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Experimental quantum chemistry and chemical reactivity (Chapter 17)
No full textThis chapter describes a framework for chemical bonding analysis called Experimental Quantum Chemistry (EQC). In EQC, energies of atoms and molecules are partitioning into terms that can be both quantum mechanically calculated and experimentally estimated. EQC is here argued to be a conceptual bridge between Molecular Orbital (MO) theory and the general idea of Energy Decomposition Analysis (EDA), as well as quantum chemical topology-based techniques. The EQC framework allows for the design of descriptors useful for distinguishing bonds and for predicting chemical reactivity. The average electron energy is an example of a central component of EQC. This descriptor of electronic structure can be analyzed over subsets of electronic levels, as these vary over chemical reactions, and as spatially resolved over molecules. Electronegativity is in EQC defined as the average binding energy of valence electrons, which has allowed the extension of that central chemical concept to conditions of high pressure
Towards joint communication and sensing (Chapter 4)
Get PDFLocalization of user equipment (UE) in mobile communication networks has been supported from the early stages of 3rd generation partnership project (3GPP). With 5th Generation (5G) and its target use cases, localization is increasingly gaining importance. Integrated sensing and localization in 6th Generation (6G) networks promise the introduction of more efficient networks and compelling applications to be developed
Scalable Computation of Dynamic Flow Problems via Multimarginal Graph-Structured Optimal Transport
No full textIn this work, we develop a new framework for dynamic network flow pro-blems based on optimal transport theory. We show that the dynamic multicommodity minimum-cost network flow problem can be formulated as a multimarginal optimal transport problem, where the cost function and the constraints on the marginals are asso-ciated with a graph structure. By exploiting these structures and building on recent advances in optimal transport theory, we develop an efficient method for such entropy -regularized optimal transport problems. In particular, the graph structure is utilized to efficiently compute the projections needed in the corresponding Sinkhorn iterations, and we arrive at a scheme that is both highly computationally efficient and easy to implement. To illustrate the performance of our algorithm, we compare it with a state-of-the-art linear programming (LP) solver. We achieve good approximations to the solution at least one order of magnitude faster than the LP solver. Finally, we showcase the methodology on a traffic routing problem with a large number of commodities
Quaternion Variational Integration for Inertial Maneuvering in a Biomimetic Unmanned Aerial Vehicle
No full textBiological flying, gliding, and falling creatures are capable of extraordinary forms of inertial maneuvering: free-space maneuvering based on fine control of their multibody dynamics, as typified by the self-righting reflexes of cats. However, designing inertial maneuvering capability into biomimetic robots, such as biomimetic unmanned aerial vehicles (UAVs), is challenging. Accurately simulating this maneuvering requires numerical integrators that can ensure both singularity-free integration, and momentum and energy conservation, in a strongly coupled system—properties unavailable in existing conventional integrators. In this work, we develop a pair of novel quaternion variational integrators (QVIs) showing these properties, and demonstrate their capability for simulating inertial maneuvering in a biomimetic UAV showing complex multibody dynamics coupling. Being quaternion-valued, these QVIs are innately singularity-free; and being variational, they can show excellent energy and momentum conservation properties. We explore the effect of variational integration order (left-rectangle versus midpoint) on the conservation properties of integrator, and conclude that in complex coupled systems in which canonical momenta may be time-varying, the midpoint integrator is required. The resulting midpoint QVI is well suited to the analysis of inertial maneuvering in a biomimetic UAV—a feature that we demonstrate in simulation—and of other complex dynamical systems
Three-dimensional reconstruction and computational analysis of a structural battery composite electrolyte
Get PDFStructural batteries are multifunctional composite materials that can carry mechanical load and store electrical energy. Their multifunctionality requires an ionically conductive and stiff electrolyte matrix material. For this purpose, a bi-continuous polymer electrolyte is used where a porous solid phase holds the structural integrity of the system, and a liquid phase, which occupies the pores, conducts lithium ions. To assess the porous structure, three-dimensional topology information is needed. Here we study the three-dimensional structure of the porous battery electrolyte material using combined focused ion beam and scanning electron microscopy and transfer into finite element models. Numerical analyses provide predictions of elastic modulus and ionic conductivity of the bi-continuous electrolyte material. Characterization of the three-dimensional structure also provides information on the diameter and volume distributions of the polymer and pores, as well as geodesic tortuosity
Rail machining - current practices and potential for optimisation
Get PDFCurrent practices on rail machining show large variations in strategies and amount of grinding and milling. To identify reasons for this and suggest strategies to further optimise rail machining, objectives of machining are scrutinised and consequences of not fulfilling objectives are investigated. This leads to a discussion on potentially detrimental effects of rail machining and how to minimise these. With this background, general aspects of rail machining optimisation are discussed. The study shows several means to improve rail machining, but also how the potential is restricted by the current lack of knowledge and predictive models. This prevents quantifying benefits of innovative solutions, and complicates transfer of knowledge between different operational conditions and translations of (scaled and controlled) test results to (full-scale, uncontrolled) operational conditions
Nonlinear semigroups for nonlocal conservation laws
Get PDFWe investigate a class of nonlocal conservation laws in several space dimensions, where the continuum average of weighted nonlocal interactions are considered over a finite horizon. We establish well-posedness for a broad class of flux functions and initial data via semigroup theory in Banach spaces and, in particular, via the celebrated Crandall–Liggett Theorem. We also show that the unique mild solution satisfies a Kružkov-type nonlocal entropy inequality. Similarly to the local case, we demonstrate an efficient way of proving various desirable qualitative properties of the unique solution
Evaluation of full-face, open-face, and airbag-equipped helmets for facial impact protection
No full textObjective: Two-wheeler riders frequently sustain injuries to the head and face in real-world crashes, including traumatic brain injury, basilar skull fracture, and facial fracture. Different types of helmets exist today, which are recognized as preventing head injuries in general; however, their efficacy and limitations in facial impact protection are underexplored. Biofidelic surrogate test devices and assessment criteria are lacking in current helmet standards. This study addresses these gaps by applying a new, more biofidelic test method to evaluate conventional full-face helmets and a novel airbag-equipped helmet design. Ultimately, this study aims to contribute to better helmet design and testing standards. Methods: Facial impact tests at two locations, mid-face and lower face, were conducted with a complete THOR dummy. Forces applied to the face and at the junction of the head and neck were measured. Brain strain was predicted by a finite element head model taking both linear and rotational head kinematics as input. Four helmet types were evaluated: full-face motorcycle and bike helmets, a novel design called a face airbag (an inflatable structure integrated into an open-face motorcycle helmet), and an open-face motorcycle helmet. The unpaired, two-sided student\u27s t-test was performed between the open-face helmet and the others, which featured face-protective designs. Results: A substantial reduction in brain strain and facial forces was found with the full-face motorcycle helmet and face airbag. Upper neck tensile forces increased slightly with both full-face motorcycle (14.4%, p >.05) and bike helmets (21.7%, p =.039). The full-face bike helmet reduced the brain strain and facial forces for lower-face impacts, but not for mid-face impacts. The motorcycle helmet reduced mid-face impact forces while slightly increasing forces in the lower face. Significance of results: The chin guards of full-face helmets and the face airbag protect by reducing facial load and brain strain for lower face impact; however, the full-face helmets’ influence on neck tension and increased risk for basilar skull fracture need further investigation. The motorcycle helmet\u27s visor re-directed mid-face impact forces to the forehead and lower face via the helmet\u27s upper rim and chin guard: a thus-far undescribed protective mechanism. Given the significance of the visor for facial protection, an impact test procedure should be included in helmet standards, and the use of helmet visors promoted. A simplified, yet biofidelic, facial impact test method should be included in future helmet standards to ensure a minimum level of protection performance
Bulk-Processed Plasmonic Plastic Nanocomposite Materials for Optical Hydrogen Detection
Get PDFConspectus Sensors are ubiquitous, andtheir importanceis only going to increaseacross many areas of modern technology. In this respect, hydrogengas (H-2) sensors are no exception since they allow mitigationof the inherent safety risks associated with mixtures of H-2 and air. The deployment of H-2 technologies is rapidlyaccelerating in emerging energy, transport, and green steel-makingsectors, where not only safety but also process monitoring sensorsare in high demand. To meet this demand, cost-effective and scalableroutes for mass production of sensing materials are required. Here,the state-of-the-art often resorts to processes derived from the microelectronicsindustry where surface-based micro- and nanofabrication are the methodsof choice and where (H-2) sensor manufacturing is no exception. In this Account, we discuss how our recent efforts to develop sensorsbased on plasmonic plastics may complement the current state-of-the-art.We explore a new H-2 sensor paradigm, established througha series of recent publications, that combines (i) the plasmonic opticalH(2) detection principle and (ii) bulk-processed nanocompositematerials. In particular, plasmonic plastic nanocomposite sensingmaterials are described that comprise plasmonic H-2-sensitivecolloidally synthesized nanoparticles dispersed in a polymer matrixand enable the additive manufacturing of H-2 sensors ina cost-effective and scalable way. We first discuss the concept ofplasmonic plastic nanocomposite materials for the additive manufacturingof an active plasmonic sensing material on the basis of the threekey components that require individual and concerted optimization:(i) the plasmonic sensing metal nanoparticles, (ii) the surfactant/stabilizermolecules on the nanoparticle surface from colloidal synthesis, and(iii) the polymer matrix. We then introduce the working principleof plasmonic H-2 detection, which relies on the selectiveabsorption of H species into hydride-forming metal nanoparticles that,in turn, induces distinct changes in their optical plasmonic signaturein proportion to the H-2 concentration in the local atmosphere.Subsequently, we assess the roles of the key components of a plasmonicplastic for H-2 sensing, where we have established that(i) alloying Pd with Au and Cu eliminates hysteresis and introducesintrinsic deactivation resistance at ambient conditions, (ii) surfactant/stabilizermolecules can significantly accelerate and decelerate H-2 sorption and thus sensor response, and (iii) polymer coatings acceleratesensor response, reduce the limit of detection (LoD), and enable molecularfiltering for sensor operation in chemically challenging environments.Based on these insights, we discuss the rational development and detailedcharacterization of bulk-processed plasmonic plastics based on glassyand fluorinated matrix polymers and on tailored flow-chemistry-basedsynthesis of Pd and PdAu alloy colloidal nanoparticles with optimizedstabilizer molecules. In their champion implementation, they enablehighly stable H-2 sensors with response times in the 2 srange and an LoD of few 10 ppm of H-2. To put plasmonicplastics in a wider perspective, we also report their implementationusing different polymer matrix materials that can be used for 3D printingand (an)isotropic Au nanoparticles that enable the manufacturing ofmacroscopic plasmonic objects with, if required, dichroic opticalproperties and in amounts that can be readily upscaled. We advertisethat melt processing of plasmonic plastic nanocomposites is a viableroute toward the realization of plasmonic objects and sensors, producedby scalable colloidal synthesis and additive manufacturing techniques
Precession-induced Variability in AGN Jets and OJ 287
No full textThe combined study of the flaring of active galactic nuclei (AGNs) at radio wavelengths and parsec-scale jet kinematics with Very Long Baseline Interferometry has led to the view that (i) the observed flares are associated with ejections of synchrotron blobs from the core, and (ii) most of the flaring follows a one-to-one correlation with the ejection of the component. Recent results have added to the mounting evidence showing that the quasi-regular component injections into the relativistic jet may not be the only cause of the flux variability. We propose that AGN flux variability and changes in jet morphology can both be of deterministic nature, i.e., having a geometric/kinetic origin linked to the time-variable Doppler beaming of the jet emission as its direction changes due to precession (and nutation). The physics of the underlying jet leads to shocks, instabilities, or ejections of plasmoids. The appearance (morphology, flux, etc.) of the jet can, however, be strongly affected and modulated by precession. We demonstrate this modulating power of precession for OJ 287. For the first time, we show that the spectral state of the spectral energy distribution (SED) can be directly related to the jet’s precession phase. We model the SED evolution and reproduce the precession parameters. Further, we apply our precession model to 11 prominent AGNs. We show that for OJ 287 precession seems to dominate the long-term variability (≳1 yr) of the AGN flux, SED spectral state, and jet morphology, while stochastic processes affect the variability on short timescales (≲0.2 yr)