the relevant physics. Here, we discuss some of our recent work on the use of machine learning (ML) to combine the accuracy and flexibility of electronic structure calculations with the speed of classical potentials. Our ML framework attempts to bridge the significant gulf that exists between the handful of research groups that develop new interatomic potential models (often requiring several years of effort), and the increasingly large user community from academia and industry that applies these models. Our data-driven approach represents significant departure from the status quo and involves several steps including generation and manipulation of extensive training data sets through electronic structure calculations, defining novel potential functional forms, employing state-of-the-art ML algorithms to formulate highly optimized training procedures, and subsequently developing user-friendly workflow tools integrating these algorithms on high-performance computers (HPCs). Our ML approach shows marked success in developing force fields for a wide range of materials from metals, oxides, nitrides, and heterointerfaces to two-dimensional (2D) materials.

Chan, Henry↗
DOE OSTI2024

Leveraging Triphenylphosphine-Containing Polymers to Explore Design Principles for Protein-Mimetic Catalysts

Complex interactions between noncoordinating residues are significant yet commonly overlooked components of macromolecular catalyst function. While these interactions have been demonstrated to impact binding affinities and catalytic rates in metalloenzymes, the roles of similar structural elements in synthetic polymeric catalysts remain underexplored. Using a model Suzuki–Miyuara cross-coupling reaction, we performed a series of systematic studies to probe the interconnected effects of metal–ligand cross-links, electrostatic interactions, and local rigidity in polymer catalysts. To achieve this, a novel bifunctional triphenylphosphine acrylamide (BisTPPAm) monomer was synthesized and evaluated alongside an analogous monofunctional triphenylphosphine acrylamide (TPPAm). In model copolymer catalysts, increased initial reaction rates were observed for copolymers untethered by Pd complexation (BisTPPAm-containing) compared to Pd-cross-linked catalysts (TPPAm-containing). Further, incorporating local rigidity through secondary structure-like and electrostatic interactions revealed nonmonotonic relationships between composition and the reaction rate, demonstrating the potential for tunable behavior through secondary-sphere interactions. Lastly, through rigorous cheminformatics featurization strategies and statistical modeling, we quantitated relationships between chemical descriptors of the substrate and reaction conditions on catalytic performance. Collectively, these results provide insights into relationships among the composition, structure, and function of protein-mimetic catalytic copolymers.

Catalysts↗
DOE OSTI2012

Solid–Electrolyte Interphase Formation and Electrolyte Reduction at Li-Ion Battery Graphite Anodes: Insights from First-Principles Molecular Dynamics

Understanding the nature and formation of the solid–electrolyte interphase (SEI) formed in electrochemical storage devices, such as Li-ion batteries, is most important for improving functionality. Few experiments exist that adequately probe the SEI, particularly in situ. We perform predictive ab initio molecular dynamics simulations of the anode–electrolyte interface for several electrolytes and interface functionalizations. These show strongly differing effects on the reducibility of the electrolyte. Electrolyte reduction occurs rapidly, on a picosecond time scale. Orientational ordering of electrolyte near the interface precedes reduction. The reduced species depend strongly on surface functionalization and presence of LiPF6 salt. While LiPF6 salt in ethylene carbonate is more stable at a hydrogen-terminated anode, oxygen/hydroxyl termination causes spontaneous dissociation to form LiF and other fluorophosphates. LiF migrates to the interface creating chainlike structures, consistent with experimental observations of LiF agglomeration. Inorganic products such as LiF and Li2CO3 migrate closer to the anode than purely organic components, consistent with their more ionic character. Significantly, we conclude that while the electrolyte reduction occurs at the molecular level near the interface, requiring specific alignments and proximity, the reducibility is governed by the average reduction potential barrier between the electrode (anode) and the electrolyte.

25 ENERGY STORAGE↗
DOE OSTI2014

Revisiting Photoemission and Inverse Photoemission Spectra of Nickel Oxide from First Principles: Implications for Solar Energy Conversion

We use two different ab initio quantum mechanics methods, complete active space self-consistent field theory applied to electrostatically embedded clusters and periodic many-body G₀W₀ calculations, to reanalyze the states formed in nickel(II) oxide upon electron addition and ionization. In agreement with interpretations of earlier measurements, we find that the valence and conduction band edges consist of oxygen and nickel states, respectively. However, contrary to conventional wisdom, we find that the oxygen states of the valence band edge are localized whereas the nickel states at the conduction band edge are delocalized. We argue that these characteristics may lead to low electron-hole recombination and relatively efficient electron transport, which, coupled with band gap engineering, could produce higher solar energy conversion efficiency compared to that of other transition-metal oxides. Both methods find a photoemission/inverse-photoemission gap of 3.6-3.9 eV, in good agreement with the experimental range, lending credence to our analysis of the electronic structure of NiO.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2018

Design principles for electronic charge transport in solution-processed vertically stacked 2D perovskite quantum wells

State-of-the-art quantum-well-based devices such as photovoltaics, photodetectors, and light-emission devices are enabled by understanding the nature and the exact mechanism of electronic charge transport. Ruddlesden–Popper phase halide perovskites are two-dimensional solution-processed quantum wells and have recently emerged as highly efficient semiconductors for solar cell approaching 14% in power conversion efficiency. However, further improvements will require an understanding of the charge transport mechanisms, which are currently unknown and further complicated by the presence of strongly bound excitons. Here, we unambiguously determine that dominant photocurrent collection is through electric field-assisted electron–hole pair separation and transport across the potential barriers. This is revealed by in-depth device characterization, coupled with comprehensive device modeling, which can self-consistently reproduce our experimental findings. These findings establish the fundamental guidelines for the molecular and device design for layered 2D perovskite-based photovoltaics and optoelectronic devices, and are relevant for other similar quantum-confined systems.

36 MATERIALS SCIENCE↗