Ni(COD)(2)-Catalyzed ipso-Silylation of 2-Methoxynaphthalene: A Density Functional Theory Study

Density functional theory has been used for the systematic investigation of the mechanism involved in Ni(COD)(2)-catalyzed ipso-silylation of 2-methoxynaphthalene. The two fundamental mechanistic pathways, internal nucleophilic substitution and a nonclassical oxidative addition, have been studied. In both pathways, the first equivalent of KOtBu directly reacts with the silyl boronate (Et3SiBpin) to generate the silyl anion surrogate Et3SiK or silylborate [Et3Si-Bpin(OtBu)]K (IN3), which further reacts with Ni(COD)(2) to form a substrate catalyst complex, [(eta(2)-COD)(2)NiSiEt3]K. The internal nucleophilic substitution reaction pathway proceeds through eta(2) complexation of nickel with the C(1)=C(2) bond of 2-methoxynaphthalene. Later, nickel connects to =C(1) through sigma-bond formation and coordinates with oxygen of the -OMe group. Simultaneously, the -SiEt3 group approaches =C(2) possessing -OMe followed by rearomatization which is facilitated by coordination of K+ with nickel and methoxy oxygen. In a nonclassical oxidative addition, the chelation of K+ with -OMe as well as -SiEt3 from [(eta(2)-COD)(2)NiSiEt3] is the key step which promotes the insertion of NiSiEt3 to the =C(2) carbon of 2-methoxynaphthalene. We also observed that the activation energy barrier in the non-pi-extended aromatic systems is higher than that of the pi-extended aromatic systems. The overall study manifests that Ni(COD)(2)-catalyzed ipso-silylation of 2-methoxynapthalene operates through an internal nucleophilic substitution pathway

Exploiting Hierarchical Configuration to Improve Run-Time MPSoC Task Assignment ∗

Run-time assignment of a set of communicating tasks onto a heterogeneous multiprocessor system-on-chip (MP-SoC) platform is a challenging task. Having FPGA fabric tiles in such MPSoC platform increases performance and flexibility of the platform. Such FPGA tiles can not only run tasks in hardware but also instantiate a soft IP core that executes the task functionality. Thus fully exploiting the available FPGA fabric resources must include exploiting such a hierarchical configuration. This paper details the benefits of using a hierarchical configuration and illustrates how to incorporate it within a generic run-time task assignment heuristic. We show that adding a hierarchical configuration significantly improves task assignment performance (i.e. success rate and assignment quality). In several cases, the performance of a heuristic with a hierarchical configuration extends beyond the capabilities of a full solution space exploration without hierarchical configuration, at only a fraction of the computation time. 1

Computational Approach to Unravel the Role of Hydrogen Bonding in the Interaction of NAMI-A with DNA Nucleobases and Nucleotides

Density functional theory method in combination with a continuum solvation model is used to understand the role of hydrogen bonding in the interactions of tertiary nitrogen centers of guanine and adenine with monoaqua and diaqua NAMI-A. In the case of adenine, the interaction of N3 with monoaqua NAMI-A is preferred over that of N7 and N1 whereas, N7 site is the most preferred site over N3 and N1 in the diaqua ruthenium-adenine interaction. In the monoaqua and diaqua NAMI-A-guanine interactions, the N7 site is the most preferred site over the N3 site. Here, the strength and number of H-bonds play important roles in stabilizing intermediates and transition states involved in the interaction of NAMI-A and purine bases. Atoms in molecules and Becke surface analysis confirm that the interactions between monoaqua and diaqua NAMI-A with the base pairs of GC and AT dinucleotides leads to the structural deformation in the geometry of the base pairs of dinucleotides. The diaqua NAMI-A adducts induce more disruption in the base pairs as compared to monoaqua NAMI- A adducts. which suggests that diaqua NAMI-A could be a better anticancer agent than monoaqua NAMI-A. This study can be extended to envisage the potential applications of computational studies in the development of new drugs and targeted drug delivery systems

Centralized run-time resource management in a network-on-chip containing reconfigurable hardware tiles

Run-time management of both communication and computation resources in a heterogeneous Network-on-Chip (NoC) is a challenging task. First, platform resources need to be assigned in a fast and efficient way. Secondly, the resources might need to be reallocated when platform conditions or user requirements change. We developed a run-time resource management scheme that is able to efficiently manage a NoC containing fine grain reconfigurable hardware tiles. This paper details our task assignment heuristic and two run-time task migration mechanisms that deal with the message consistency problem in a NoC. We show that specific reconfigurable hardware tile support improves performance of the heuristic and that task migration mechanisms need to be tailored to on-chip networks. 1

Design Space Exploration for Run-time Management of a Reconfigurable System for Video Streaming

This Chapter reports a case study of Design Space Exploration for supporting Run-time Resource Management (RRM). In particular the management of system resources for an MPSoC dedicated to multiple MPEG4 encoding is addressed in the context of an Automotive Cognitive Safety System (ACSS). The run-time management problem is defined as the minimization of the platform power consumption under resource and Quality of Service (QoS) constraints. The Chapter provides an insight of both, design-time and run-time aspects of the problem. During the prelimiary design-time Design Space Exploration (DSE) phase, the best configurations of run-time tunable parameters are statically identified for providing the best trade-offs in terms of run-time costs and application QoS. To speed up the optimization process without reducing the quality of final results, a multi-simulator framework is used for modeling platform performance. At run-time, the RRM exploits the design-time DSE results for deciding an operating configuration to be loaded for each MPEG4 encoder. This operation is carried out dynamically, by following the QoS requirements of the specific use-case

Machine Learning-Enabled Predictions of Condensed Fukui Functions and Designing of Metal Pincer Complexes for Catalytic Hydrogenation of CO₂

This research showcases the machine learning (ML)-enabled homogeneous catalyst discovery to be employed in carbon dioxide hydrogenation. To achieve the desired turnover frequency (TOF), the electrophilicity of the central metal atom is a crucial factor in transition metal pincer complexes. The condensed Fukui function is a direct measure of the catalytic performance of these pincer complexes. Herein, we demonstrate that machine learning is a convenient and effiecient method to calculate condensed Fukui functions of the central metal atom. The electrophilicity values of 202 pincer complexes were calculated by using density functional theory (DFT) to train the ML model. The test data of the experimentally established pincer complexes show a direct linkage between calculated electrophilicity and experimental TOF. Further, this data was used to develop an ML protocol to screen 2,84,062 catalyst complexes to get the electrophilicity values of the Mn, Fe, Co, and Ni transition metals encompassing various permutation combinations of PNP, PNN, NNN, and PCP pincer ligands. These findings validate the efficacy of machine learning in the rapid screening of metal pincer catalysts based on condensed Fukui functions