AC-LGAD silicon detectors with alternate gain layer for improved reliability.
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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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A method is disclosed for doping a quantity of powder particles. A container having a central chamber is initially charged with a quantity of powder particles. A quantity of precursor is sublimed to form a heated precursor. A quantity of carrier gas is mixed with the precursor to form a mixture of heated precursor/carrier gas. The central chamber is charged with the heated precursor/carrier gas and then moved to cause interaction of the powder particles with the heated precursor/carrier gas to form a first monolayer coating on the powder particles. The heated precursor/carrier gas is then removed from the central chamber and the central chamber is charged with a O2/O3 gas under a plasma. The central chamber is then further moved to produce interaction of the O2/O3 gas with the first monolayer coating on the powder particles to modify the first monolayer coating to create a different, single monolayer coating forming an oxide coating on the powder particles.
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Summary Presentation of Instrumentation and Sensors workpackage
This data set provides model output and post-processing files required to reproduce the results, tables, and figures in the paper "Bringing Hydrologic Realism to Water Markets" by Grogan et al. (in review). Other input data used in this study includes: Lisk, M., Grogan, D., Zuidema, S., Caccese, R., Peklak, D., Zheng, J., Fisher-Vanden, K., Lammers, R., Olmstead, S., & Fowler, L. (2023). Harmonized Database of Western U.S. Water Rights (HarDWR) (Version v1) [Data set]. MSD-LIVE Data Repository. https://doi.org/10.57931/2205619 Two models were used in this study: (1) The University of New Hampshire Water Balance Model WBM, and (2) a Water Market Model. Market model code and model output post-processing code that make use of these data can be found here Model output files are: 1. WBM output files: scenario[x]_wbm_output.zip Where [x] is one of 1, 2, 2a, 3, and 3a Each zipped directory contains 7 gridded NetCDF files, each reporting the 10-year annual average value of a given variable, in units of average mm/day: File Name: wbm_indUseGross_yc.nc; Description: Water withdrawals by industry (part of the urban sector) File Name: wbm_domUseGross_yc.nc; Description: Water withdrawals by the domestic sector (part of the urban sector) File Name: wbm_irrigationGross_yc.nc; Description: Water withdrawals for agriculture File Name: wbm_irrigationExtra_yc.nc; Description: Water withdrawals from unsustainable groundwater for agriculture File Name: wbm_indUseEvap_yc.nc; Description: Consumptive water use by industry File Name: wbm_domUseEvap_yc.nc; Description: Consumptive water use by the domestic sector File Name: wbm_irrigationNet_yc.nc; Description: Consumptive water use by agriculture The file full_cell_area.nc gives the area of each grid cell in km2, which is used for converting water depth to water volume. 2. Water market model output & post processing output Folder: marketTrdSummaries/ Description: Files in this folder are used as input to code 1_WelfareCalculation_actual_trades.R. They summarize historical water right trade transactions in each state. File Name: welfare_gain_by_state_sector.csv; Description: Welfare gains by state and sector, as shown in Figure 3F. Used in code Figure3.R and produced (as a .xlsx file) by code 2_DemandCurves_simulated_trades.R File Name: welfare_data_actual.rdata; Description: welfare gains by WMA from actual historical trades, as shown in Figure 3A. This data is the output of code 1_WelfareCalculation_actual_trades.R File Name: welfare_summary_simulated.xlsx; Description: Welfare gains by state as simulated by the market model in Scenario 1. Produced by code 2_DemandCurves_simulated_trades.R, and used in code 4_WelfareCalculation.R. File Name: welfare_summary_cutoffs.xlsx; Description: Welfare gains by state as simulated by the market model in Scenario 2. Produced by code 3_DemandCurves_simulated_trades_cutoffs.R, and used in code 4_WelfareCalculation.R. File Name: welfare_summary_cutoffs_SGMS.xlsx; Description: Welfare gains by state as simulated by the market model in Scenario 2a. Produced by code 3_DemandCurves_simulated_trades_cutoffs.R, and used in code 4_WelfareCalculation.R. File Name: welfare_data_actual.rdata; Description: Spatial data, actual historical welfare gains by WMA as shown in Figure 3A. Produced by code 4_WelfareCalculation.R and used by code Figure3.R. File Name: welfare_data_simulated.rdata; Description: Spatial data, simulated Scenario 1 welfare gains by WMA as shown in Figure 3B. Produced by code 4_WelfareCalculation.R and used by code Figure3.R. File Name: welfare_data_simulated_cutoffs.rdata; Description: Spatial data, simulated Scenario 2 welfare gains by WMA. Produced by code 4_WelfareCalculation.R and used by code Figure3.R. File Name: welfare_data_simulated_cutoffs_SGMA.rdata; Description: Spatial data, simulated Scenario 2a welfare gains by WMA. Produced by code 4_WelfareCalculation.R and used by code Figure3.R. Additional files are provided for efficient reproduction of tables and figures. These include: File Name: wma_thresold_dates_Scenario2(a).csv; Description: Wet vs. paper right threshold dates for each WMA. Shown in Figure 2A,B. Produced and used by code calculate_thresolds_Figure2.R File Name: WWRTradeBounds (directory); Description: Trade boundary shapefile required to reproduce Figure 3A-D. Used in code Figure3.R File Name: welfare_region_totals.csv; Description: Welfare gains for the entire study region, as shown in Figure 3E. Used in code Figure3.R File Name: Welfare_gain_by_state_sector.csv; Description: Welfare gains by state and sector, as shown in Figure 3F. Used in code Figure3.R and produced (as a .xlsx file) by code 2_DemandCurves_simulated_trades.R File Name: WECC_MERIT_5min_v3b_mask.nc; Description: Gridded file that identified which land grid cells are in the WBM model domain, used for processing in code Figure4.py File Name: Table_1.csv; Description: All data in Table 1, reproducible from WBM output files using code table_1.R
We present the performance of a X-γ ray detection systems based on a 300 µm thick silicon low-gain avalanche diode (LGAD) and of an equivalent Diode structure without the gain layer, read-out by a custom-made low-noise charge amplifier. For the LGAD structure, the multiplication gains M s from 10.2 to 19.3 are measured, and the Equivalent Noise Charge (ENC) components have been studied in detail. As expected, a significant reduction of the white and 1/f voltage series and dielectric ENC components is observed with increasing gain, shortening the optimum peaking time to τ = 0.4÷8 μs depending on the gain value, with respect to the standard diode, while the parallel ENC component increases proportionally to the gain up to M s = 15. Setting the gain M s = 12.7, a minimum ENC = 34.5 electrons r.m.s. (298 eV FWHM) at τ = 1 μs is found. However, the electronic noise, evaluated on the pulser FWHM, is found to only marginally contribute to the width of the spectral lines of a radioactive source, which are dominated instead by the statistical noise of the charge multiplication within the LGAD structure. The spectral lines' excess width is found to be proportional to the signal multiplication gain M s and increases with the energy of the photons. A minimum line width of 850 eV FWHM at 13.9 keV is measured at room temperature, τ = 2 μs and a gain M s = 10.2.
Abstract. Wind farm flow control represents a category of control strategies for achieving wind-plant-level objectives, such as increasing wind plant power production and/or reducing structural loads, by mitigating the impact of wake interactions between wind turbines. Wake steering is a wind farm flow control technology in which specific turbines are misaligned with the wind to deflect their wakes away from downstream turbines, thus increasing overall wind plant power production. In addition to promising results from simulation studies, wake steering has been shown to successfully increase energy production through several recent field trials. However, to better understand the benefits of wind farm flow control strategies such as wake steering, the value of the additional energy to the electrical grid should be evaluated – for example, by considering the price of electricity when the additional energy is produced. In this study, we investigate the potential for wake steering to increase the value of wind plant energy production by combining model predictions of power gains using the FLOw Redirection and Induction in Steady State (FLORIS) engineering wind farm flow control tool with historical electricity price data for 15 existing US wind plants in four different electricity market regions. Specifically, for each wind plant, we use FLORIS to estimate power gains from wake steering for a time series of hourly wind speeds and wind directions spanning the years 2018–2020, obtained from the ERA5 reanalysis dataset. The modeled power gains are then correlated with hourly electricity prices for the nearest transmission node. Through this process we find that wake steering increases annual energy production (AEP) between 0.4 % and 1.7 %, depending on the wind plant, with average increases in potential annual revenue (i.e., annual revenue of production, ARP) 4 % higher than the AEP gains. For most wind plants, ARP gain was found to exceed AEP gain. But the ratio between ARP gain and AEP gain is greater for wind plants in regions with high wind penetration because electricity prices tend to be relatively higher during periods with below-rated wind plant power production, when wake losses occur and wake steering is active; for wind plants in the Southwest Power Pool – the region with the highest wind penetration analyzed (31 %) – the increase in ARP from wake steering is 11 % higher than the AEP gain. Consequently, we expect the value of wake steering, and other types of wind farm flow control, to increase as wind penetration continues to grow.
Precooling is a recognized technique for reducing cooling energy in buildings during peak hours by shifting load to off-peak hours. This technique is particularly effective in buildings with high thermal mass, because of their large thermal energy storage capacity, and in commercial buildings due to their variable electricity pricing based on time-of-use rates. Precooling in residential buildings has been a matter of limited interest in the past because of their low thermal mass and typically uniform electricity pricing rate. While previous studies on precooling primarily focused on cost savings, an important aspect of precooling is the thermal load modulation, which could be very effective in managing peak demand in lightweight residential buildings integrated with thermal energy storage systems. In this study, we examine different precooling strategies to manage the heat gains in lightweight building walls integrated with phase-change materials. We create nine different precooling profiles by controlling the interior temperature, and then evaluate the influence of the precooling profiles on four key building energy performance parameters: total heat gain, peak heat gain, maximum heat gain during peak hours, and time at which peak occurs. To thoroughly understand the fundamental physics, we first consider hypothetical climates and obtain the optimal precooling strategy required to achieve maximum peak shedding and shifting while minimizing the total heat gains. We then extend the model to Baltimore, Maryland, and estimate the benefits of the optimized precooling strategy under real conditions. The optimal precooling strategy proposed in this study can shift the peak heat gain by up to 14 hours, thereby reducing the heat gain during peak period by up to 95%, at the expense of a 23% increase in the total heat gains.
Coastal cities offer a unique environment for studying aerosol-cloud interactions and the effects of urban emissions on cloud properties. As part of the Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE), the Partitioning Thrust by Los Alamos National Laboratory (EPCAPE-PT-LANL) was conducted. Our campaign focused on measuring the optical and chemical properties of aerosols and their interactions within marine stratocumulus clouds in La Jolla, California. EPCAPE-PT-LANL enhances the primary goals of EPCAPE through innovative observations of vapor-phase transitions between aerosols and cloud droplets, the impact of black carbon on aerosol-cloud dynamics, and the effects of cloud processing on aerosol optical properties. Instrument: Single Particle Soot Photometer (Droplet Measurements Technology) Data Notes: Contact us if you want additional data products from this instrument. Reported data is the black carbon (rBC) number and mass concentration with diagnostic flags. The SP2 measures incandescence from particles that is induced with a 1064 Nd-YAG laser. Particles that absorb the laser energy and then emit radiation is assumed to contain black carbon. The amount of intensity of radiation is related to the mass of absorbing material in the particle. Here, we calibrate the incandescence intensity to size selected Regal Black (Cabot) nebulized from solution. Data provided for the EPCAPE campaign used the combined broadband high-gain + low-gain channels (BHBL). Each channel has a lower threshold of detection equivalent to 2-s of the respective channel noise. Thresholding has been applied to select between the high-gain and low-gain channels. The detection limit is 80-540 nm (Deq) or 0.36- 55 fg. It is assumed that rBC is the only aerosol type that is in significant concentration in the sampled atmosphere that absorbs the laser energy. Particle data are integrated over 10 second windows to calculate a rBC number and mass concentration. QC/QA: • Diagnostic flags that impacted measured concentration: - Sample, Sheath, and Purge Flow Rates: Despite observing fluctuations in all flows, the rBC detection and mass quantification are generally observed to be stable, although large changes in sample flow rate did impact detection efficiency. A flag was implemented for sample flow deviations >12 cm3/min from the set point averaged over 30 seconds - Laser Power: Detection efficiency decreases with laser power and deviations in laser power also affect mass quantification. Flag for laser power is set for deviations in laser current from the set value >5 mA. - Primary Detector Threshold: Primary thresholding is the signal value which determines whether a “particle” is recorded. Thresholding errors occur when the threshold value is too HIGH and real particles are ignored. • Several periods without data: - 16-18 Nov: Ultra Zero Air generator failure, flows deviated significantly from set points. rBC # conc recovered but questionable. - 20-21 Nov: Offline for calibrations for several hours each day. - 25-27 Nov: Data is missing. - 30 Nov: Power outage 3 Dec: SP2 hard-drive full. - 3 Dec: Power Outage Header: - BHBL_NumbConc[#/cc]: Refers to the number concentration of refractory black carbon (rBC) measured from combined broadband high-gain and low-gain channels, expressed in particles per cubic centimeter. - BHBL_BCMass_Conc[ug/m3]: Refers to the mass concentration of refractory black carbon (rBC) measured from combined broadband high-gain and low-gain channels, expressed in micrograms per cubic meter. - NoData_Flag[bool]: A boolean flag that indicates whether no data was recorded during a measurement. - NoBC_Flag[bool]: A boolean flag indicating whether no black carbon particles were recorded during the measurement. - Laser_Flag[bool]: A boolean flag indicating deviations in laser current during the measurement. - SampleFlow_Flag[bool]: A boolean flag indicating deviations from the set sample flow rate during the measurement. - PrimThresh_Flag[bool]: A boolean flag indicating deviations from the set primary threshold during the measurement, potentially ignoring real particles. - Manual_Flag[bool]: A boolean flag indicating manual intervention or adjustments during the measurement. - CVI_Flag[bool]: A boolean flag indicating whether the Counterflow Virtual Impactor (CVI) was active or inactive during the measurement.
Photonic integrated circuits incorporating intersubband transitions are ideal for mid-infrared and terahertz nanophotonics. However, the design of epitaxies has long been inhibited by two factors: the modest predictivity of ab initio theory and the absence of absolute intersubband gain and loss measurements under operating conditions. Existing measurements either yield inaccurate gain profiles or do not accurately assess dependence on frequency, bias, and temperature. Here, we present a delay-resolved absolute-referencing method for accurate gain evaluation without these limitations, addressing a long-standing challenge. By creating a photonic circuit that allows broadband pulses to traverse different lengths of a gain medium, we measure the absolute transmission of intersubband structures. Gain profiles match theoretical predictions at lower temperatures, with gain and dispersion clamping after lasing, and faster-than-expected degradation occurs at higher temperatures. Our approach provides a precise experimental evaluation of temperature-dependent gain performance and gives insight into optimizing temperature performance and frequency comb designs.
Traditionally, a single-loop fixed-gain controller is applied to supply fan (SF) and cooling coil (CC) valve controls while a fixed-damper position control is applied to outdoor air (OA) damper control at air handling units (AHUs) in commercial buildings. With the increasing application of occupancy sensors, the information generated by occupancy sensors is applied to not only reduce the electricity loads from lighting and controllable plug loads, but also reset OA intake and minimum supply airflow setpoints. Meanwhile, these intermittent operation actions greatly elevate the dynamics of AHU systems, which may introduce unstable SF and CC valve operations and inaccurate OA flow control at AHUs and consequently degrade maximum energy efficiency gains. With virtual fan and valve flow meter technologies, two advanced controls, including cascade control and gain scheduling control, can be implemented on both the SF and CC valve, and an advanced control using a virtual OA flow meter can be implemented on OA damper integrated with occupancy sensors. The goal of this project is to demonstrate the savings, cost, and performance of an integrated solution that integrates the three advanced HVAC controls with occupancy sensors to allow accurate and stable AHU operations in real buildings. The project objectives are to: 1) develop and validate an advance SF control algorithm; 2) develop and validate an advanced CC valve control algorithm; 3) validate an algorithm to implement a virtual OA flow meter; and 4) demonstrate the savings, cost, and performance of the integrated solution in real buildings. The technical approaches are to: 1) select a test system at the University of Oklahoma; 2) develop and implement the algorithms of advanced SF and CC valve controls and validate the performance; 3) develop and implement the advanced OA control using a virtual OA flow meter and validate the performance; 4) demonstrate the savings, cost, and performance of the proposed integrated solution with and without three advanced HVAC controls; and 5) disseminate the project results through publications and presentations. For the SF control, both the gain scheduling and cascade controls can improve the fan energy performance by reducing the fan power during the transient period and the fan control performance at lower speeds by reducing fan speed variation. Moreover, the gain scheduling control provides a simple and low-cost solution and is recommended. The fan power savings can reach 30% in a transient period. For the CC valve control, the gain scheduling control can considerably reduce the supply air temperature oscillation range and frequency under both higher and lower load conditions and the control valve response is much more stable. As a result, the gain scheduling control is recommended. The projected pump energy consumption can be reduced by 68.5%. With the developed virtual OA flow meter, the OA can be accurately controlled at its setpoint, which is determined based on the actual number of occupants in the building provided by occupancy sensors. The RMSE of the proposed OA control is 15.9 L/s. The energy data shows that the fan power and CC cooling energy were significantly reduced. On the other hand, the energy savings majorly results from the occupancy sensors and the energy savings by the advanced HVAC controls is minimal because that the controllers in the test AHU were tuned with very slow response. An annual technical savings potential is estimated as 0.5 quads in the commercial sector.
Due to its nonlinear feature, supply air temperature control systems at air handling units using single-loop fixed gain control frequently suffer unstable response under dynamic conditions. This paper is aimed at identifying a more effective control strategy to stabilize the valve control and achieve desirable supply air temperature response under various operation conditions by evaluating three control strategies, cascade, gain scheduling and cascade plus gain scheduling controls. Firstly, a control-oriented model is developed and calibrated through open-loop tests. Then, the control issues with single-loop fixed gain control are evaluated through simulations and field tests, which indicates that the system has more aggressive response or becomes unstable under lower load conditions when the chilled-water flow rate is less than 0.1 L/s. Finally, three control strategies are proposed and evaluated. Further, the results reveal that all three proposed controls can achieve better robustness with the integral square error of supply air temperature decreased to 16%, 47% and 5%, respectively, under lower load condition. However, since high-frequency oscillation of the control valve occurs with cascade and cascade plus gain scheduling control, the gain scheduling control is recommended considering a trade-off among the supply air temperature response, valve lifetime and implementation complexity.
Abstract A Kinetic Inductance Traveling Wave Amplifier (KIT) utilizes the nonlinear kinetic inductance of superconducting films, particularly niobium titanium nitride (NbTiN), for parametric amplification. These amplifiers achieve remarkable performance in terms of gain, bandwidth, and compression power and frequently approach the quantum limit for noise. However, most KIT demonstrations have been isolated from practical device readout systems. Using a KIT as the first amplifier in the readout chain of an unoptimized microwave SQUID multiplexer coupled to a transition-edge sensor microcalorimeter, we see an initial improvement in the flux noise [1]. One challenge in KIT integration is the considerable microwave pump power required to drive the non-linearity. To address this, we have initiated efforts to reduce the pump power by using thinner NbTiN films and an inverted microstrip transmission line design. In this article, we present the new transmission line design, fabrication procedure, and initial device characterization—including gain and added noise. These devices exhibit over 10 dB of gain with a 3 dB bandwidth of approximately 5.5–7.25 GHz, a maximum practical gain of 12 dB, and typical gain ripple under 4 dB peak to peak. We observe an appreciable impedance mismatch in the NbTiN transmission line, which is likely the source of the majority of the gain ripple. Finally, we perform an initial noise characterization and demonstrate system-added noise of three quanta or less over nearly the entire 3 dB bandwidth.
Enhancing the signal-to-noise ratio in avalanche photodiodes by utilizing impact ionization gain requires materials exhibiting low excess noise factors. Amorphous selenium (a-Se) as a wide bandgap at ~2.1 eV, a solid-state avalanche layer, demonstrates single-carrier hole impact ionization gain and manifests ultralow thermal generation rates. A comprehensive study of the history dependent and non-Markovian nature of hot hole transport in a-Se was modeled using a Monte Carlo (MC) random walk of single hole free flights, interrupted by instantaneous phonon, disorder, hole–dipole, and impact-ionization scattering interactions. The hole excess noise factors were simulated for 0.1–15 μm a-Se thin-films as a function of mean avalanche gain. The hole excess noise factors in a-Se decreases with an increase in electric field, impact ionization gain, and device thickness. The history dependent nature of branching of holes is explained using a Gaussian avalanche threshold distance distribution and the dead space distance, which increases determinism in the stochastic impact ionization process. An ultralow non-Markovian excess noise factor of ~1 was simulated for 100 nm a-Se thin films corresponding to avalanche gains of 1000. Future detector designs can utilize the nonlocal/non-Markovian nature of the hole avalanche in a-Se, to enable a true solid-state photomultiplier with noiseless gain.
Colloidal semiconductor nanocrystals (NCs) have emerged as promising candidates for developing solution-processable optical gain media, with potential applications in integrated photonic circuits and lasers. However, the deployment of NCs in these technologies has been hindered by nonradiative Auger recombination of multiexciton states, which shortens the optical gain lifetime and reduces its spectral range. Here, we demonstrate that these limitations can be overcome by using giant colloidal quantum shells (g-QSs), comprising a quantum-confined CdSe shell grown over a large (~14 nm) CdS bulk core. Such bulk-nanoscale architecture minimizes exciton–exciton interactions, leading to suppressed Auger recombination and one of the broadest gain bandwidths reported for colloidal nanomaterials, spanning energies both above and, remarkably, below the bandgap. Ultrafast transient absorption and photoluminescence measurements demonstrate that the high-energy portion of optical gain arises from states containing more than 15 excitons per particle while the unusual sub-bandgap gain behaviour results from an Auger-assisted radiative recombination, a mechanism that has traditionally been viewed as a loss pathway. Altogether, these results reveal a unique gain regime associated with bulk-nanocrystal hybrid systems, which offers a promising path toward solution-processable light sources.
Background: Blood-based biomarker tests can potentially change the landscape of colorectal cancer (CRC) screening. We characterize the conditions under which blood test screening would be as effective and cost-effective as annual fecal immunochemical testing or decennial colonoscopy. Methods: We used the 3 Cancer Information and Surveillance Modeling Network–Colon models to compare scenarios of no screening, annual fecal immunochemical testing, decennial colonoscopy, and a blood test meeting Centers for Medicare & Medicaid (CMS) coverage criteria (74% CRC sensitivity and 90% specificity). We varied the sensitivity to detect CRC (74%-92%), advanced adenomas (10%-50%), screening interval (1-3 years), and test cost ($25-$500). Primary outcomes included quality-adjusted life-years (QALY) gained from screening and costs for a US average-risk cohort of individuals aged 45 years. Results: Annual fecal immunochemical testing yielded 125-163 QALY gained per 1000 at a cost of 3811-5384 dollars per person, whereas colonoscopy yielded 132-177 QALY gained at a cost of 5375-7031 dollars per person. A blood test with 92% CRC sensitivity and 50% advanced adenoma sensitivity yielded 117-162 QALY gained if used every 3 years and 133-173 QALY gained if used every year but would not be cost-effective if priced above $$125 per test. If used every 3 years, a $500 blood test only meeting CMS coverage criteria yielded 83-116 QALY gained at a cost of $8559-$9413 per person. Conclusion: Blood tests that only meet CMS coverage requirements should not be recommended to patients who would otherwise undergo screening by colonoscopy or fecal immunochemical testing because of lower benefit. Blood tests need higher advanced adenoma sensitivity (above 40%) and lower costs (below $125) to be cost-effective.
In this paper, we demonstrate a multi-parameter fiber sensing system based on stimulated Brillouin scattering in a double-Brillouin peak specialty fiber with enhanced Brillouin gain response. The amplitude level of the second Brillouin gain peak, which originated from the higher-order acoustic modes, has been improved with an approximately similar amplitude level to the first Brillouin gain peak from the fundamental acoustic mode. Compared to other multi-Brillouin peak fibers presented in the literature, the proposed fiber significantly reduces the measured Brillouin frequency shift error, thus improving strain and temperature accuracies. By utilizing the sensitivity values of the strain and temperature associated with each Brillouin gain spectrum (BGS) peak, a successful discriminative measurement of strain and temperature is performed with an accuracy of ±13 μɛ, and ±0.5 °C, respectively. The proposed double-Brillouin peak fiber appears to be a possible alternative to other multi-BGS peak fibers, for instance, large effective area fiber and dispersion compensating fibers, which are inherently accompanied by large measurement errors due to the weak Brillouin gain values originating from the higher-order acoustic modes. The demonstrated results show different strain and temperature coefficients of 47 kHz/µɛ, 1.15 MHz/°C for peak 1 and 51 kHz/µɛ, 1.37 MHz/°C for peak 2. Moreover, the enhanced BGS peak gains having nearly the same amplitude levels enable the discriminative measurement of strain and temperature. Such fibers in Brillouin interrogation eliminate the need for complex monitoring setups and reduce measurement errors. We recommend that for long-distance natural gas pipeline monitoring, where discriminative strain and temperature measurement is crucial, the proposed double-Brillouin peak fiber can be highly beneficial.