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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Genetic algorithm applied to the optimization of quantum cascade lasers with second harmonic generation

A computational model for the optimization of the second order optical nonlinearities in GaInAs/AlInAs quantum cascade laser structures is presented. The set of structure parameters that lead to improved device performance was obtained through the implementation of the Genetic Algorithm. In the following step, the linear and second harmonic generation power were calculated by self-consistently solving the system of rate equations for carriers and photons. This rate equation system included both stimulated and simultaneous double photon absorption processes that occur between the levels relevant for second harmonic generation, and material-dependent effective mass, as well as band nonparabolicity, were taken into account. The developed method is general, in the sense that it can be applied to any higher order effect, which requires the photon density equation to be included. Specifically, we have addressed the optimization of the active region of a double quantum well In{sub 0.53}Ga{sub 0.47}As/Al{sub 0.48}In{sub 0.52}As structure and presented its output characteristics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

Genetically designed L3 photonic crystal nanocavities with measured quality factor exceeding one million

We report on the experimental realization of ultra-high quality factor (Q) designs of the L3-type photonic crystal nanocavity. Based on genetic optimization of the positions of few nearby holes, our design drastically improves the performance of the conventional L3 as experimentally confirmed by direct measurement of Q ≃ 2 × 10{sup 6} in a silicon-based photonic crystal membrane. Our devices rank among the highest Q/V ratios ever reported in photonic crystal cavities, holding great promise for the realization of integrated photonic platforms based on ultra-high-Q resonators.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2014

A genetic algorithm for first principles global structure optimization of supported nano structures

We present a newly developed publicly available genetic algorithm (GA) for global structure optimisation within atomic scale modeling. The GA is focused on optimizations using first principles calculations, but it works equally well with empirical potentials. The implementation is described and benchmarked through a detailed statistical analysis employing averages across many independent runs of the GA. This analysis focuses on the practical use of GA’s with a description of optimal parameters to use. New results for the adsorption of M{sub 8} clusters (M = Ru, Rh, Pd, Ag, Pt, Au) on the stoichiometric rutile TiO{sub 2}(110) surface are presented showing the power of automated structure prediction and highlighting the diversity of metal cluster geometries at the atomic scale.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Quantum dot ternary-valued full-adder: Logic synthesis by a multiobjective design optimization based on a genetic algorithm

A methodology is proposed for designing a low-energy consuming ternary-valued full adder based on a quantum dot (QD) electrostatically coupled with a single electron transistor operating as a charge sensor. The methodology is based on design optimization: the values of the physical parameters of the system required for implementing the logic operations are optimized using a multiobjective genetic algorithm. The searching space is determined by elements of the capacitance matrix describing the electrostatic couplings in the entire device. The objective functions are defined as the maximal absolute error over actual device logic outputs relative to the ideal truth tables for the sum and the carry-out in base 3. The logic units are implemented on the same device: a single dual-gate quantum dot and a charge sensor. Their physical parameters are optimized to compute either the sum or the carry out outputs and are compatible with current experimental capabilities. The outputs are encoded in the value of the electric current passing through the charge sensor, while the logic inputs are supplied by the voltage levels on the two gate electrodes attached to the QD. The complex logic ternary operations are directly implemented on an extremely simple device, characterized by small sizes and low-energy consumption compared to devices based on switching single-electron transistors. The design methodology is general and provides a rational approach for realizing non-switching logic operations on QD devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Weight optimization of large span steel truss structures with genetic algorithm

The paper presents the weight optimization process of the main steel truss that supports the Slatina Sport Hall roof. The structure was loaded with self-weight, dead loads, live loads, snow, wind and temperature, grouped in eleven load cases. The optimization of the structure was made using genetic algorithms implemented in a Matlab code. A total number of four different cases were taken into consideration when trying to determine the lowest weight of the structure, depending on the types of connections with the concrete structure ( types of supports, bearing modes), and the possibility of the lower truss chord nodes to change their vertical position. A number of restrictions for tension, maximum displacement and buckling were enforced on the elements, and the cross sections are chosen by the program from a user data base. The results in each of the four cases were analyzed in terms of weight, element tension, element section and displacement. The paper presents the optimization process and the conclusions drawn.

42 ENGINEERING↗
DOE OSTI2015

Parameterization of interatomic potential by genetic algorithms: A case study

A framework for Genetic Algorithm based methodology is developed to systematically obtain and optimize parameters for interatomic force field functions for MD simulations by fitting to a reference data base. This methodology is applied to the fitting of ThO{sub 2} (CaF{sub 2} prototype) – a representative of ceramic based potential fuel for nuclear applications. The resulting GA optimized parameterization of ThO{sub 2} is able to capture basic structural, mechanical, thermo-physical properties and also describes defect structures within the permissible range.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Simultaneous parameter optimization of x-ray and neutron reflectivity data using genetic algorithms

X-ray and neutron reflectivity are two non destructive techniques which provide a wealth of information on thickness, structure and interracial properties in nanometer length scale. Combination of X-ray and neutron reflectivity is well suited for obtaining physical parameters of nanostructured thin films and superlattices. Neutrons provide a different contrast between the elements than X-rays and are also sensitive to the magnetization depth profile in thin films and superlattices. The real space information is extracted by fitting a model for the structure of the thin film sample in reflectometry experiments. We have applied a Genetic Algorithms technique to extract depth dependent structure and magnetic in thin film and multilayer systems by simultaneously fitting X-ray and neutron reflectivity data.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2018

Structures and magnetic properties of iron silicide from adaptive genetic algorithm and first-principles calculations

We performed a systematic search for low-energy structures of binary iron silicide over a wide range of compositions using the crystal structure prediction method based on adaptive genetic algorithm. 36 structures with formation energies within 50 meV/atom (11 of them are within 20 meV) above the convex hull formed by experimentally known stable structures are predicted. Magnetic properties of these low-energy structures are investigated. Some of these structures can be promising candidates for rare-earth-free permanent magnet.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Theoretical search for possible Li–Ni–B crystal structures using an adaptive genetic algorithm

The structural diversity of rare-earth and transition metal borides indicates that alkali-transition metal borides (A-T-B) show tremendous promise in exhibiting a variety of crystal structures with different dimensionalities of T-B frameworks. On the other hand, the A-T-B ternary systems are severely underexplored because of the synthetic challenges associated with their preparation. Accurate and efficient computational predictions of low-energy stable and metastable phases can identify the optimal compositions of the hypothetical compounds in the A-T-B systems to guide the synthesis. As such, in this work, we have computationally discovered several new phases in the Li–Ni–B ternary system. The newly discovered LiNiB, Li 2 Ni 3 B, and Li 2 NiB phases expand the existing theoretical database, and the convex-hull surface of Li–Ni–B has been re-constructed. The lowest energy structure of the LiNiB compound has been found by an adaptive genetic algorithm with layered motif, which matches with the experimentally determined structure. According to our electrochemical calculations, LiNiB and another predicted layered Li 2 NiB compounds have great potential as anode materials for lithium batteries. The Li 2 Ni 3 B compound with the space group P4 3 32 was predicted to crystallize in a cubic structure composed of distorted octahedral units of BNi 6 , which is isostructural to two noncentrosymmetric superconductors Li 2 Pd 3 B and Li 2 Pt 3 B. While we were unable to experimentally confirm the Li 2 Ni 3 B compound utilizing the hydride synthetic route, attempts to synthesize this compound by alternate methods remain highly desirable, considering its potential superconducting properties.

36 MATERIALS SCIENCE↗
DOE OSTI2020

An ultra-incompressible Mn3N compound predicted by first-principles genetic algorithm

Using genetic algorithms for an unbiased structure search and first-principles total-energy calculations, a stable manganese nitride, Mn3N, is discovered. Mn3N is a nonmagnetic metal and isostructural to superhard Re3N. Mn3N exhibits a large bulk modulus and incompressibility comparable to that of the ultra-incompressible OsB. We show that the large bulk modulus can be attributed to the strong covalent bonding in this system. Phonon calculations and analysis confirm the dynamical stability of the Mn3N compound. We also show that weak electron–phonon coupling leads to a small superconducting transition temperature for Mn3N.

Zhang, Chao (ORCID:0000000259572287)↗
DOE OSTI2020

A genetic algorithm approach for reconstructing spectral content from filtered x-ray diode array spectrometers

Filtered diode array spectrometers are routinely employed to infer the temporal evolution of spectral power from x-ray sources, but uniquely extracting spectral content from a finite set of broad, spectrally overlapping channel spectral sensitivities is decidedly nontrivial in these under-determined systems. Here, we present the use of genetic algorithms to reconstruct a probabilistic spectral intensity distribution and compare to the traditional approach most commonly found in the literature. Unlike many of the previously published models, spectral reconstructions from this approach are neither limited by basis functional forms nor do they require a priori spectral knowledge. While the original intent of such measurements was to diagnose the temporal evolution of spectral power from quasi-blackbody radiation sources—where the exact details of spectral content were not thought to be crucial—we demonstrate that this new technique can greatly enhance the utility of the diagnostic by providing more physical spectra and improved robustness to hardware configuration for even strongly non-Planckian distributions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Genetic algorithm-based geometry calibration for dynamic compression x-ray diffraction experiments

An important component of dynamic compression x-ray diffraction (XRD) experiment analysis is geometry calibration: proper data interpretation requires knowledge of the precise detector position and orientation and, if the experiment involves a single-crystal sample, knowledge of the lattice orientation. The determination of these parameters in the arbitrary three-dimensional (3D) scattering geometries often present in dynamic compression facilities is challenging, as the associated optimization problem can be highly nonlinear, nonsmooth, and discontinuous. We present a genetic algorithm-based approach for performing dynamic compression XRD calibrations that overcomes these obstacles. We provide details regarding the image processing, algorithm implementation, and open-source software deployment and demonstrate the capability of the approach to calibrate the detector and crystal parameters in 3D geometries. Notably, we demonstrate the solver’s capacity to find the crystal orientation without a priori rotation constraints.

Brown, Nathan P. [Sandia National Laboratories (SN↗
DOE OSTI2015

Modelling of radiative transfer by the Monte Carlo method and solving the inverse problem based on a genetic algorithm according to experimental results of aerosol sensing on short paths using a femtosecond laser source

We consider the algorithms that implement a broadband ('multiwave') radiative transfer with allowance for multiple (aerosol) scattering and absorption by main atmospheric gases. In the spectral range of 0.6 – 1 μm, a closed numerical simulation of modifications of the supercontinuum component of a probing femtosecond pulse is performed. In the framework of the algorithms for solving the inverse atmospheric-optics problems with the help of a genetic algorithm, we give an interpretation of the experimental backscattered spectrum of the supercontinuum. An adequate reconstruction of the distribution mode for the particles of artificial aerosol with the narrow-modal distributions in a size range of 0.5 – 2 mm and a step of 0.5 mm is obtained. (light scattering)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Genetically encoded sensors of protein hydrodynamics and molecular proximity

Significance The lumazine binding protein (LUMP) emits a cyan-colored fluorescence and has the longest average fluorescence lifetime of any genetically encoded fluorescent protein complex. Coupled with a small mass of 20 kDa, LUMP and its fusion with capture sequences are exploited as unique sensors of protein hydrodynamics and are shown to enable quantitative fluorescence anisotropy imaging of specific target proteins in vitro and in vivo. Moreover, the surface location of the lumazine probe is shown to improve the efficiency of Förster resonance energy transfer (FRET) with the Venus acceptor protein compared with CFP, which is used in the development of a new class of FRET-based sensor.

Hoepker, Alexander C.↗
DOE OSTI2015

Exploring the potential impact of an expanded genetic code on protein function

Significance We describe a general strategy that begins to allow us to address the question of whether an expanded genetic code provides an evolutionary advantage to an organism. A large library of β-lactamase variants with distinct noncanonical amino acids substituted randomly at single sites throughout the protein was generated and then subjected to an antibiotic growth-based screen to identify mutants with enhanced catalytic activity. We show that a unique noncanonical mutation in the enzyme β-lactamase significantly increases catalytic activity by unexpected mechanisms. These effects cannot be recapitulated by other canonical amino acids at this site, suggesting that an expanded set of building blocks beyond the canonical 20 may offer unique solutions to organisms in the evolution of new functions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Genetically encoded sensors enable real-time observation of metabolite production

Advances in biotechnology are enabling engineers to harness natural processes for the production of valuable new chemicals and materials. Cells engineered for chemical production act as renewable factories and redefine what is possible in industries as diverse as manufacturing, pharmaceuticals, and energy. Despite this potential, long and uncertain timelines for biobased product development hinder progress. Engineering cells for chemical production is challenging because the complexity of biology necessitates many attempted designs before an optimal combination of genetic elements or culture conditions is discovered. In this work, we develop a framework that allows design evaluation to be performed with fluorescence such that microbial chemical production can be monitored in real time without the need for sample preparation or laborious analytical techniques.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Age of Jupiter inferred from the distinct genetics and formation times of meteorites

The age of Jupiter, the largest planet in our Solar System, is still unknown. Gas-giant planet formation likely involved the growth of large solid cores, followed by the accumulation of gas onto these cores. Thus, the gas-giant cores must have formed before dissipation of the solar nebula, which likely occurred within less than 10 My after Solar System formation. Although such rapid accretion of the gas-giant cores has successfully been modeled, until now it has not been possible to date their formation. Here, using molybdenum and tungsten isotope measurements on iron meteorites, we demonstrate that meteorites derive from two genetically distinct nebular reservoirs that coexisted and remained spatially separated between ~1 My and ~3–4 My after Solar System formation. The most plausible mechanism for this efficient separation is the formation of Jupiter, opening a gap in the disk and preventing the exchange of material between the two reservoirs. As such, our results indicate that Jupiter’s core grew to ~20 Earth masses within <1 My, followed by a more protracted growth to ~50 Earth masses until at least ~3–4 My after Solar System formation. Furthermore, Jupiter is the oldest planet of the Solar System, and its solid core formed well before the solar nebula gas dissipated, consistent with the core accretion model for giant planet formation.

58 GEOSCIENCES↗
DOE OSTI2025

State-dependent motion of a genetically encoded fluorescent biosensor

Genetically encoded biosensors can measure biochemical properties such as small-molecule concentrations with single-cell resolution, even in vivo. Despite their utility, these sensors are “black boxes”: Very little is known about the structures of their low- and high-fluorescence states or what features are required to transition between them. We used LiLac, a lactate biosensor with a quantitative fluorescence-lifetime readout, as a model system to address these questions. X-ray crystal structures and engineered high-affinity metal bridges demonstrate that LiLac exhibits a large interdomain twist motion that pulls the fluorescent protein away from a “sealed,” high-lifetime state in the absence of lactate to a “cracked,” low-lifetime state in its presence. Understanding the structures and dynamics of LiLac will help to think about and engineer other fluorescent biosensors.

Rosen, Paul C. (ORCID:000000017414454X)↗