Selective laser melting is a powder-based, additive-manufacturing process where a threedimensional part is produced, layer by layer, by using a high-energy laser beam to fuse the metallic powder particles. A particular challenge in this process is the selection of appropriate process parameters that result in parts with desired properties. In this study, we describe an approach to selecting parameters for high density (>99%) parts using 316L stainless steel. Though there has been significant success in achieving near-full density for 316L parts, this work has been limited to laser powers <225W. We discuss how we can exploit prior knowledge, design of computational experiments using a simple model of laser melting, and single-track experiments to determine the process parameters for use at laser powers up to 400W. Our results show that, at higher power values, there is a large range of scan speeds over which the relative density remains >99%, with the density reducing rapidly at high speeds due to insufficient melting, and less rapidly at low speeds due to the effect of voids created as the process enters keyhole mode.

Conspectus Although advances in computer hardware and algorithms tuned for novel computer architectures are leading to significant increases in the size and time scale for molecular simulations, it remains true that new methods and algorithms will be needed to address some of the problems in complex chemical systems, such as electrochemistry, excitation energy transport, proton transport, and condensed phase reactivity. Ideally, these new methods would exploit the strengths of emerging architectures. Fragment based approaches for electronic structure theory decompose the problem of solving the electronic Schrodinger equation into a series of much smaller problems. Because each of these smaller problems is largely independent, this strategy is particularly well-suited to parallel architectures. It appears that the most significant advances in computer architectures will be toward increased parallelism, and therefore fragment-based approaches are an ideal match to these trends. When the computational effort involved scales with the third (or higher) power of the molecular size, there is a large benefit to fragment-based approaches even on serial architectures. This is the case for many of the well-known methods for solving the electronic structure theory problem, especially when wave function-based approaches including electron correlation are considered. A major issue in fragment-based approaches is determining or improving their accuracy. Since the Achilles' heel of any such method lies in the approximations used to stitch the smaller problems back together (i.e., in the treatment of the cross-fragment interactions), it can often be important to ensure that the size of the smaller problems is "large enough." Thus, there are two frontiers that need to be extended in order to enable molecular simulations for large systems and long times: the strongly coupled problem of medium sized molecules (100-500 atoms) and the more weakly coupled problem of decomposing ("fragmenting") a molecular system and then stitching it back together. In this Account, we address both of these problems, the first by using graphical processing units (GPUs) and electronic structure algorithms tuned for these architectures and the second by using an exciton model as a framework in which to stitch together the solutions of the smaller problems. The multitiered parallel framework outlined here is aimed at nonadiabatic dynamics simulations on large supramolecular multichromophoric complexes in full atomistic detail. In this framework, the lowest tier of parallelism involves GPU-accelerated electronic structure theory calculations, for which we summarize recent progress in parallelizing the computation and use of electron repulsion integrals (ERIs), which are the major computational bottleneck in both density functional theory (DFT) and time-dependent density functional theory (TDDFT). The topmost tier of parallelism relies on a distributed memory framework, in which we build an exciton model that couples chromophoric units. Combining these multi...

We recently outlined an efficient multi-tiered parallel ab initio excitonic framework that utilizes time dependent density functional theory (TDDFT) to calculate ground and excited state energies and gradients of large supramolecular complexes in atomistic detail - enabling us to undertake non-adiabatic simulations which explicitly account for the coupled anharmonic vibrational motion of all the constituent atoms in a supramolecular system. Here we apply that framework to the 27 coupled bacterio-chlorophyll-a chromophores which make up the LH2 complex, using it to compute an on-the-fly nonadiabatic surface-hopping (SH) trajectory of electronically excited LH2. Part one of this article is focussed on calibrating our ab initio exciton Hamiltonian using two key parameters: a shift δ, which corrects for the error in TDDFT vertical excitation energies; and an effective dielectric constant ε, which describes the average screening of the transition-dipole coupling between chromophores. Using snapshots obtained from equilibrium molecular dynamics simulations (MD) of LH2, we tune the values of both δ and ε through fitting to the thermally broadened experimental absorption spectrum, giving a linear absorption spectrum that agrees reasonably well with experiment. In part two of this article, we construct a time-resolved picture of the coupled vibrational and excitation energy transfer (EET) dynamics in the sub-picosecond regime following photo-excitation. Assuming Franck-Condon excitation of a narrow eigenstate band centred at 800 nm, we use surface hopping to follow a single nonadiabatic dynamics trajectory within the full eigenstate manifold. Consistent with experimental data, this trajectory gives timescales for B800→B850 population transfer (τ) between 650-1050 fs, and B800 population decay (τ) between 10-50 fs. The dynamical picture that emerges is one of rapidly fluctuating LH2 eigenstates that are delocalized over multiple chromophores and undergo frequent crossing on a femtosecond timescale as a result of the atomic vibrations of the constituent chromophores. The eigenstate fluctuations arise from disorder that is driven by vibrational dynamics with multiple characteristic timescales. The scalability of our ab initio excitonic computational framework across massively parallel architectures opens up the possibility of addressing a wide range of questions, including how specific dynamical motions impact both the pathways and efficiency of electronic energy-transfer within large supramolecular systems.

The full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. AbstractThe ultrafast decay dynamics of 4-(N,N-dimethylamino)benzonitrile (DMABN) following photoexcitation was studied with the ab initio multiple spawning (AIMS) method, combined with GPU-accelerated linear-response time-dependent density functional theory (LR-TDDFT). We validate the LR-TDDFT method for this case and then present a detailed analysis of the first ≈200 fs of DMABN excited-state dynamics. Almost complete nonadiabatic population transfer from S 2 (the initially populated bright state) to S 1 takes place in less than 50 fs, without significant torsion of the dimethylamino (DMA) group.Significant torsion of the DMA group is only observed after the nuclear wavepacket reaches S 1 and acquires locally-excited electronic character. Our results show that torsion of the DMA group is not prerequisite for nonadiabatic transitions in DMABN, although such motion is indeed relevant on the lowest excited state (S 1 ).Curchod, et al. -DMABN -Page 2

Selective laser melting is a powder-based, additive-manufacturing process where a threedimensional part is produced, layer by layer, by using a high-energy laser beam to fuse the metallic powder particles. A particular challenge in this process is the selection of appropriate process parameters that result in parts with desired properties. In this study, we describe an approach to selecting parameters for high density (>99%) parts using 316L stainless steel. Though there has been significant success in achieving near-full density for 316L parts, this work has been limited to laser powers <225W. We discuss how we can exploit prior knowledge, design of computational experiments using a simple model of laser melting, and single-track experiments to determine the process parameters for use at laser powers up to 400W. Our results show that, at higher power values, there is a large range of scan speeds over which the relative density remains >99%, with the density reducing rapidly at high speeds due to insufficient melting, and less rapidly at low speeds due to the effect of voids created as the process enters keyhole mode.

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Over the past two years, key issues associated with the development of realistic metal hydride storage systems have been identified and studied at Purdue University’s Hydrogen Systems Laboratory, part of the Energy Center at Discovery Park. Ongoing research projects are aimed at the demonstration of a prototype large-scale metal hydride tank that achieves fill and release rates compatible with current automotive use. The large-scale storage system is a prototype with multiple pressure vessels compatible with 350 bar operation. Tests are conducted at the Hydrogen Systems Lab in a 1000 ft2 laboratory space comprised of two test cells and a control room that has been upgraded for hydrogen service compatibility. The infrastructure and associated data acquisition and control systems allow for remote testing with several kilograms of high-pressure reversible metal hydride powder. Managing the large amount of heat generated during hydrogen loading directly affects the refueling time. However, the thermal management of hydride systems is problematic because of the low thermal conductivity of the metal hydrides (∼ 1 W/m-K). Current efforts are aimed at optimizing the filling-dependent thermal performance of the metal hydride storage system to minimize the refueling time of a practical system. Combined heat conduction within the metal hydride and the enhancing material particles, across the contacts of particles and within the hydrogen gas between non-contacted particles plays a critical role in dissipating heat to sustain high reaction rates during refueling. Methods to increase the effective thermal conductivity of metal hydride powders include using additives with substantially higher thermal conductivity such as aluminum, graphite, metal foams and carbon nanotubes. This paper presents the results of experimental studies in which various thermal enhancement materials are added to the metal hydride powder in an effort to maximize the effective thermal conductivity of the test bed. The size, aspect ratio, and intrinsic thermal conductivity of the enhancement materials are taken into account to adapt heat conduction models through composite nanoporous media. Thermal conductivity and density of the composite materials are measured and enhancement metrics are calculated to rate performance of composites. Experimental results of the hydriding process of thermally enhanced metal hydride powder are compared to un-enhanced metal hydride powder and to model predictions. The development of the Hydrogen Systems Laboratory is also discussed in light of the lessons learned in managing large quantities of metal hydride and high pressure hydrogen gas.

Recent advances in nanofabrication technology have facilitated the development of arrays of nanostructures in the classical or quantum confinement regime, e.g., single-walled carbon nanotube (SWCNT) arrays with long-range order across macroscopic dimensions. So far, an accurate generalized method of modeling radiative properties of these systems has yet to be realized. In this work, a multiscale computational approach combining first-principles methods based on density functional theory (DFT) and classical electrodynamics simulations based on the finite element method (FEM) is described and applied to the calculations of optical properties of macroscopic SWCNT arrays. The first-principles approach includes the use of the GW approximation and Bethe–Salpeter methods to account for excited electron states, and the accuracy of these approximations is assessed through evaluation of the absorption spectra of individual SWCNTs. The fundamental mechanisms for the unique characteristics of extremely low reflectance and high absorptance in the near-IR are delineated. Furthermore, opportunities to tune the optical properties of the macroscopic array are explored.