Widefield quantitative phase imaging by second-harmonic dispersion interferometry
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Infrared spectroscopy is a well-established method for identifying solid, liquid, and gas-phase chemicals. Accurate infrared spectroscopic analysis requires reference libraries where library endmembers reflect all optical phenomena contributing to the observed spectra. Traditional spectral libraries most often contain molecular-based absorption spectra, but these do not account for the complex scattering effects that become significant when measuring aerosols. In this work, we combine the laboratory-derived, wavelength-dependent complex optical vectors ( n / k ) of liquid dioctyl sebacate (DOS) with Mie scattering theory and the Beer–Lambert law to generate synthetic infrared transmission spectra of aerosolized DOS. Additionally, we record experimental infrared transmission spectra using an FTIR spectrometer coupled to a simple aerosol chamber filled with a quantified number size distribution of aerosolized DOS. The modeled and measured spectra show strong agreement, with Mie scattering effects clearly altering the overall spectral shape as well as the positions and profiles of absorption features. The results demonstrate that synthetic spectra generated from n / k values can reliably capture aerosol-specific spectral behavior and thus serve as a foundation for building scalable, physics-based aerosol reference libraries to enable infrared spectroscopic detection of aerosols.
Our basic understanding of carbon cycling in the biosphere remains qualitative and incomplete, precluding our ability to effectively engineer novel solutions to climate change. How can we attempt to engineer the unknown? This challenge has been faced before in plant biology, providing a roadmap to guide future efforts. We use examples from over a century of photosynthesis research to illustrate the key principles that will set future plant engineering on a solid footing, namely, an effort to identify the key control variables, quantify the effects of systematically tuning these variables, and use theory to account for these observations. The main contributions of plant synthetic biology will stem not from delivering desired genotypes but from enabling the kind of predictive understanding necessary to rationally design these genotypes in the first place. Only then will synthetic plant biology be able to live up to its promise.
The COVID-19 pandemic has highlighted a need for better understanding of countries’ vulnerability and resilience to not only pandemics but also disasters, climate change, and other systemic shocks. A comprehensive characterization of vulnerability can inform efforts to improve infrastructure and guide disaster response in the future. In this paper, we propose a data-driven framework for studying countries’ vulnerability and resilience to incident disasters across multiple dimensions of society. To illustrate this methodology, we leverage the rich data landscape surrounding the COVID-19 pandemic to characterize observed resilience for several countries (USA, Brazil, India, Sweden, New Zealand, and Israel) as measured by pandemic impacts across a variety of social, economic, and political domains. We also assess how observed responses and outcomes (i.e., resilience) of the COVID-19 pandemic are associated with pre-pandemic characteristics or vulnerabilities, including (1) prior risk for adverse pandemic outcomes due to population density and age and (2) the systems in place prior to the pandemic that may impact the ability to respond to the crisis, including health infrastructure and economic capacity. Our work demonstrates the importance of viewing vulnerability and resilience in a multi-dimensional way, where a country’s resources and outcomes related to vulnerability and resilience can differ dramatically across economic, political, and social domains. This work also highlights key gaps in our current understanding about vulnerability and resilience and a need for data-driven, context-specific assessments of disaster vulnerability in the future.
Two irradiated AGR-2 TRISO particles were chosen to demonstrate a recently developed mass balance technique in which EPMA-generated concentration data was used to determine fission product mass on a layer-by-layer basis in TRISO particles. EPMA-calculated fission product masses for most fission products in the two particles were within +/- 20% of their ORIGEN-modelled masses. Results show that Sr, Ba, and Eu accumulate preferentially in the carbon-rich kernel periphery on the particles’ side that lacks a gap between the buffer and IPyC. In addition, the more mobile elements--Cs, Sr, and Pd, accumulate in greater quantity in the outer layers of particle AGR2-223-RS34 compared to particle AGR2-223-RS06, which has relatively more of those elements’ mass located in the kernel and kernel periphery, suggesting enhanced fission product transport in particle AGR2-223-RS34. This model can be used better understand and test fission product transport in TRISO particles.
Paper presented at 16th International Conference on Greenhouse Gas Control Technologies (GHGT-16), October 23–27, 2022, Lyon, France. Rock physics is key to understanding the feasibility of monitoring and the actual monitoring of the location and volume of CO 2 in the subsurface. Examples from the Broom Creek Formation of the Williston Basin in North Dakota and the Muddy Formation of the Powder River Basin in Montana and Wyoming are used to show the effect of geology and injection of CO 2 on the velocity and density of reservoir rocks.
Intended for the Web, the technology snapshot provides a short summary, market, benefits, a contact and a few brief snippets on the technology development.
This report presents highlights of these efforts. Section 2 describes work that has been done to compare the performance of proxy applications on AMD MI60 vs. Nvidia V100 GPUs. So far only a small set of ECP proxies are running on AMD GPUs, but we will continue to expand this analysis as additional proxies become available. We find that although the MI60 and V100 have nearly the same measured memory bandwidth, memory bound proxy app kernels perform 20-30% worse on the MI60. Further work is needed to refine these comparisons to determine whether the root cause is due to differences in the hardware, software stack, platform specific optimization, or some combination of the three. Section 3 describes our continuing effort to find methods to accurately assess the similarity of proxies and parents. We have recently seen very encouraging results using a cosine similarity metric. This technique uses the angle between two vectors of hardware performance counters to characterize the similarity (or difference) between two applications or proxies. We show not only that several widely used proxies are highly similar to their parents, but also that they differ from non-related codes. We also show that cosine similarity can be used to identify gaps and redundancies in suites and even to gain insight into the effects of architectural differences between platforms. Our work on assessing the Exascale toolchain is ongoing. Our successes with performance measurement tools are evident from the data provided in this report. However, our assessments across the broader tool chain are still too incomplete to provide a meaningful report at this time. We will continue to assess tools and work with vendors and third party developers as issues are identified.
Investigate the passivation quality of p-TOPCon to evaluate the promise and viability of upgraded p-PERC with p-TOPCon back. Model and simulate the p-PERC and p-TOPCon cells to predict the gain in cell efficiency by implementation of the p-TOPCon Develop a simple process sequence and fabricate p-TOPCon-PERC cell with ≥ 21.0% efficiency
Abstract not provided.
The purpose of this DOE SBIR award was to develop new scanning probe microscopy tools for the elucidation of electrical and electrochemical properties at the nanoscale. High performance probes are important for energy materials research. In both solar cells and batteries, the essential physics and chemistry occur at the nanoscale and nanoscale characterization tools are required for their elucidation. Two products were developed: an electrically shielded probe and an electrically conductive probe with low leakage currents. Our processes were based on post processing of existing probes and fabrication methods were tested, leading to a laser micromachining based approach that led to the first minimal viable product. We invented a method to make a reliable electrical contact that attaches a flexible printed circuit board to the chip. enable leak-free operation crucial when used in conductive liquids and electrolytes. This proprietary solution improves chip handling, reduces contamination, and maintains effective electrical contact. The probes fabricated in this Phase IIa are a minimal viable product which attracted attention from various tip manufacturers and instrument manufacturers alike.
The purpose of this DOE SBIR award was to develop new scanning probe microscopy tools for the elucidation of electrical and electrochemical properties at the nanoscale. High performance probes are important for energy materials research. In both solar cells and batteries, the essential physics and chemistry occur at the nanoscale and nanoscale characterization tools are required for their elucidation. The introduced new models are a shielded probe and an electrically insulated probe where only less than one micron of a conductive tip is exposed. In Phases I and IIa, we explored the development of cost-effective methods to insulate cantilevers from aqueous solutions and patented a technology that provides an insulated electrical contact to the tip. Also, our technology was adapted to be compatible with all popular commercial AFM systems. In Phase IIb, we improved reproducibility and batch size to drive down costs while maintaining quality control with testing. We transformed our product into a convenient turnkey solution to make electrochemical characterization approachable to a wide range of researchers. In January 2021, the technology was well received by the AFM community and Nanosurf Inc. (Woburn, MA) acquired Scuba Probe Technologies. The technology and expertise of Scuba Probe Technologies complements Nanosurf’s development of the full range of nano-electrical characterization tools.
In this report, we assess the data recorded by a Distributed Acoustic Sensing (DAS) cable deployed during the Source Physics Experiment, Phase II (DAG) in comparison with the data recorded by nearby 4.5-Hz geophones. DAS is a novel recording method with unprecedented spatial resolution, but there are significant concerns around the data fidelity as the technology is ramped up to more common usage. Here we run a series of tests to quantify the similarity between DAS data and more conventional data and investigate cases where the higher spatial resolution of the DAS can provide new insights into the wavefield. These tests include 1D modeling with seismic refraction and bootstrap uncertainties, assessing the amplitude spectra with distance from the source, measuring the frequency dependent inter-station coherency, estimating time-dependent phase velocity with beamforming and semblance, and measuring the cross-correlation between the geophone and the particle velocity inferred from the DAS. In most cases, we find high similarity between the two datasets, but the higher spatial resolution of the DAS provides increased details and methods of estimating uncertainty.
Based on sensor fusion and machine learning, this project developed a novel non-destructive evaluation (NDE) methodology, which consists of a remaining useful life (RUL) prediction framework and regression models for predicting residual stress and full width at half maximum (FWHM). A series of fatigue testing experiments were conducted using 5052-H32 aluminum alloy specimens. All specimens were measured using linear ultrasonic (LU) and nonlinear ultrasonic (NLU) testing methods non-destructively. Machine learning models were developed to use LU and NLU measurements to predict loading condition, fatigue level, residual stress, and FWHM. It was demonstrated that the developed methodology could distinguish new and fatigue specimens with an accuracy of 97.53%. Also, the prediction errors for residual stress and FWHM were as low as 4.73% and 1.62%, respectively. An interactive database was created to publicly share the data generated from the project. It is envisioned that the developed NDE technology will equip manufacturers with a responsive screening system for incoming used metallic components, and potentially lead to a significant increase in using used metallic components for remanufacturing.
The Long Island Solar Farm (LISF) is a 32-megawatt solar photovoltaic power plant built through a collaboration including BP Solar, the Long Island Power Authority (LIPA), and the U.S. Department of Energy (DOE). The LISF, located on the Brookhaven National Laboratory site, began delivering power to the LIPA grid in November 2011, and is currently one of the largest solar photovoltaic power plants in the eastern United States. It is generating enough renewable energy to power approximately 4,500 homes and is helping New York State meet its clean energy and carbon reduction goals. Brookhaven National Laboratory (BN)L has the LISF instrumented and is capturing solar insolation and power data that can be used for research purposes. Additional information on LISF is available here: https://www.bnl.gov/lisf/. A network of nine high-definition (HD cameras) and 32 pyranometers are deployed within the LISF for the purpose of monitoring the location and characteristics of clouds and available global horizontal irradiance at the surface across the region. Information collected by this network every 30 s is currently used in BNL’s solar NowCasting algorithm, which forecasts near-term solar energy availability accounting for the behavior of clouds. The most important parameters for forecasting the near-term solar energy availability are accurate estimations of their horizontal extend, horizontal motion, and cloud base height. Currently, images from nearly located cameras are used to estimate the cloud base height. In order to evaluate the potential of this method for estimating the cloud base height, we decided to deploy a Vaisala ceilometer at the LISF.
In this report, we assess the data recorded by a Distributed Acoustic Sensing (DAS) cable deployed during the Source Physics Experiment, Phase II (DAG) in comparison with the data recorded by nearby 4.5-Hz geophones. DAS is a novel recording method with unprecedented spatial resolution, but there are significant concerns around the data fidelity as the technology is ramped up to more common usage. Here we run a series of tests to quantify the similarity between DAS data and more conventional data and investigate cases where the higher spatial resolution of the DAS can provide new insights into the wavefield. These tests include 1D modeling with seismic refraction and bootstrap uncertainties, assessing the amplitude spectra with distance from the source, measuring the frequency dependent inter-station coherency, estimating time-dependent phase velocity with beamforming and semblance, and measuring the cross-correlation between the geophone and the particle velocity inferred from the DAS. In most cases, we find high similarity between the two datasets, but the higher spatial resolution of the DAS provides increased details and methods of estimating uncertainty.
The paper provides the approach to providing a benefit cost analysis of energy and water alternatives to provide resilience to extreme events. The approach estimates the costs and returns of providing greater resilience of water and energy infrastructure. Extreme events are defined as high impact, low-frequency events such as, but not limited to, hurricanes, floods, storm surges and earthquakes. The provides justification for hardening water and energy infrastructure. Resilience is defined as “the ability to prepare for and to withstand an extreme event with little or no damage, or to recover more quickly from an extreme event.” The approach can be summarized as follows. The approach requires the development of a baseline with which to compare alternatives. The baseline is used to evaluate the baseline’s resilience to hazards through the probability of the hazard(s), the likelihood of damage from that the hazard through a vulnerability analysis, and the consequence to calculate a cost of the damage. The approach then evaluates proposed mitigation alternatives that would improve the resilience of the system. Each alternative is evaluated based on probability of the hazard, probability of vulnerability and consequence to determine the reduced damage that each alternative presents. The approach includes any monetary and non-monetary benefits that can quantified for each of the alternatives. Non-quantifiable benefits are evaluated based on the relative importance of each alternative to the criteria used to determine how well the alternative meets the goals and objectives of the site/facility. Then, a life cycle cost analysis should be conducted for the baseline and alternatives. Finally, the results of the life cycle analysis should be presented in a decision matrix with cost, net present value, benefit/cost ratios, and any non-monetary criteria ranked to show how well the alternatives met the criteria, weighted with the decision maker’s weights and the results presented.