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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 307 records · Page 17

Testing the Performance and Dynamic Control of Energy-Efficient Cellular Shades in the PNNL Lab Homes

This report describes the experimental design and results of testing the energy performance of Hunter Douglas double-cell cellular shades under various control schemes in the Pacific Northwest National Laboratory’s (PNNL) Lab Homes. The results of both heating and cooling season experiments are presented, where testing is designed to assess the heating, ventilation, and air conditioning (HVAC) savings resulting from the thermal insulating properties as well as the automated and dynamic control strategies of shading devices. Control schemes tested include common “connected home” strategies where controls are integrated and coordinated between the window shading device, building thermostats, and external sensors.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Better Batteries for Transportation: Behind the Scenes @ Berkeley Lab

Vince Battaglia leads a behind-the-scenes tour of Berkeley Lab's BATT, the Batteries for Advanced Transportation Technologies Program he leads, where researchers aim to improve batteries upon which the range, efficiency, and power of tomorrow's electric cars will depend. This is the first in a forthcoming series of videos taking viewers into the laboratories and research facilities that members of the public rarely get to see.

25 ENERGY STORAGE↗

Perspectives for self-driving labs in synthetic biology

Self-driving labs (SDLs) combine fully automated experiments and data collection with artificial intelligence (AI) and control algorithms that decide not only the set of parameters for the next experiment, but also potentially which scientific hypotheses to test. Taken to their ultimate expression, SDLs could usher a new paradigm of scientific research, where the world is probed, interpreted, and explained by machines for human benefit. Whereas there are functioning SDLs in the fields of chemistry and materials science, we contend that synthetic biology provides a unique opportunity since the genome provides a single, easily accessible, target for affecting the incredibly wide repertoire of biological cell behavior. Since they can provide large amounts of high-quality data, SDLs can be a platform for AI to develop approaches to systematically convert data into scientific knowledge systems. These knowledge systems can be used both to understand the biological world and to design bioengineered systems to fit a desired specification (inverse design). However, the level of investment required for the creation of biological SDLs is only warranted if directed towards solving difficult and enabling biological questions. Here, we discuss challenges and opportunities in creating SDLs for synthetic biology.

59 BASIC BIOLOGICAL SCIENCES↗

Lab-scaled performance evaluation of novel water-lean solvents for post combustion CO 2 capture

Here, this work focuses on demonstrating the energetic performance and operational reliability in a continuous system of RTI's water-lean solvents for post-combustion CO 2 capture applications. RTI's Non-Aqueous Solvent, NAS-1A was subjected to 100 h of continuous, CO 2 capture and regeneration operation using a Lab-scale Gas Absorption System (LsGAS) while the CO 2 capture efficiency, mass balance, and total energy inputs were monitored. Throughout the test period, NAS-1A demonstrated stable operation with 90% CO 2 capture while requiring about 15% lower total energy input for solvent regeneration compared to 30 wt% monoethanolamine (MEA) solution. The use of a slipstream of CO 2 -rich solvent from the absorber sump reduced the regenerated CO 2 temperature before the gas was further cooled by the overhead condenser at the top of the desorber. The rich-split setup combined with a wash section may be an effective approach to remove water and solvent vapor from the regenerated CO 2 as well as to recover heat at the top of the desorber. NAS-1B was later developed and included a modifier component that lowers the heat of CO 2 absorption and reduces the vapor pressure of the amine component. The total energy inputs for 90% CO 2 capture with NAS-1B was found to be 25% less than that of the MEA. A gas chromatograph was used to monitor the amine concentration in the gas leaving the absorber wash section. It was found that under similar operating conditions, the presence of the modifier in NAS-1B reduces the amine in the absorber off-gas from 143 ppm in NAS-1A to 20 ppm.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

How technoscientific knowledge advances: A Bell-Labs-inspired architecture

Understanding how science and technology advance has long been of interest to diverse scholarly communities. Thus far, however, such understanding has not been easy to map to, and thus to improve, the operational practice of research and development. Indeed, one might argue that the operational practice of research and development, particularly its exploratory research half, has become less effective in recent decades. In this paper, we describe a rethinking of how science and technology advance, one that is consistent with many (though not all) of the perspectives of the scholarly communities just mentioned, and one that helps bridge the divide between theory and practice. In conclusion, the result is an architecture we call “Bell's Dodecants,” to reflect its six mechanisms and two flavors, and their balanced nurturing at Bell Labs, the iconic 20th century industrial research and development laboratory.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Superconducting Magnets for the 12 GeV Upgrade at Jefferson Lab

Jefferson Laboratory is embarked on an energy upgrade to its flagship continuous electron beam accelerator in order to expand the scope of its research capabilities and probe further into the structure of nuclear particles. The 12 GeV upgrade includes the design, manufacture, integration, installation and commissioning of eight different superconducting magnets in three separate experimental halls. The effort involves other national laboratories, universities and industry spanning three countries. This paper will summarize the key characteristics of these magnets, ranging in size from 0.2 to 23 MJ in stored energy, and featuring many different types and configurations. The paper will also give an overview of the specific technical challenges for each magnet, and a status report on magnet manufacture and expected delivery dates. The 12GeV upgrade at J-Lab represents the largest superconducting magnet fabrication and installation program currently ongoing in the United States and this paper will present the breadth of collaborations supporting it.

12 GeV upgrade, continuous electron beam accelerat↗

A Charge Sensitive Pre-Amplifier for Smart Point-of-Care Devices Employing Polymer Based Lab-on-a-Chip

With increasing emphasis on implantable and portable medical devices, low-power, small-chip-area sensor readout system realized in lab-on-a-chip (LOC) platform is gaining more and more importance these days. The main building blocks of the LOC system include a front-end transducer that generates an electrical signal in response to the presence of an analyte of interest, signal processing electronics to process the signal to comply with a specific transmission protocol and a low-power transmitter, all realized in a single integrated circuit platform. Low power consumption and compactness of the components are essential requirements of the LOC system. This paper presents a novel charge sensitive pre-amplifier developed in a standard 180-nm CMOS process suitable for implementing in an LOC platform. The pre-amplifier converts the charge generated by a pyroelectric transducer into a voltage signal, which provides a measurement of the temperature variation in biological fluids. The proposed design is capable of providing 0.8-mV/pC gain while consuming only 2.1 μW of power. Finally, the pre-amplifier composed of integrated components occupies an area of 0.038 mm 2 .

36 MATERIALS SCIENCE↗

A Beamdump facility at Jefferson Lab

The potential of the intense secondary muon, neutrino, and (hypothetical) light dark matter beams at the Thomas Jefferson National Accelerator Facility (Jefferson Lab) is explored. These are produced in the high-power dumps with high-current electron beams. Light dark matter searches with the approved Beam Dump eXperiment (BDX) are driving the realization of a new underground vault behind Hall A that could be extended to a Beamdump Facility with little additional installations. High-energy muons created via the Bethe–Heitler process uniquely do not proceed through the more common pion production and decay channels. Several possible muon physics applications are highlighted. Neutrino detector technologies and experiments suitable for a beamdump facility are outlined.

Accelerator Physics↗

Exploring Benchmarks for Self-Driving Labs using Color Matching

Self Driving Labs (SDLs) that combine automation of experimental procedures with autonomous decision making are gaining popularity as a means of increasing the throughput of scientific workflows. The task of identifying quantities of supplied colored pigments that match a target color, the color matching problem, provides a simple and flexible SDL test case, as it requires experiment proposal, sample creation, and sample analysis, three common components in autonomous discovery applications. We present a robotic solution to the color matching problem that allows for fully autonomous execution of a color matching protocol. Our solution leverages the WEI science factory platform to enable portability across different robotic hardware, the use of alternative optimization methods for continuous refinement, and automated publication of results for experiment tracking and post-hoc analysis.

Artificial intelligence↗

Lab-Scale Stimulation Results on Surrogate Fused Silica Samples

Lab-scale stimulation work on non-porous fused silica (similar mechanical properties to igneous rock) was performed using pure water, pure CO2 and water/CO2 mixtures to compare back to back fracturing performance of these fluids with PNNL's StimuFrac.

15 GEOTHERMAL ENERGY↗

Processed Lab Data for Neural Network-Based Shear Stress Level Prediction

Machine learning can be used to predict fault properties such as shear stress, friction, and time to failure using continuous records of fault zone acoustic emissions. The files are extracted features and labels from lab data (experiment p4679). The features are extracted with a non-overlapping window from the original acoustic data. The first column is the time of the window. The second and third columns are the mean and the variance of the acoustic data in this window, respectively. The 4th-11th column is the the power spectrum density ranging from low to high frequency. And the last column is the corresponding label (shear stress level). The name of the file means which driving velocity the sequence is generated from. Data were generated from laboratory friction experiments conducted with a biaxial shear apparatus. Experiments were conducted in the double direct shear configuration in which two fault zones are sheared between three rigid forcing blocks. Our samples consisted of two 5-mm-thick layers of simulated fault gouge with a nominal contact area of 10 by 10 cm^2. Gouge material consisted of soda-lime glass beads with initial particle size between 105 and 149 micrometers. Prior to shearing, we impose a constant fault normal stress of 2 MPa using a servo-controlled load-feedback mechanism and allow the sample to compact. Once the sample has reached a constant layer thickness, the central block is driven down at constant rate of 10 micrometers per second. In tandem, we collect an AE signal continuously at 4 MHz from a piezoceramic sensor embedded in a steel forcing block about 22 mm from the gouge layer The data from this experiment can be used with the deep learning algorithm to train it for future fault property prediction.

15 GEOTHERMAL ENERGY↗

Lab Homes

This dataset includes processed data from the Lab Homes (LH) Test Facility located on the PNNL campus in Richland, WA. This a set of 2 identical homes that allow for the side-by-side comparison/performance evaluation of different technologies under the same weather at any given time. The dataset spans December 6, 2021 to December 27, 2021 and represents a series of tests performed; calibration, set-point excitation, pre-heating, free-floating and warm up. The measurements correspond to whole building electrical power, HVAC energy use, water heating, appliances and lighting, as well as space temperatures, space humidity, window glass surface temperatures, through glass solar radiation, and meterological data from an onsite meteorological weather station. In addition to the measurements, a metadata .json file, a .ttl file to visualize the data as per BRICK schema, and a detailed .pdf description of the dataset are also provided.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Study of Double Spin Asymmetries in Inclusive ep Scattering at Jefferson Lab

The spin structure of the proton has been investigated in the high Bjorken x and low momentum transfer Q 2 region. We used Jefferson Lab's polarized electron beam, a polarized target, and a spectrometer to get both the parallel and perpendicular spin asymmetries Apar and Aperp. These asymmetries produced the physics asymmetries A_1 and A_2 and spin structure functions g_1 and g_2. We found Q 2 dependences of the asymmetries at resonance region and higher-twist effects. Our result increases the available data on the proton spin structure, especially at resonance region with low Q 2 . Moreover, A_2 and g_2 data show clear Q 2 evolution, comparing with RSS and SANE-BETA. Negative resonance in A_2 data needs to be examined by theory. It can be an indication of very negative transverse-longitudinal interference contribution at W ~ 1.3 GeV. Higher twist effect appears at the low Q 2 of 1.9 GeV 2 , although it is less significant than lower Q 2 data of RSS. Twist03 matrix element d_2 was calculated using our asymmetry fits evaluation at Q 2 – 1.9 GeV 2 . D-bar_2 = -0.0087±0.0014 was obtained by integrating 0.47 ≤ x ≤ 0.87.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Innovation Incubator: Whisker Labs Technical Evaluation

The Wells Fargo Innovation Incubator (IN2) is a program to foster and accelerate startup companies with commercial building energy-efficiency and demand management technologies. The program is funded by the Wells Fargo Foundation and co-administered by the National Renewable Energy Laboratory (NREL). Whisker Labs, an Oakland, California-based company, was one of four awardees in the first IN2 cohort and was invited to participate in the program because of its novel electrical power sensing technology for circuit breakers. The stick-on Whisker meters install directly on the front face of the circuit breakers in an electrical panel using adhesive, eliminating the need to open the panel and install current transducers (CTs) on the circuit wiring.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗