All Solid-State Mid-IR Laser Development, Nonlinear Absorption Investigation and Laser-Induced Damage Study

In this research, nonlinear optical absorption coefficients and laser-induced damage thresholds are measured in Ge and GaSb, which are materials that are used in IR detectors. Using a simultaneous fitting technique to extract nonlinear absorption coefficients from data at two pulse widths, two-photon and free-carrier absorption coefficients are measured in Ge and GaSb at 2.05 and 2.5 μm for the first time. At these wavelengths, nonlinear absorption is the primary damage mechanism, and damage thresholds at picosecond and nanosecond pulse widths were measured and agreed well with modeled thresholds using experimentally measured parameters. The damage threshold for a single-layer Al2O3 anti-reflective coating on Ge was 55% or 35% lower than the uncoated threshold for picosecond or nanosecond pulses, respectively. It was necessary to develop a pulsed 2.5 μm wavelength laser to conduct these measurements, as prior lasers at this wavelength possessed insufficient pulse energy to induce nonlinear absorption or damage these materials. Using a Cr2+:ZnSe gain medium, a 3.1 mJ pulse energy laser was created whose peak power exceeded all Cr2+:ZnSe literature by a factor of eight. The characteristics of the laser include nanosecond pulse width, 52% slope efficiency, beam quality of M2 = 1.4, Gaussian spatial profile and a spectral line width of 110 nm

Cost Analysis of Optimized Islanded Energy Systems in a Dispersed Air Base Conflict

The United States Air Force has implemented a dispersed air base strategy to enhance mission effectiveness for near-peer conflicts. Asset dispersal places many smaller bases across a wide geographic area, which increases resupply requirements and logistical complexity. Hybrid energy systems reduce resupply requirements through sustainable, off-grid energy production. This paper presents a novel hybrid energy renewable delivery system (HERDS) model capable of (1) selecting the optimal hybrid energy system design that meets demand at the lowest net present cost and (2) optimizing the delivery of the selected system using existing Air Force cargo aircraft. The novelty of the model’s capabilities is displayed using Clark Air Base, Philippines as a case study. The HERDS model selected an optimal configuration consisting of a 676-kW photovoltaic array, an 1846-kWh battery system, and a 200-kW generator. This hybrid energy system predicts a 54% reduction in cost and an 88% reduction in fuel usage, as compared to the baseline Air Force system. The HERDS model is expected to support planners in their ongoing efforts to construct cost-effective sites that minimize the transport and logistic requirements associated with remote installations. Additionally, the results of this paper may be appropriate for broader civilian applications

A Sustainable Prototype for Renewable Energy: Optimized Prime-power Generator Solar Array Replacement

Remote locations such as disaster relief camps, isolated arctic communities, and military forward operating bases are disconnected from traditional power grids forcing them to rely on diesel generators with a total installed capacity of 10,000 MW worldwide. The generators require a constant resupply of fuel, resulting in increased operating costs, negative environmental impacts, and challenging fuel logistics. To enhance remote site sustainability, planners can develop stand-alone photovoltaic-battery systems to replace existing prime power generators. This paper presents the development of a novel cost-performance model capable of optimizing solar array and Li-ion battery storage size by generating tradeoffs between minimizing initial system cost and maximizing power reliability. A case study for the replacement of an 800 kW generator, the US Air Force’s standard for prime power at deployed locations, was analyzed to demonstrate the model and its capabilities. A MATLAB model, simulating one year of solar data, was used to generate an optimized solution to minimize initial cost while providing over 99% reliability. Replacing a single diesel generator would result in a savings of 1.9 million liters of fuel, eliminating 100 fuel tanker truck deliveries annually. The distinctive capabilities of this model enable designers to enhance environmental, economic, and operational sustainability of remote locations by creating energy self-sufficient sites, which can operate indefinitely without the need for resupply

Meeting Temporary Facility Energy Demand with Climate-Optimized Off-Grid Energy Systems

Remote and contingency operations, including military and disaster-relief activities, often require the use of temporary facilities powered by inefficient diesel generators that are expensive to operate and maintain. Site planners can reduce operating costs by increasing shelter insulation and augmenting generators with photovoltaic-battery hybrid energy systems, but they must select the optimal design configuration based on the region’s climate to meet the power demand at the lowest cost. To assist planners, this paper proposes an innovative, climate-optimized, hybrid energy system selection model capable of selecting the facility insulation type, solar array size, and battery backup system to minimize the annual operating cost. To demonstrate the model’s capability in various climates, model performance was evaluated for applications in southwest Asia and the Caribbean. For a facility in Southwest Asia, the model reduced fuel consumption by 93% and saved $271 thousand compared to operating a diesel generator. The simulated facility in the Caribbean resulted in more significant savings, decreasing fuel consumption by 92$291 thousand. This capability is expected to support planners of remote sites in their ongoing effort to minimize fuel supply requirements and annual operating costs of temporary facilities

Machine Learning Modeling of Horizontal Photovoltaics Using Weather and Location Data

Solar energy is a key renewable energy source; however, its intermittent nature and potential for use in distributed systems make power prediction an important aspect of grid integration. This research analyzed a variety of machine learning techniques to predict power output for horizontal solar panels using 14 months of data collected from 12 northern-hemisphere locations. We performed our data collection and analysis in the absence of irradiation data—an approach not commonly found in prior literature. Using latitude, month, hour, ambient temperature, pressure, humidity, wind speed, and cloud ceiling as independent variables, a distributed random forest regression algorithm modeled the combined dataset with an R2 value of 0.94. As a comparative measure, other machine learning algorithms resulted in R2 values of 0.50–0.94. Additionally, the data from each location was modeled separately with R2 values ranging from 0.91 to 0.97, indicating a range of consistency across all sites. Using an input variable permutation approach with the random forest algorithm, we found that the three most important variables for power prediction were ambient temperature, humidity, and cloud ceiling. The analysis showed that machine learning potentially allowed for accurate power prediction while avoiding the challenges associated with modeled irradiation data

Tracked Vehicle Physics-based Energy Modelling and Series Hybrid System Optimisation for the Bradley Fighting Vehicle

A hybrid electric tracked ground vehicle (HETGV) can reduce military fuel usage, however a review of current tools determined they are not suitable to estimate HEGTV performance. Based on topographic data and vehicle attributes, this research developed an estimation tool by creating a model to determine tracked vehicle energy and fuel requirements, and using these requirements, created a HEGTV cost and performance optimisation for the Bradley fighting vehicle energy system. The optimised design reduced fuel consumption by 15%, and met the vehicle\u27s peak power requirement of 365 kW, with a recommended configuration of a 135 kW generator and 100 kWh battery, and an estimated drivetrain and fuel cost of $155,000. This analysis concludes by articulating the operational and tactical impacts of increased fuel efficiency

Spintronics: Fundamentals and applications

Spintronics, or spin electronics, involves the study of active control and manipulation of spin degrees of freedom in solid-state systems. This article reviews the current status of this subject, including both recent advances and well-established results. The primary focus is on the basic physical principles underlying the generation of carrier spin polarization, spin dynamics, and spin-polarized transport in semiconductors and metals. Spin transport differs from charge transport in that spin is a nonconserved quantity in solids due to spin-orbit and hyperfine coupling. The authors discuss in detail spin decoherence mechanisms in metals and semiconductors. Various theories of spin injection and spin-polarized transport are applied to hybrid structures relevant to spin-based devices and fundamental studies of materials properties. Experimental work is reviewed with the emphasis on projected applications, in which external electric and magnetic fields and illumination by light will be used to control spin and charge dynamics to create new functionalities not feasible or ineffective with conventional electronics.Comment: invited review, 36 figures, 900+ references; minor stylistic changes from the published versio

Seroprevalence of Toxoplasma gondii infection in arthritis patients in eastern China

Background: There is accumulating evidence for an increased susceptibility to infection in patients with arthritis. We sought to understand the epidemiology of Toxoplasma gondii infection in arthritis patients in eastern China, given the paucity of data on the magnitude of T. gondii infection in these patients. Methods: Seroprevalence of T. gondii infection was assessed by enzyme-linked immunosorbent assay using a crude antigen of the parasite in 820 arthritic patients, and an equal number of healthy controls, from Qingdao and Weihai cities, eastern China. Sociodemographic, clinical and lifestyle information on the study participants were also obtained. Results: The prevalence of anti-T. gondii IgG was significantly higher in arthritic patients (18.8%) compared with 12% in healthy controls (P < 0.001). Twelve patients with arthritis had anti-T. gondii IgM antibodies comparable with 10 control patients (1.5% vs 1.2%). Demographic factors did not significantly influence these seroprevalence frequencies. The highest T. gondii infection seropositivity rate was detected in patients with rheumatoid arthritis (24.8%), followed by reactive arthritis (23.8%), osteoarthritis (19%), infectious arthritis (18.4%) and gouty arthritis (14.8%). Seroprevalence rates of rheumatoid arthritis and reactive arthritis were significantly higher when compared with controls (P < 0.001 and P = 0.002, respectively). A significant association was detected between T. gondii infection and cats being present in the home in arthritic patients (odds ratio [OR], 1.68; 95% confidence interval [CI]: 1.24 – 2.28; P = 0.001). Conclusions: These findings are consistent with and extend previous results, providing further evidence to support a link between contact with cats and an increased risk of T. gondii infection. Our study is also the first to confirm an association between T. gondii infection and arthritis patients in China. Implications for better prevention and control of T. gondii infection in arthritis patients are discussed. Trial registration: This is an epidemiological survey, therefore trial registration was not required

The glial growth factors deficiency and synaptic destabilization hypothesis of schizophrenia

BACKGROUND: A systems approach to understanding the etiology of schizophrenia requires a theory which is able to integrate genetic as well as neurodevelopmental factors. PRESENTATION OF THE HYPOTHESIS: Based on a co-localization of loci approach and a large amount of circumstantial evidence, we here propose that a functional deficiency of glial growth factors and of growth factors produced by glial cells are among the distal causes in the genotype-to-phenotype chain leading to the development of schizophrenia. These factors include neuregulin, insulin-like growth factor I, insulin, epidermal growth factor, neurotrophic growth factors, erbB receptors, phosphatidylinositol-3 kinase, growth arrest specific genes, neuritin, tumor necrosis factor alpha, glutamate, NMDA and cholinergic receptors. A genetically and epigenetically determined low baseline of glial growth factor signaling and synaptic strength is expected to increase the vulnerability for additional reductions (e.g., by viruses such as HHV-6 and JC virus infecting glial cells). This should lead to a weakening of the positive feedback loop between the presynaptic neuron and its targets, and below a certain threshold to synaptic destabilization and schizophrenia. TESTING THE HYPOTHESIS: Supported by informed conjectures and empirical facts, the hypothesis makes an attractive case for a large number of further investigations. IMPLICATIONS OF THE HYPOTHESIS: The hypothesis suggests glial cells as the locus of the genes-environment interactions in schizophrenia, with glial asthenia as an important factor for the genetic liability to the disorder, and an increase of prolactin and/or insulin as possible working mechanisms of traditional and atypical neuroleptic treatments