Thermal Transport Across a Substrate-Thin-Film Interface: Effects of Film Thickness and Surface Roughness

Using Molecular Dynamics Simulations and a Model AlN-GaN Interface, We Demonstrate that the Interfacial Thermal Resistance RK (Kapitza Resistance) between a Substrate and Thin Film Depends on the Thickness of the Film and the Film Surface Roughness When the Phonon Mean Free Path is Larger Than Film Thickness. in Particular, When the Film (External) Surface is Atomistically Smooth, Phonons Transmitted from the Substrate Can Travel Ballistically in the Thin Film, Be Scattered Specularly at the Surface, and Return to the Substrate Without Energy Transfer. If the External Surface Scatters Phonons Diffusely, Which is Characteristic of Rough Surfaces, RK is Independent of Film Thickness and is the Same as RK that Characterizes Smooth Surfaces in the Limit of Large Film Thickness. at Interfaces Where Phonon Transmission Coefficients Are Low, the Thickness Dependence is Greatly Diminished Regardless of the Nature of Surface Scattering. the Film Thickness Dependence of RK is Analogous to the Well-Known Fact of Lateral Thermal Conductivity Thickness Dependence in Thin Films. the Difference is that Phonon-Boundary Scattering Lowers the In-Plane Thermal Transport in Thin Films, But It Facilitates Thermal Transport from the Substrate to the Thin Film. © 2014 American Physical Society

Liquid Phase Stability under an Extreme Temperature Gradient

Using Nonequilibrium Molecular Dynamics Simulations, We Subject Bulk Liquid to a Very High-Temperature Gradient and Observe a Stable Liquid Phase with a Local Temperature Well above the Boiling Point. Also, under This High-Temperature Gradient, the Vapor Phase Exhibits Condensation into a Liquid at a Temperature Higher Than the Saturation Temperature, Indicating that the Observed Liquid Stability is Not Caused by Nucleation Barrier Kinetics. We Show that, Assuming Local Thermal Equilibrium, the Phase Change Can Be Understood from the Thermodynamic Analysis. the Observed Elevation of the Boiling Point is Associated with the Interplay between the Bulk Driving Force for the Phase Change and Surface Tension of the Liquid-Vapor Interface that Suppresses the Transformation. This Phenomenon is Analogous to that Observed for Liquids in Confined Geometries. in Our Study, However, a Low-Temperature Liquid, Rather Than a Solid, Confines the High-Temperature Liquid. © 2013 American Physical Society

Curvature Induced Phase Stability of an Intensely Heated Liquid

We Use Non-Equilibrium Molecular Dynamics Simulations to Study the Heat Transfer Around Intensely Heated Solid Nanoparticles Immersed in a Model Lennard-Jones Fluid. We Focus Our Studies on the Role of the Nanoparticle Curvature on the Liquid Phase Stability under Steady-State Heating. for Small Nanoparticles We Observe a Stable Liquid Phase Near the Nanoparticle Surface, Which Can Be at a Temperature Well above the Boiling Point. Furthermore, for Particles with Radius Smaller Than a Critical Radius of 2 Nm We Do Not Observe Formation of Vapor Even above the Critical Temperature. Instead, We Report the Existence of a Stable Fluid Region with a Density Much Larger Than that of the Vapor Phase. We Explain the Stability in Terms of the Laplace Pressure Associated with the Formation of a Vapor Nanocavity and the Associated Effect on the Gibbs Free Energy. © 2014 AIP Publishing LLC

Evolutionary optimization of a charge transfer ionic potential model for Ta/Ta-oxide hetero-interfaces

Tantalum, tantalum oxide and their hetero-interfaces are of tremendous technological interest in several applications spanning electronics, thermal management, catalysis and biochemistry. For example, local oxygen stoichiometry variation in TaOx memristors comprising of metallic (Ta) and insulating oxide (Ta2O5) have been shown to result in fast switching on the sub-nanosecond timescale over a billion cycles, relevant to neuromorphic computation. Despite its broad importance, an atomistic scale understanding of oxygen stoichiometry variation across Ta/TaOx hetero-interfaces, such as during early stages of oxidation and oxide growth, is not well understood. This is mainly due to the lack of a variable charge interatomic potential model for tantalum oxides that can accurately describe the ionic interactions in the metallic (Ta) and oxide (TaOx) environment as well as at their interfaces. To address this challenge, we introduce a charge transfer ionic potential (CTIP) model for Ta/Ta-oxide system by training against lattice parameters, cohesive energies, equations of state, and elastic properties of various experimentally observed Ta2O5 polymorphs. The best set of CTIP parameters are determined by employing a single-objective global optimization scheme driven by genetic algorithms followed by local Simplex optimization. Our newly developed CTIP potential accurately predicts structure, thermodynamics, energetic ordering of polymorphs, as well as elastic and surface properties of both Ta and Ta2O5, in excellent agreement with DFT calculations and experiments. We employ our newly parameterized CTIP potential to investigate the early stages of oxidation of Ta at different temperatures and atomic/molecular nature of the oxidizing species

Comparing optimization strategies for force field parameterization

Classical molecular dynamics (MD) simulations enable modeling of materials and examination of microscopic details that are not accessible experimentally. The predictive capability of MD relies on the force field (FF) used to describe interatomic interactions. FF parameters are typically determined to reproduce selected material properties computed from density functional theory (DFT) and/or measured experimentally. A common practice in parameterizing FFs is to use least-squares local minimization algorithms. Genetic algorithms (GAs) have also been demonstrated as a viable global optimization approach, even for complex FFs. However, an understanding of the relative effectiveness and efficiency of different optimization techniques for the determination of FF parameters is still lacking. In this work, we evaluate various FF parameter optimization schemes, using as example a training data set calculated from DFT for different polymorphs of Ir$O_2$. The Morse functional form is chosen for the pairwise interactions and the optimization of the parameters against the training data is carried out using (1) multi-start local optimization algorithms: Simplex, Levenberg-Marquardt, and POUNDERS, (2) single-objective GA, and (3) multi-objective GA. Using random search as a baseline, we compare the algorithms in terms of reaching the lowest error, and number of function evaluations. We also compare the effectiveness of different approaches for FF parameterization using a test data set with known ground truth (i.e generated from a specific Morse FF). We find that the performance of optimization approaches differs when using the Test data vs. the DFT data. Overall, this study provides insight for selecting a suitable optimization method for FF parameterization, which in turn can enable more accurate prediction of material properties and chemical phenomena

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

Atomic Cross-Talk at the Interface: Enhanced Lubricity and Wear and Corrosion Resistance in Sub 2 nm Hybrid Overcoats via Strengthened Interface Chemistry

Friction, wear, and corrosion remain the major causes of premature failure of diverse systems including hard-disk drives (HDDs). To enhance the areal density of HDDs beyond 1 Tb/in2, the necessary low friction and high wear and corrosion resistance characteristics with sub 2 nm overcoats remain unachievable. Here we demonstrate that atom cross-talk not only manipulates the interface chemistry but also strengthens the tribological and corrosion properties of sub 2 nm overcoats. High-affinity (HA) atomically thin (∼0.4 nm) interlayers (ATIs, XHA), namely Ti, Si, and SiNx, are sandwiched between the hard-disk media and 1.5 nm thick carbon (C) overlayer to develop interface-enhanced sub 2 nm hybrid overcoats that consistently outperform a thicker conventional commercial overcoat (≥2.7 nm), with the C/SiNx bilayer overcoat bettering all other <2 nm thick overcoats. These hybrid overcoats can enable the development of futuristic 2–4 Tb/in2 areal density HDDs and can transform various moving-mechanical-system based technologies

Efficient crystal structure prediction for structurally related molecules with accurate and transferable tailor-made force fields

Crystal structure prediction (CSP) has been historically used to complement experimental solid form screening and applied to individual molecules in drug development. The fast development of algorithms and computing resources offers the opportunity to use CSP earlier and for a broader range of applications in the drug design cycle. This study presents a novel paradigm of CSP specifically designed for structurally related molecules, referred to as Quick-CSP. The approach prioritizes more accurate physics through robust and transferable tailor-made force fields (TMFFs), such that significant efficiency gains are achieved through the reduction of expensive ab initio calculations. The accuracy of the TMFF is increased by the introduction of electrostatic multipoles and the fragment-based force field parameterization scheme is demonstrated to be transferable for a family of chemically related molecules. The protocol is benchmarked with structurally related compounds from the Bromodomain and Extraterminal (BET) domain inhibitors series. A new convergence criterion is introduced that aims at performing only as many ab initio optimizations of crystal structures as required to locate the bottom of the crystal energy landscape within a user-defined accuracy. The overall approach provides significant cost savings ranging from three to eight-fold less than the Full-CSP workflow. The reported advancements expand the scope and utility of the underlying CSP building blocks as well as their novel reassembly to other applications earlier in the drug design cycle to guide molecule design and selection