Unraveling the effects of inter-site Hubbard interactions in spinel Li-ion cathode materials

Accurate first-principles predictions of the structural, electronic, magnetic, and electrochemical properties of cathode materials can be key in the design of novel efficient Li-ion batteries. Spinel-type cathode materials Li$_x$Mn$_2$O$_4$ and Li$_x$Mn$_{1.5}$Ni$_{0.5}$O$_4$ are promising candidates for Li-ion battery technologies, but they present serious challenges when it comes to their first-principles modeling. Here, we use density-functional theory with extended Hubbard functionals - DFT+$U$+$V$ with on-site $U$ and inter-site $V$ Hubbard interactions - to study the properties of these transition-metal oxides. The Hubbard parameters are computed from first-principles using density-functional perturbation theory. We show that while $U$ is crucial to obtain the right trends in properties of these materials, $V$ is essential for a quantitative description of the structural and electronic properties, as well as the Li-intercalation voltages. This work paves the way for reliable first-principles studies of other families of cathode materials without relying on empirical fitting or calibration procedures

Understanding the role of Hubbard corrections in the rhombohedral phase of BaTiO3_3

We present a first-principles study of the low-temperature rhombohedral phase of BaTiO$_3$ using Hubbard-corrected density-functional theory. By employing density-functional perturbation theory, we compute the onsite Hubbard $U$ for Ti($3d$) states and the intersite Hubbard $V$ between Ti($3d$) and O($2p$) states. We show that applying the onsite Hubbard $U$ correction alone to Ti($3d$) states proves detrimental, as it suppresses the Ti($3d$)-O($2p$) hybridization and drives the system towards a cubic phase. Conversely, when both onsite $U$ and intersite $V$ are considered, the localized character of the Ti($3d$) states is maintained, while also preserving the Ti($3d$)-O($2p$) hybridization, restoring the rhombohedral phase of BaTiO$_3$. The generalized PBEsol+$U$+$V$ functional yields remarkable agreement with experimental results for the band gap and dielectric constant, while the optimized geometry is slightly less accurate compared to PBEsol. Zone-center phonon frequencies and Raman spectra, being significantly influenced by the underlying geometry, demonstrate better agreement with experiments in the case of PBEsol, while PBEsol+$U$+$V$ exhibits reduced accuracy, and the PBEsol+$U$ Raman spectrum diverges remarkably from experimental data, highlighting the adverse impact of the $U$ correction alone in BaTiO$_3$. Our findings underscore the promise of the extended Hubbard PBEsol+$U$+$V$ functional with first-principles $U$ and $V$ for the investigation of other ferroelectric perovskites with mixed ionic-covalent interactions

Habituation based synaptic plasticity and organismic learning in a quantum perovskite

A central characteristic of living beings is the ability to learn from and respond to their environment leading to habit formation and decision making. This behavior, known as habituation, is universal among all forms of life with a central nervous system, and is also observed in single-cell organisms that do not possess a brain. Here, we report the discovery of habituation-based plasticity utilizing a perovskite quantum system by dynamical modulation of electron localization. Microscopic mechanisms and pathways that enable this organismic collective charge-lattice interaction are elucidated by first-principles theory, synchrotron investigations, ab initio molecular dynamics simulations, and in situ environmental breathing studies. We implement a learning algorithm inspired by the conductance relaxation behavior of perovskites that naturally incorporates habituation, and demonstrate learning to forget: A key feature of animal and human brains. Incorporating this elementary skill in learning boosts the capability of neural computing in a sequential, dynamic environment.United States. Army Research Office (Grant W911NF-16-1-0289)United States. Air Force Office of Scientific Research (Grant FA9550-16-1-0159)United States. Army Research Office (Grant W911NF-16-1-0042

Charge Transport in Molecular Junctions: A Study of Level-Alignment, Thermoelectric Properties, and Environmental Effects

Here, we use and develop first-principles methods based on density functional theory (DFT) and beyond to understand and predict charge transport phenomena in the novel class of nanostructured devices: molecular junctions. Molecular junctions, individual molecules contacted to two metallic leads, which can be systematically altered by modifying the chemistry of each component, serve as test beds for the study of transport at the nanoscale. To date, various experimental methods have been designed to reliably assemble and mea- sure transport properties of molecular junctions. Furthermore, theoretical methods built on DFT designed to yield quantitative agreement with these experiments for certain classes of molecular junctions have been developed. In order to gain insight into a broader range of molecular junctions and environmental effects associated with the surrounding solution, this dissertation will employ, explore and extend first-principles DFT calculations coupled with approximate self-energy corrections known to yield quantitative agreement with experiments for certain classes of molecular junctions.To start we examine molecular junctions in which the molecule is strongly hybridized with the leads: a challenging limit for the existing methodology. Using a physically motivated tight-binding model, we find that the experimental trends observed for such molecules can be explained by the presence of a so-called “gateway” state associated with the chemical bond that bridges the molecule and the lead. We discuss the ingredients of a self-energy corrected DFT based approach to quantitatively predict conductance in the presence of these hybridization effects.We also develop and apply an approach to account for the surrounding environment on the conductance, which has been predominantly ignored in past transport calculations due to computational complexity. Many experiments are performed in a solution of non-conducting molecules; far from benign, this solution is known to impact the measured conductance by as much as a factor of two. Here, we show that the dominant effect of the solution stems from nearby molecules binding to the lead surface surrounding the junction and altering the local electrostatics. This effect operates in much the same way adsorbates alter the work function of a surface. We develop a framework which implicitly includes the surrounding molecules through an electrostatic-based lattice model with parameters from DFT calculations, reducing the computational complexity of this problem while retaining predictive power. Our approach for computing environmental effects on charge transport in such junctions will pave the way for a better understanding of the physics of nanoscale devices, which are known to be highly sensitive to their surroundings

Thermodynamics and dielectric response of BaTiO3 by data-driven modeling

Modeling ferroelectric materials from first principles is one of the successes of density-functional theory and the driver of much development effort, requiring an accurate description of the electronic processes and the thermodynamic equilibrium that drive the spontaneous symmetry breaking and the emergence of macroscopic polarization. We demonstrate the development and application of an integrated machine learning model that describes on the same footing structural, energetic, and functional properties of barium titanate (BaTiO3), a prototypical ferroelectric. The model uses ab initio calculations as a reference and achieves accurate yet inexpensive predictions of energy and polarization on time and length scales that are not accessible to direct ab initio modeling. These predictions allow us to assess the microscopic mechanism of the ferroelectric transition. The presence of an order-disorder transition for the Ti off-centered states is the main driver of the ferroelectric transition, even though the coupling between symmetry breaking and cell distortions determines the presence of intermediate, partly-ordered phases. Moreover, we thoroughly probe the static and dynamical behavior of BaTiO3 across its phase diagram without the need to introduce a coarse-grained description of the ferroelectric transition. Finally, we apply the polarization model to calculate the dielectric response properties of the material in a full ab initio manner, again reproducing the correct qualitative experimental behavior

Microscopic picture of paraelectric perovskites from structural prototypes

We highlight with first-principles molecular dynamics the persistence of intrinsic 〈111〉 Ti off-centerings for BaTiO_{3} in its cubic paraelectric phase. Intriguingly, these are inconsistent with the Pm3[over ¯]m space group often used to atomistically model this phase using density-functional theory or similar methods. Therefore, we deploy a systematic symmetry analysis to construct representative structural models in the form of supercells that satisfy a desired point symmetry but are built from the combination of lower-symmetry primitive cells. We define as structural prototypes the smallest of these that are both energetically and dynamically stable. Remarkably, two 40-atom prototypes can be identified for paraelectric BaTiO_{3}; these are also common to many other ABO_{3} perovskites. These prototypes can offer structural models of paraelectric phases that can be used for the computational engineering of functional materials. Last, we show that the emergence of B-cation off-centerings and the primitive-cell phonon instabilities is controlled by the equilibrium volume, in turn, dictated by the filler A cation