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At least 235 records · Page 13

Enabling Ultralow Volume Analysis with a High-Resolution Ion Mobility Mass Spectrometry Platform

Of all the molecules thought to exist in the universe, it is estimated that researchers only know the chemical structures of 5% of them. Identifying the chemical structures of the remaining 95% has proven extremely challenging because many molecules exhibit low abundance, are contained in small volumes (e.g., <10 nL), do not readily ionize, exhibit similar structures to other molecules, etc. No single analytical technique exists to definitively identify the structure of an unknown molecule, and thus multiple different molecular measurements are typically made (i.e., multi-modal approach). Ion mobility (IMS) and mass spectrometry (MS) are two key tools that researchers use to determine the chemical structures of unknown molecules, and recently high-resolution and ultrahigh resolution IMS-MS instruments have provided greater confidence than ever before. However, HR-IMS-MS instruments typically exhibit low ion utilization efficiency, meaning they require large amounts of sample for an analysis (e.g., >10 µL). Unfortunately, this limitation prohibits the analysis of small volume samples where many unknown molecules exist. Described herein are the efforts made to enable the analysis of ultralow volumes with an HR-IMS-MS platform. A new scanning technique, termed a ‘stuttered traveling wave scan’, was developed as a replacement for the dual-gated scanning technique and works by halting the traveling waves after allowing ions to separate and then repeatedly restarting and stopping the traveling waves to incrementally move ions from the SLIM to the Orbitrap. Ions were stored inside the SLIM while the TWs were stopped, allowing the Orbitrap to perform high-resolution mass analysis. When the Orbitrap was ready, the TWs were restarted for short periods of time (<10 ms) to move ions from the SLIM to the Orbitrap. It was discovered that lower TW amplitudes and speeds than used during IMS separation were required to produce IMS peaks with the highest signal intensities and best resolving powers. The stuttered TW scan was found to produce similar resolutions and signal intensities compared to the dual-gated scanning technique. A new IMS design possessing an intersecting ‘tee’ with a reversible traveling wave was also developed to improve ion utilization efficiency during cyclic operation, which is necessary when only a single IMS spectrum can be acquired, such as when analyzing ultralow volume samples. The new capabilities described in this report lay the groundwork for acquiring HR-IMS-MS spectra of ultralow volume biological samples, such as single cells, where HR-IMS-MS can help elucidate the structures of unknown compounds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Methodology for determining optimal milling parameters for low-taper microtensile sample production

Femtosecond lasers are beginning to see an increase in interest for industrial and high throughput microsample milling applications. Despite this, much of the literature regarding removal rate studies for ultrashort pulse laser milling continues to focus on single-pulse or similar experiments that have a very small time on target. The material volume removal rates of femtosecond milling can vary wildly depending on parameters like laser scan speed, hatch spacing, z-axis step size, and pulses on the material. Currently, there is no established methodology for determining the optimal values of these parameters for micromilling applications. This methodology was developed in this study. The methodology consists of a pulse study, a repeat study, and a z-step study that will return the milling parameters that resulted in the largest volume removal rate for the laser used for this research. The methodology was created for the laser system used in this study, and was tested on 316 Stainless Steel, but was developed in such a way that it may be adapted to any material, and with some tweaking of variables might be used in other laser systems. The laser system used in this study utilizes a novel positioning stage that introduces 6 degrees of freedom to the translation of laser samples, being able to tilt and move in all three axes. Using both the developed methodology and the unique capabilities of the laser microtensile samples were produced with taper angles of <1° in 316 Stainless Steel.

Barker, Zachary Wayne↗

Dynamic Bottlebrush Polymer Networks: Self-Healing in Super-Soft Materials

Here, we introduce a design strategy to expand the range of accessible mechanical properties in covalent adaptable networks (CANs) using bottlebrush polymer building blocks. Well-defined bottlebrush polymers with rubbery poly(4-methylcaprolactone) side-chains were crosslinked in formulations that include a bislactone and strong Lewis acid (tin ethylhexanoate). The resulting materials exhibit tunable stress relaxation rates at elevated temperatures (160–180 °C) due to dynamic ester crosslinks that undergo transesterification with residual hydroxy groups. Varying the crosslinker loading or bottlebrush backbone degree of polymerization yields predictable low-frequency shear moduli ca. 10–100 kPa, well below values typical of linear polymer CANs (1 MPa). These extensible networks can be stretched to strains as large as 350% before failure and undergo efficient self-healing to recover >85% of their original toughness upon repeated fracture and melt processing. In summary, molecular architecture creates new opportunities to tailor the mechanical properties of CANs in ways that are otherwise difficult to achieve.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Fuel property evaluation of unique fatty acid methyl esters containing β-hydroxy esters from engineered microorganisms

Unique fatty acid methyl esters (FAME) containing ..beta..-hydroxy esters were produced using an engineered microorganism by glucose fermentation. This study investigated the properties of the unique FAME mixture both neat and in blends with conventional diesel, as well as properties of ..beta..-hydroxy esters. The unique FAME blend contained relatively shorter-chain FAME (average fatty acid chain carbon number 14.6) with 58 % monounsaturated fatty acids and 9 % saturated and monounsaturated ..beta..-hydroxy acid chains. The unique FAME had significantly lower distillation T90 (321 °C versus 352 °C) and higher cetane number (56.7 versus 52) compared to soy biodiesel. Cloud points were within method repeatability. Unexpectedly (because of the lack of methylene-interrupted double bonds), the unique FAME had low oxidation stability (1.5 h) as determined by Rancimat induction period. Stability could be improved through addition of commonly used antioxidants. We speculate that monounsaturated ..beta..-hydroxy FAME may be the source of this instability. Blends with conventional diesel up to 50 vol% showed similar kinematic viscosity (within method repeatability) as blends of conventional FAME. The unique FAME had no effect on distillation T90 even at the 80% blend level. A 30 vol% blend into conventional diesel had a Rancimat induction period of only 2 h, very nearly the same as the neat unique FAME sample. The addition of antioxidants produced blends of acceptable stability. Based on an assessment of the properties of individual ..beta..-hydroxy FAME molecules, they have higher boiling point, higher cloud point, lower cetane number, and potentially lower storage stability than analogous FAME not having the ..beta..-hydroxy group. Removing them from the fuel product in the production process may result in a biodiesel product with superior properties to what is on the market today.

09 BIOMASS FUELS↗

Toward All-Solid-State Lithium Batteries: Three-Dimensional Visualization of Lithium Migration in β-Li 3 PS 4 Ceramic Electrolyte

All-solid lithium batteries are an attractive next-generation technology that use ion-conducting solids such as ..beta..-Li3PS4 (LPS) to enable use of a lithium metal anode, which increases theoretical capacity and widens the stable voltage window over traditional lithium-ion systems. These ion-conductive solids also provide increased safety by replacing flammable liquid electrolytes. Although solid-state electrolytes are significantly more stable and dendrite-resistant than traditional liquid electrolytes, lithium anodes in all-solid systems may nevertheless grow dendrites under high stress or repeated cycling, leading to short circuits and premature battery breakdown. For this reason, we study the formation and propagation of Li metal features within solid electrolytes using synchrotron-based X-ray tomography with in-situ current-voltage cycling supported by our custom sample platform. Our results demonstrate the ability of this technique to delineate different layers of the Li/LPS/Li structure with spatial resolution approaching 1 um. At this resolution, we are able to detect expansion of voids, especially in early stages of cycling. This expansion of voids is observed throughout the volume of the symmetric cells and visually resembles propagation of cracks resulting from interactions between the Li metal and pre-existing voids in the LPS electrolyte.

25 ENERGY STORAGE↗

Deep Learning and Photogrammetric Reconstruction for Automated Crack Detection and Dimensional Measurement in Mining Operations

Surface crack detection and dimensional measurement at active mining sites present significant safety and operational challenges. Manual inspection methods are labor-intensive, spatially incomplete, and expose personnel to hazardous environments, while existing automated approaches have been developed primarily for concrete civil infrastructure and have not been validated on the complex, variable surfaces characteristic of mining environments. This dissertation presents an automated pipeline that integrates deep learning semantic segmentation with Structure-from-Motion photogrammetry to detect surface cracks and measure their aperture, length, and vertical displacement from standard RGB imagery acquired during routine Uncrewed Aerial Vehicle (UAV) survey operations, without requiring additional sensor hardware or manual measurement. The pipeline combines a U-Net architecture with an EfficientNet-B0 encoder, pretrained on the SDNET2018 concrete crack dataset and fine-tuned on a mining-specific dataset spanning laboratory concrete specimens, coal refuse impoundment embankments, and post-blast limestone quarry benches. Photogrammetric reconstruction is performed using COLMAP Structure-from-Motion and Multi-View Stereo, with crack segmentation masks projected into the reconstructed point cloud to enable three-dimensional vertical displacement measurement through local plane fitting and bimodal surface detection. The pipeline was validated across 36 controlled laboratory specimens at three imaging distances and four vertical displacement levels, achieving aperture measurement RMSE of 0.047 cm and R² of 0.954, and vertical displacement RMSE of 0.140 cm and R² of 0.966, against independent caliper measurements. Field application at a coal refuse impoundment in southwestern Pennsylvania detected 71 crack components across the embankment crest, with a dominant longitudinal crack exhibiting aperture values reaching 28 cm and a 95th percentile vertical displacement of 35.53 cm, consistent in magnitude and spatial distribution with simultaneously acquired LiDAR-derived estimates. Application across four post-blast limestone quarry bench datasets in California successfully characterized blast-induced fracture networks at ground sampling distances ranging from 0.59 to 1.23 cm/pixel, with detected crack geometries physically consistent with observable surface conditions at each site. The results demonstrate that deep learning-based crack detection and photogrammetric measurement can be integrated into routine UAV inspection workflows at mining sites, providing repeatable, scalable, and quantitative crack characterization across surface types, crack scales, and displacement magnitudes not previously addressed in the literature. The pipeline requires no dedicated surveying equipment beyond the UAV platforms already deployed at mine sites for survey and monitoring purposes, supporting practical adoption within existing operational workflows.

Crack detection, Dimensional Measurement↗

IER 557: Godiva Pulse Repeatability and Characterization (CED-3A Report)

Godiva IV is a fast burst critical assembly constructed of approximately 65 kg of highly enriched uranium (HEU) fuel alloyed with 1.5% molybdenum for strength. Godiva IV is proposed as the radiation source for IER 498: Design a Shielding Benchmark with a Metal Critical Source. IER 498 proposes a two-burst method to determine the performance of shielding samples, comparing the transmission of the source radiation to detectors with and without a shielding sample present. This eliminates the need for an absolute calibration and allows many uncertainties to cancel. However, the source term variability must be low compared to other sources of experimental uncertainty to ensure the overall uncertainty meets acceptable levels to provide useful measurements. The primary goal of this experiment is to quantify the source term variability, or reproducibility, of Godiva bursts, focusing on the 70 °C bursts planned for IER 498 measurements. Discussions during IER 498 noted that a number of bursts (on the order of six to ten) as identical as possible would be performed and that a 5-7% standard deviation in source intensity would be acceptable.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Compost Amendment to a Grazed California Annual Grassland Increases Gross Primary Productivity Due To a Longer Growing Season

Abstract Compost amendment to rangelands is a proposed nature‐based climate solution to increase plant productivity and soil carbon sequestration. However, it has not been evaluated using quasicontinuous ecosystem‐scale measurements. Here, we present the first study to utilize eddy covariance and footprint partitioning to monitor carbon exchange in a grassland with and without compost amendment, monitoring for 1 year before and 1 year after treatment. Compost amendment to an annual California grassland was found to enhance net ecosystem removal of carbon. Our study confirmed that compost‐amended grasslands, similar to nonamended grasslands, are net carbon sources to the atmosphere; however, the amendment appears to be slowing down the rate at which these ecosystems lose carbon by 0.71 Mg C ha −1 per growing season. Digital repeated imagery of the canopy revealed that compost‐amended grasslands experienced an earlier green‐up, resulting in an overall longer growing season by >60 days. Notably, we did not detect significantly higher amounts of soil carbon in compost‐amended soils. High variability in soil carbon demands greater sampling replication in future studies. A longer growing season and higher productivity are hypothesized to be a result of greater availability of macronutrients and micronutrients in the top layer of soil (specifically nitrogen, phosphorus, and zinc).

Fenster, Tommy L. D.↗

Fermionic Partial Tomography via Classical Shadows

Here we propose a tomographic protocol for estimating any k-body reduced density matrix (k-RDM) of an n-mode fermionic state, a ubiquitous step in near-term quantum algorithms for simulating many-body physics, chemistry, and materials. Our approach extends the framework of classical shadows, a randomized approach to learning a collection of quantum-state properties, to the fermionic setting. Our sampling protocol uses randomized measurement settings generated by a discrete group of fermionic Gaussian unitaries, implementable with linear-depth circuits. We prove that estimating all k-RDM elements to additive precision ϵ requires on the order of ($^{n}_{k}$)k 3/2 log(n)/ϵ 2 repeated state preparations, which is optimal up to the logarithmic factor. Furthermore, numerical calculations show that our protocol offers a substantial improvement in constant overheads for k ≥ 2, as compared to prior deterministic strategies. We also adapt our method to particle-number symmetry, wherein the additional circuit depth may be halved at the cost of roughly 2–5 times more repetitions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Dynamic in vivo monitoring of granum structural changes of Ctenanthe setosa (Roscoe) Eichler during drought stress and subsequent recovery

Investigating the effects of drought stress and subsequent recovery on the structure and function of chloroplasts is essential to understanding how plants adapt to environmental stressors. We investigated Ctenanthe setosa (Roscoe) Eichler, an ornamental plant that can tolerate prolonged drought periods (40 and 49 days of water withdrawal). Conventional biochemical, biophysical, physiological and (ultra)structural methods combined for the first time in a higher plant with in vivo small-angle neutron scattering (SANS) were used to characterize the alterations induced by drought stress and subsequent recovery. Upon drought stress, no significant changes occurred in the chloroplast ultrastructure, chlorophyll content, 77K fluorescence emission spectra and maximal quantum efficiency of PSII (Qy dark), but the actual quantum efficiency of PSII (Qy light) decreased, the amounts of PSI-LHCII complexes and PSII monomers declined, and that of PSII supercomplexes increased. Thickness of the leaf and of the adaxial hypodermis, chloroplast length and granum repeat distance (RD) values decreased upon drought stress, as shown by light microscopy and SANS, respectively. Because of the very slight (nm-range) changes in RD values, the large biological variability (significant differences in RD values among the leaves and studied leaf regions) and the invasive sampling required for this method, transmission electron microscopy (TEM) hardly showed significant differences. On the other side, in situ SANS analyses provided a unique insight in vivo into the fast structural recovery of the granum structure of drought-stressed leaves, which happened already 18 h after re-watering, while functional and biochemical recovery took place on a longer time scale.

59 BASIC BIOLOGICAL SCIENCES↗

The track-length extension fitting algorithm for energy measurement of interacting particles in liquid argon TPCs and its performance with ProtoDUNE-SP data

This paper introduces a novel track-length extension fitting algorithm for measuring the kinetic energies of inelastically interacting particles in liquid argon time projection chambers (LArTPCs). The algorithm finds the most probable offset in track length for a track-like object by comparing the measured ionization density as a function of position with a theoretical prediction of the energy loss as a function of the energy, including models of electron recombination and detector response. The algorithm can be used to measure the energies of particles that interact before they stop, such as charged pions that are absorbed by argon nuclei. The algorithm's energy measurement resolutions and fractional biases are presented as functions of particle kinetic energy and number of track hits using samples of stopping secondary charged pions in data collected by the ProtoDUNE-SP detector, and also in a detailed simulation. Additional studies describe the impact of the dE/dx model on energy measurement performance. The method described in this paper to characterize the energy measurement performance can be repeated in any LArTPC experiment using stopping secondary charged pions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Multi-amplifier Sensing Charge-coupled Devices for Next Generation Spectroscopy

We present characterization results and performance of a prototype Multiple-Amplifier Sensing (MAS) silicon charge-coupled device (CCD) sensor with 16 channels potentially suitable for faint object astronomical spectroscopy and low-signal, photon-limited imaging. The MAS CCD is designed to reach sub-electron readout noise by repeatedly measuring charge through a line of amplifiers during the serial transfer shifts. Using synchronized readout electronics based on the Dark Energy Spectroscopic Instrument CCD controller, we report a read noise of 1.03 e$^{−}$ rms pix$^{−1}$ at a speed of 26 μs pix$^{−1}$ with a single-sample readout scheme where charge in a pixel is measured only once for each output stage. At these operating parameters, we find the amplifier-to-amplifier charge transfer efficiency (ACTE) to be >0.9995 at low counts for all amplifiers but one for which the ACTE is 0.997. This charge transfer efficiency falls above 50,000 electrons for the read-noise optimized voltage configuration we chose for the serial clocks and gates. The amplifier linearity across a broad dynamic range from ∼300 to 35,000 e$^{−}$ was also measured to be ±2.5%. We describe key operating parameters to optimize on these characteristics and describe the specific applications for which the MAS CCD may be a suitable detector candidate.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

High-Performance Piezoelectric MEMS Manufacturing & Application on Micro Power Generators (CRADA Final Report)

This project aimed to develop and characterize a micro-fabrication technology for wafer-scale heterogeneous integration of bulk piezoelectric materials on silicon substrates that could enable manufacturing of high-performance micro transducers. Typical technical challenges for piezoelectric microfabrication technologies are high-temperature processing, non-uniform film quality, and low process repeatability, which will be addressed during this project. Progress was made on preliminary research towards development of a technology platform that will enable a new micro-fabrication process to provide the highest electromechanical coupling among any other thin/thick-film deposition methods available today. This work has tested and characterized samples that we hope will further our goal of refining and enabling existing micro transducers to achieve unprecedentedly high performance. This project focused solely on the characterization of the proposed microfabrication process technology, and it did not consist of design or manufacturing of new transducers, such as sensors, actuators or energy harvesters based on this fabrication process. Future work will be aimed at the research and development of process steps specifically to enable integration of on-chip electronics with piezoelectric materials.

36 MATERIALS SCIENCE↗

Development of a Freeze-Dried CRISPR-Cas12 Sensor for Detecting Wolbachia in the Secondary Science Classroom

Training the future synthetic biology workforce requires the opportunity for students to be exposed to biotechnology concepts and activities in secondary education. Detecting Wolbachia bacteria in arthropods using polymerase chain reaction (PCR) has become a common way for secondary students to investigate and apply recombinant DNA technology in the science classroom. Despite this important activity, cutting-edge biotechnologies such as clustered regularly interspaced short palindromic repeat (CRISPR)-based diagnostics have yet to be widely implemented in the classroom. To address this gap, we present a freeze-dried CRISPR-Cas12 sensing reaction to complement traditional recombinant DNA technology education and teach synthetic biology concepts. The reactions accurately detect Wolbachia from arthropod-derived PCR samples in under 2 h and can be stored at room temperature for over a month without appreciable degradation. Here, the reactions are easy-to-use and cost less than $40 to implement for a classroom of 22 students including the cost of reusable equipment. We see these freeze-dried CRISPR-Cas12 reactions as an accessible way to incorporate synthetic biology education into the existing biology curriculum, which will expand biology educational opportunities in science, technology, engineering, and mathematics.

59 BASIC BIOLOGICAL SCIENCES↗

Unorthodox parallelization for Bayesian quantum state estimation

Quantum state tomography (QST) allows for the reconstruction of quantum states through measurements and some inference technique under the assumption of repeated state preparations. Bayesian inference provides a promising platform to achieve both efficient QST and accurate uncertainty quantification, yet is generally plagued by the computational limitations associated with long Markov chains. In this work, we present a novel Bayesian QST approach that leverages modern distributed parallel computer architectures to efficiently sample a D-dimensional Hilbert space. Using a parallelized preconditioned Crank–Nicholson Metropolis–Hastings algorithm, we demonstrate our approach on simulated data and experimental results from IBM Quantum systems up to four qubits, showing significant speedups through parallelization. Although highly unorthodox in pooling independent Markov chains, our method proves remarkably practical, with validation ex post facto via diagnostics like the intrachain autocorrelation time. We conclude by discussing scalability to higher-dimensional systems, offering a path toward efficient and accurate Bayesian characterization of large quantum systems.

Bayesian inference↗

The geometry of signal space: a case study of direct mapping between seismic signals and event distribution

SUMMARY Under favourable circumstances, seismic waveforms corresponding to an ensemble of events related by a common, spatially distributed process collectively exhibit a regular, signal-space geometry. When events in the ensemble have a common, or nearly common, source mechanism, this geometry is a distorted image of the distribution of events in the source region. The signal-space image can be visualized using a relatively simple waveform alignment and projection operation. Ensemble waveform correlation measurements can be inverted to estimate the distribution of the events in the source region, up to an arbitrary rotation, reflection and scaling, with residual distortion. We demonstrate these concepts with synthetic waveforms and with observations of long-wall mining induced seismicity for which substantial ground truth information is available. Our experience with these data has implications for location, correlation detection and machine learning and possible application to studies of repeating events in induced, volcanic and glacial seismicity. Our results place limits on the widely held assumption that waveform correlation is a useful measure of event separation. We suggest that the constraints on event separation need to be evaluated in the context of a population of related events, whose waveforms sample the signal space image of the source region. A better indicator of event separation is the length of the shortest path in signal space along the image.

58 GEOSCIENCES↗

Cyclic moisture reactivation of calcium sorbents for long duration thermochemical energy storage

The transition to a flexible and reliable energy infrastructure, using electro-thermal energy generation technologies such as geothermal, concentrated solar power, and nuclear, usually demands simultaneous advancement of thermal energy storage (TES) to support on-demand electricity generation and industrial applications while mitigating the inherent intermittency of renewable energy sources and power outages from direct energy generation. Among TES technologies, thermochemical energy storage (TCES) based on calcium looping emerges as a compelling high-power energy storage candidate due to its high reaction enthalpy, compatibility with elevated operating temperatures, and abundance of low-cost materials. However, the long-term durability of calcium-based sorbents for TCES is hindered by surface sintering and particle aggregation, leading to performance degradation over repeated thermal cycles. This study explores a moisture hydration-based strategy to regenerate a degraded calcium sorbent and mitigate performance degradation for long duration TCES. The addition of moisture transforms calcium oxide into calcium hydroxide and produces intercalation water layers, associated with a regenerated surface area and reduced calcium oxide crystallite size. Both these effects are beneficial in restoring the sorbents' reactivity for carbonization. Additionally, an optimized hydration-assisted reactivation protocol balances the recovered energy storage capacity with heating penalty required for moisture removal from hydrated samples, resulting in an enhanced energy storage capacity up to 176% compared to benchmark sorbents that undergo cycling without reactivation after 60 cycles. In conclusion, these results highlight the potential of hydration-assisted reactivation to enhance the long-term performance of TCES, providing an effective pathway to advancing electro-thermal storage technologies.

36 MATERIALS SCIENCE↗

A 0.2–2 GHz Time-Interleaved Multistage Switched-Capacitor Delay Element Achieving 2.55–448.6 ns Programmable Delay Range and 330 ns/mm 2 Area Efficiency

Simulation of radar returns, full-duplex systems, and signal repeaters require hundreds of ns of programmable broadband radio frequency (RF) delay in the signal path to simulate large distances in the case of radar returns, for signal cancellation in full-duplex, and for isolation from reflections in signal repeaters. However, programmable broadband RF delay has been limited to ones of ns due to challenges in miniaturization with low loss and low power consumption. In this work, we present a 0.2–2 GHz digitally programmable RF delay element based on a time-interleaved multistage switched-capacitor (TIMS-SC) approach. The proposed approach enables hundreds of ns of broadband RF delay by employing sample time expansion in multiple stages of switched-capacitor storage elements. Further, the delay element was implemented in a 45 nm SOI CMOS process and achieves a 2.55–448.6 ns programmable delay range with < 0.12% delay variation across 1.8 GHz of bandwidth at maximum delay, 2.42 ns programmable delay steps, and 330 ns/mm 2 area efficiency. Through the proposed approach, the device shows minimal delay change across a -40 °C to 85 °C temperature range and < 0.25 dB gain variation across delay settings. The device achieves 26 dB gain, 7.4 dB noise figure, and consumes 74 mW from a 1 V supply with an active area of 1.36 mm 2 .

42 ENGINEERING↗