R. Ramprasad

University of Connecticut, Storrs, Connecticut, United States

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Publications (117)233.58 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: Being in the group with the most diverse set of properties among all in the periodic table, the Group 14 elements (C, Si, Ge, Sn, and Pb) are particularly interesting candidates for structure–property investigation. Motivated by the need to create new insulators for energy storage and electronics applications, we study a few compounds based on Group 14 elements in this work, namely the dihydrides, dichlorides, and difluorides. Using density functional theory (DFT) calculations, we establish patterns in their properties, including favored coordination chemistry, stability, electronic structure, and dielectric behavior. While a coordination number (CN) of 4 is commonly associated with Group 14 elements, there is a significant deviation from it down the group, with CNs as high as 7 and 8 common in Pb. Further, there is an increase in the relative stability of the +2 oxidation state as opposed to +4 when we go from C to Pb, a direct consequence of which is the existence of the di-compounds of C and Si as polymers, whereas the compounds of Ge, Sn, and Pb are strictly 3D crystalline solids. The coordination chemistries are further linked with the band gaps and dielectric constants (divided into two components: the electronic part and the ionic part) of these compounds. We also see that the more stable difluorides and dichlorides have large band gaps and small electronic dielectric constants, and most of the Ge and Sn compounds have remarkably large ionic dielectric constants by virtue of having polar and more flexible bonds. The staggering variation in properties displayed by these parent compounds offers opportunities for designing derivative materials with a desired combination of properties.
    Journal of Materials Science 01/2015; 50(2). · 2.31 Impact Factor
  • Venkatesh Botu, Rampi Ramprasad
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    ABSTRACT: Quantum mechanics based ab-initio molecular dynamics (MD) simulation schemes offer an accurate and direct means to monitor the time-evolution of materials. Nevertheless, the expensive and repetitive energy and force computations required in such simulations lead to significant bottlenecks. Here, we lay the foundations for such an accelerated ab-initio MD approach integrated with a machine learning framework. The proposed algorithm learns from previously visited configurations in a continuous and adaptive manner on-the-fly, and predicts (with chemical accuracy) the energies and atomic forces of a new configuration at a minuscule fraction of the time taken by conventional ab-initio methods. Key elements of this new accelerated ab-initio MD paradigm include representations of atomic configurations by numerical fingerprints, the learning algorithm, a decision engine that guides the choice of the prediction scheme, and requisite amount of ab-initio data. The performance of each aspect of the proposed scheme is critically evaluated for Al in several different chemical environments. This work can readily be extended to address non-elemental compounds, and has enormous implications beyond ab-initio MD acceleration. It can also lead to accelerated structure and property prediction schemes, and accurate force-fields.
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    ABSTRACT: Supplementary information available for this article at http://www.nature.com/ncomms/2014/140917/ncomms5845/suppinfo/ncomms5845_S1.html
    Nat Commun. 09/2014; 5.
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    ABSTRACT: We demonstrate that weak chemical interactions between untethered moieties in molecular nanolayers on metal surfaces can strongly influence the effective work function Φeff. Electron spectroscopy shows that nanolayers of mercaptan-anchored organophosphonates on Au and Pt decrease Φeff. The measured Φeff shifts correlate with the chemical state of phosphonic acid moieties, and scale with molecular length. These results are contrary to predictions of ab initio calculations of monolayer-capped surfaces, but are consistent with calculations of bilayer-capped surfaces with face-to-face hydrogen-bonded phosphonic acid moieties. Our findings indicate that intra-layer bonding and layering in molecular nanolayers can be key to tailoring heterointerfacial electronic properties for applications.
    Applied Physics Letters 08/2014; 105(8):081601-081601-5. · 3.52 Impact Factor
  • S.K. Yadav, R. Ramprasad, A. Misra, X.-Y. Liu
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    ABSTRACT: A first-principles computational scheme was applied for studying edge and screw dislocations in non-elemental systems for the first time. For the case of TiN as a model system, we established the preferred slip systems for edge and screw dislocations, with a Burgers vector of a /2〈1 1¯ 0〉 on the {0 0 1}, {1 1 0} and {1 1 1} slip planes. The simulations adopted periodically repeating triclinic supercells containing a dipole of dislocations arranged such that periodicity can be maintained without imposition of large spurious elastic stresses. It was determined that the Peierls stress is the smallest for slip along the {1 1 0} plane, and largest for slip along the {0 0 1} plane, for both edge and screw dislocations. The dislocation core structures and the Peierls stress results are discussed and compared to those in a purely ionic MgO system.
    Acta Materialia 08/2014; 74:268–277. · 3.94 Impact Factor
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    ABSTRACT: The question of whether one can systematically identify (previously unknown) ferroelectric phases of a given material is addressed, taking hafnia (HfO$_2$) as an example. Low free energy phases at various pressures and temperatures are identified using a first-principles based structure search algorithm. Ferroelectric phases are then recognized by exploiting group theoretical principles for the symmetry-allowed displacive transitions between non-polar and polar phases. Two orthorhombic polar phases occurring in space groups $Pca2_1$ and $Pmn2_1$ are singled out as the most viable ferroelectric phases of hafnia, as they display low free energies (relative to known non-polar phases), and substantial switchable spontaneous electric polarization. These results provide an explanation for the recently observed surprising ferroelectric behavior of hafnia, and reveal pathways for stabilizing ferroelectric phases of hafnia as well as other compounds.
    Physical Review B 07/2014; 90(06):064111. · 3.66 Impact Factor
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    ABSTRACT: Development of new dielectric materials is of great importance for a large range of applications for modern electronics and electrical power systems. The state-of-art polymer dielectric is biaxially oriented polypropylene (BOPP) films having a maximum energy density of 5 J/cm(3) and a high breakdown field of 700 MV/m, but with limited dielectric constant (~ 2.2) and reduced breakdown strength above 85 (o)C. Great effort has been put into exploring other materials to fulfill the demand of continuous miniaturization and improved functionality. In this research, a series of polyimides were investigated as potential polymer material for this application. Polyimide with high dielectric constants of up to 7.8, was prepared that exhibits low dissipation factors (<1 %) and high energy density around 15 J/cm(3), which is three times that of BOPP. Our syntheses were guided by high-throughput density functional theory (DFT) calculations for rational design in terms of high dielectric constant and band gap. Correlations of experimental and theoretical results through judicious variations of polyimide structures allowed for a clear demonstration of the relationship between chemical functionalities and dielectric properties.
    ACS Applied Materials & Interfaces 06/2014; · 5.90 Impact Factor
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    ABSTRACT: The recently developed evolutionary algorithm USPEX proved to be a tool that enables accurate and reliable prediction of structures for a given chemical composition. Here we extend this method to predict the crystal structure of polymers by performing constrained evolutionary search, where each monomeric unit is treated as one or several building blocks with fixed connectivity. This greatly reduces the search space and allows the initial structure generation with different sequences and packings using these blocks. The new constrained evolutionary algorithm is successfully tested and validated on a diverse range of experimentally known polymers, namely polyethylene (PE), polyacetylene (PA), poly(glycolic acid) (PGA), poly(vinyl chloride) (PVC), poly(oxymethylene) (POM), poly(phenylene oxide) (PPO), and poly (p-phenylene sulfide) (PPS). By fixing the orientation of polymeric chains, this method can be further extended to predict all polymorphs of poly(vinylidene fluoride) (PVDF), and the complex linear polymer crystals, such as nylon-6 and cellulose. The excellent agreement between predicted crystal structures and experimentally known structures assures a major role of this approach in the efficient design of the future polymeric materials.
    The Journal of chemical physics. 06/2014; 141(15).
  • Chenchen Wang, Rampi Ramprasad
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    ABSTRACT: The present contribution provides a strategy to enhance the dielectric constant of polyethylene by chemical modification while not overly compromising its large band gap. Isolated polyethylene chains are considered and the CH2 motifs in the backbone are allowed to be substituted by a number of Group 14 motifs, including SiF2, SiCl2, GeF2, GeCl2, SnF2, and SnCl2, in a systematic, progressive, and exhaustive combinatorial manner. Our results indicate that consecutive SnF2 or GeF2 motifs in the polyethylene backbone are most desirable, which can lead to systems with dielectric constant as high as 47.
    International Journal of High Speed Electronics and Systems 05/2014; 23(01n02).
  • S K Yadav, R Ramprasad, J Wang, A Misra, X-Y Liu
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    ABSTRACT: Using density functional theory based first-principles calculations, we show that the preferred interfacial plane orientation relationship is determined by the strength of bonding at the interface. The thermodynamic stability, and the ideal tensile and shear strengths of Cu(1 1 1)/TiN(1 1 1) and Al(1 1 1)/TiN(1 1 1) interfaces are calculated. While there is a strong orientation relation preference for the Al/TiN interface, there is no orientation relation preference for the Cu/TiN interface. Both the ideal tensile and shear strengths of Cu/TiN interfaces are lower than those of bulk Cu and TiN, suggesting such interfaces are weaker than their bulk components. By comparison, the ideal strengths of the Al/TiN interface are comparable to the constituents in the bulk form. Such contrasting interfaces can be a test-bed for studying the role of interfaces in determining the mechanical behavior of the nanolayered structures.
    Modelling and Simulation in Materials Science and Engineering 03/2014; 22(3):035020. · 1.93 Impact Factor
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    ABSTRACT: This work examines the complex nature of SOx (x = 0–4) interaction and oxidation on Pt(111) and Pd(111) surfaces using density functional theory (DFT) calculations coupled with microkinetic modeling. Thermodynamic and kinetic analyses suggest similar adsorption and oxidation behaviors for SOx species on both metal surfaces, although the observed greater tendency of Pd to undergo sulfating is borne out by the present results. Selected quantities computed using DFT, when used in a previously developed microkinetic model, are shown to predict SO2 conversion as a function of temperature in excellent agreement with available experimental data.
    The Journal of Physical Chemistry C 03/2014; · 4.84 Impact Factor
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    Polymer 02/2014; 55(4):979–988. · 3.77 Impact Factor
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    ABSTRACT: Ceria offers great promise in catalysis, due to its facile switchable oxidation state manifested from its oxygen buffering capability. This work presents the first equilibrium surface phase diagram of ceria exposed to various oxygen providing reservoirs (e.g., a pure O2 reservoir as well as NO/NO2, H2/H2O, or CO/CO2 redox environments) using first principles thermodynamics. For a pure O2 environment, the stoichiometric ceria (111) surface is favored at ambient conditions. Any appreciable surface reduction is observed only at ultra-low oxygen partial pressures (< 10− 30 atm) and room temperature or at temperatures > 2000 K and ambient pressures. On the other hand, a redox environment promotes surface reduction at temperatures as low as 300 K. Semi-local, Hubbard modified semi-local, and hybrid electronic exchange-correlation functionals are used to capture the energetics and phase transitions. We observe no difference between the three theories in the energetics governing ceria surface reduction in the dilute limit. The predicted phase transitions by all levels of theory are in agreement with each other and in excellent agreement with literature experimental data. Creation of oxygen vacancies in the sub-surface is energetically favored over surface vacancies, and is pivotal in determining the key features of the surface phase diagram. Consequently, we identify the oxygen vacancy formation energy as a descriptor for the surface reactivity of ceria in various oxygen environments. This single governing factor could be used in future studies to probe the surface reactivity of ceria and also to design improved ceria-based materials for redox reactions.
    Surface Science 01/2014; 619:49–58. · 1.87 Impact Factor
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    ABSTRACT: The structure and magnetic ordering of bulk TbMn0.5Cr0.5O3 was revealed through bulk magnetization and neutron diffraction measurements, and first-principles calculations, respectively. G-type antiferromagnetic ordering of Mn3+ and Cr3+ moments was observed in the neutron diffraction data below Néel temperature TN ∼ 84 K. In addition, below ∼40 K, short-range magnetic ordering was identified correlating to a ferromagnetic component due to the canting of the moments along the c-axis. The spin configuration is consistent with the first-principles calculations. The magnetic structure revealed in the present TbMn0.5Cr0.5O3 sample is distinct from that observed for both end members TbMnO3 and TbCrO3.
    Journal of Applied Physics 01/2014; 116(3):033919-033919-5. · 2.21 Impact Factor
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    ABSTRACT: To date, trial and error strategies guided by intuition have dominated the identification of materials suitable for a specific application. We are entering a data-rich, modelling-driven era where such Edisonian approaches are gradually being replaced by rational strategies, which couple predictions from advanced computational screening with targeted experimental synthesis and validation. Here, consistent with this emerging paradigm, we propose a strategy of hierarchical modelling with successive downselection stages to accelerate the identification of polymer dielectrics that have the potential to surpass 'standard' materials for a given application. Successful synthesis and testing of some of the most promising identified polymers and the measured attractive dielectric properties (which are in quantitative agreement with predictions) strongly supports the proposed approach to material selection.
    Nature Communications 01/2014; 5:4845. · 10.74 Impact Factor
  • Clive R Bealing, R Ramprasad
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    ABSTRACT: A microscopic mechanism governing the initiating step in the high-field aging of crystalline polyethylene is proposed, based on density functional calculations and ab initio molecular dynamics simulations. It is assumed that electrons, holes, and excitons are present in the system. While the additional individual electrons or holes are not expected to lead to significant degradation, the presence of triplet excitons are concluded to be rather damaging. The electron and hole states of the exciton localize on a distorted region of polyethylene, significantly weakening nearby C-H bonds and facilitating C-H bond scission. The barrier to cleavage of the weakened C-H bonds is estimated and is comparable to the thermal energy, suggesting that this mechanism may be responsible for the degradation of polyethylene when placed under electrical stress, e.g., in high-voltage cables.
    The Journal of Chemical Physics 11/2013; 139(17):174904. · 3.12 Impact Factor
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    ABSTRACT: doi: 10.1080/14786435.2013.856525
    Philosophical Magazine 11/2013; 94(5):464-475. · 1.60 Impact Factor
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    ABSTRACT: Most polyolefins that are used for dielectric materials exhibit a low dielectric constant and operating temperatures up to 70°C. Polyimides offer a means to a higher dielectric constant material by the introduction of a polar group in the polymer backbone and are thermally stable at temperatures exceeding 250°C. A common dianhydride, pyromellitic dianhydride (PMDA), is reacted with various short-chain diamines to produce polymers with high imide density. Homopolymers and copolymers synthesized had dielectric constants ranging from 3.96 to 6.57. These materials exhibit a dielectric constant twice that of biaxially oriented polypropylene and therefore a twofold increase in capacitance as well as maintaining low dissipation factors that are acceptable for this application. The experimental dielectric constants of these materials are also compared to density functional theory calculations and exhibit a close relationship. © 2013 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 130: 1276-1280, 2013
    Journal of Applied Polymer Science 10/2013; 130(2). · 1.40 Impact Factor
  • L. Autry, R. Ramprasad
    Journal of Materials Science 10/2013; 48(19):6542-6548. · 2.31 Impact Factor
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    ABSTRACT: The materials discovery process|an expensive and time-consuming endeavor|can be significantly expedited and simplified if we can learn effectively from past knowledge. Indeed, the ability to make predictions or decisions by automated learning from the past has found astonishing success in the cognitive sciences. Along similar lines, the present work offers a versatile learning framework (based on chemical similarity) aimed at ultra-fast predictions of any material property, given just historic data. A family of polymeric systems is considered as an example, with the initial property dataset generated using expensive quantum mechanical computations. Trained machine learning models then predict a plethora of properties (including energetic, structural, elastic, optical, and dielectric properties) of an enormous number of new polymers within the same family, and reveal hidden correlations and tradeoffs between properties, at negligible cost with high fidelity. Harnessing such learning paradigms extends recent efforts to systematically explore and mine vast chemical spaces, and can significantly accelerate the discovery of new application-specific materials.
    Scientific Reports 09/2013; · 5.08 Impact Factor

Publication Stats

433 Citations
233.58 Total Impact Points


  • 2005–2014
    • University of Connecticut
      • • Department of Chemical and Biomolecular Engineering
      • • Department of Materials Science and Engineering
      • • Institute of Materials Science
      Storrs, Connecticut, United States
  • 2008–2011
    • University of Toronto
      • The Edward S. Rogers Sr. Department of Electrical and Computer Engineering
      Toronto, Ontario, Canada