Energy Measurements Research Articles

Status of LET assessment with active and passive detectors in ion beams

This review explores current experimental methods for determining the radiation quality in ion beams. In this context, radiation quality is commonly evaluated using the averaged linear energy transfer (LET), a metric employed to assess the response of both biological and physical systems. Dose and averaged LET can be experimentally determined with passive detectors through various techniques that have seen recent improvements. Another metric related to the LET is the mean lineal energy, which is measurable using microdosimetric detectors. This review focuses on the available possibilities for evaluating the radiation quality using three microdosimeters (mini-TEPC, Silicon Telescope, and SOI Microplus), three passive luminescence detectors (based on optical, thermo-, and radiophoto-luminescence), three track-based detectors (track-etched detector, Timepix, fluorescent nuclear track detector), and a chemical detector based on alanine. A comparison of detector properties is provided along with an overview of the underlying mechanisms enabling LET assessment or measurements of the mean lineal energy with each detector type. Finally, this review summarizes the current possibilities of LET determination with respect to the needs for quality assurance in particle therapy. Areas for future research and development are suggested.

Thermometry with a dissipative heavy impurity

Improving the measurement precision of low temperature is significant in fundamental science and advanced quantum technology application. However, the measurement precision of temperature T usually diverges as T tends to zero. Here, by utilizing a heavy impurity to measure the temperature of a Bose gas, we obtain the Landau bound to precision δ2T∝T2 to avoid the divergence. When the initial momentum of the heavy impurity is close to be fixed and nonzero, the measurement precision can be δ2T∝T3 to break the Landau bound. We derive the momentum distribution of the heavy impurity at any moment and obtain the optimal measurement precision of the temperature by calculating the Fisher information. As a result, we find that increasing the expectation value P0 and reducing the variance Δ/2 of the initial momentum can help to improve the measurement precision. Moreover, under certain conditions, Δ/P0 is a relevant parameter, the smallness of which helps improve the thermometric precision of the probe. In addition, the momentum measurement is the optimal measurement of the temperature in the case that the initial momentum is close to be fixed and not equal to zero. The kinetic energy measurement is the optimal measurement in the case that the expectation value of the initial momentum is close to zero. Finally, we obtain that the temperatures of two Bose gases can be measured simultaneously. The simultaneous measurement precision is proportional to T2 when two temperatures are close to T. Published by the American Physical Society 2024

Predissociation-based measurements of bond dissociation energies: US2, OUS, and USe.

The uranium-containing molecules US2, OUS, and USe have been investigated using a pulsed laser ablation supersonic beam molecular source with time-of-flight mass spectrometric detection. Spectra have been recorded using the resonant two-photon ionization method over the spectroscopic range from 277 to 238nm. These species have a myriad of excited electronic states in this spectroscopic region, leading to spectra that are highly congested and appear quasicontinuous. Sharp predissociation thresholds are observed, allowing precise bond dissociation energies to be measured. In the case of the triatomic molecules, it was necessary to use one laser for excitation and a delayed laser for ionization in order to observe a sharp predissociation threshold that allowed a precise bond dissociation energy to be measured. The resulting thermochemical values are D0(SU-S) = 4.910 ± 0.003eV, D0(OU-S) = 5.035 ± 0.004eV, and D0(USe) = 4.609 ± 0.009eV. These results provide the first measurement of D0(USe) and reduce the error limits in the previous values of D0(SU-S) and D0(OU-S) by a factor of more than 70.

Accuracy and Precision of the Geopyörä Breakage Test

The Geopyörä breakage test uses two counter-rotating wheels to nip and crush rock specimens with a tightly controlled gap between rollers. This paper presents the detailed measures conducted to evaluate the accuracy and precision of energy measurements across various ore types using the Geopyörä. Force measurement was assessed just for its precision. The outputs were compared directly to the drop weight test (DWT) measures of fragmentation at the same energy and fitted A and b parameters. Test reproducibility was evaluated using a Round-Robin methodology, testing several samples in multiple laboratories. The results confirmed that the new test has sufficient accuracy to match DWT results and excellent precision to assure reproducibility.

Short-Term Energy Forecasting to Improve the Estimation of Demand Response Baselines in Residential Neighborhoods: Deep Learning vs. Machine Learning

Promoting flexible energy demand through response programs in residential neighborhoods would play a vital role in addressing the issues associated with increasing the share of distributed solar systems and balancing supply and demand in energy networks. However, accurately identifying baseline-related energy measurements when activating energy demand response events remains challenging. In response, this study presents a deep learning-based, data-driven framework to improve short-term estimates of demand response baselines during the activation of response events. This framework includes bidirectional long-term memory (BiLSTM), long-term memory (LSTM), gated recurrent unit (GRU), convolutional neural networks (CNN), deep neural networks (DNN), and recurrent neural networks (RNN). Their performance is evaluated by considering different aggregation levels of the demand response baseline profile for 337 dwellings in the city of La Rochelle, France, over different time horizons, not exceeding 24 h. It is also compared with fifteen traditional statistical and machine learning methods in terms of forecasting accuracy. The results demonstrated that deep learning-based models, compared to others, significantly succeeded in minimizing the gap between the actual and forecasted values of demand response baselines at all different aggregation levels of dwelling units over the considered time-horizons. BiLSTM models, followed by GRU and LSTM, consistently demonstrated the lowest mean absolute percentage error (MAPE) in most comparison experiments, with values up to 9.08%, 8.71%, and 9.42%, respectively. Compared to traditional statistical and machine learning models, extreme gradient boosting (XGBoost) was among the best, with a value up to 11.56% of MAPE, but could not achieve the same level of forecasting accuracy in all comparison experiments. Such high performance reveals the potential of the proposed deep learning approach and highlights its importance for improving short-term estimates of future baselines when implementing demand response programs in residential neighborhood contexts.

Development and experimental assessment of a multi-annual energy monitoring tool to support energy intelligence and management in telecommunication industry

Carbon-footprint reduction of key industrial buildings is addressed, by proposing methodologies for continuously monitoring telecommunication (TLC) central offices (COs). Main aim is classifying sites according to their efficiency and reliability, via the diagnosis of anomalous electricity consumptions. Such a goal is achieved through the definition of new key performance indicators (KPIs) based on TLC and cooling energy demand, improving the outcomes of pre-existing methods. While the reliability index and index of cluster reliability are specifically proposed to evaluate and physically assess the impact of climate control (CLC, i.e., the parasitic quota) electricity consumption with respect to the TLC one, the here introduced coefficient of variation of telecommunication energy allows for a more solid evaluation of energy measurements reliability. Another target of this study is to extend the afore-mentioned KPIs-based analysis to multi-annual periods of monitoring, thus allowing successfully meeting the currently in-force ISO 50001 standard. Specific central offices were then selected and analyzed to verify the results physical meaning. The method was proven effective in classifying central offices belonging to climate-homogenous fleets, according to the reliability level estimated over a triannual timeframe. Positive impacts in terms of attainable energy saving through improved thermal management, as well as methodology extendibility to other industrial sectors are finally presented and discussed.

Radioluminescence Dosimetry in Modern Radiation Therapy

Accurate and precise measurement of radiation energy delivered to and absorbed by the patient's tissue is of great importance in radiation therapy (RT) quality assurance. Radioluminescence (RL) dosimetry has shown great potential for high spatiotemporal resolution dose measurement of RT fields. Implementation of efficient RL dosimetry in RT requires multidisciplinary effort and skills in optics, medical physics, radiation physics, electronics, and imaging science. In this review, a wide overview of fundamentals and applications of RL properties of media for RT dosimetry with emphasis on their potential use for multidimensional, small‐field, and ultra‐high dose rate RT dosimetry is provided.

Deformation-induced CPT violation in entangled pairs of neutral kaons

In this paper we consider description of kaon-antikaon interference in the context of a theory with deformed CPT symmetry. In the case of such theoretical models, deviations from the standard CPT invariance is related to the momentum carried by the particles; in particular the rest masses of particles and antiparticles are equal. We find that the decay intensity of kaon-antikaon pair has three contributing terms: the correct-parity, the wrong-parity, and the interference between them, all of which are affected by deformation. Using the fact that the presence of such terms was not observed we estimate, under plausible assumptions, the magnitude of deformation parameter κ≳1017 GeV at the LHC energy. This limit can be possibly improved to values closer to the expected Planck mass scale κ≳1018 GeV using a next-generation collider with energy larger by an order of magnitude. This raises hopes that the effect, if it exists, could be detected in future accelerator experiments. Uncertainties of the energy measurement and time resolution are important for accuracy of these predictions. Published by the American Physical Society 2024

Analysis and Comparison of Three Bending Tests on Phosphogypsum-Based Material According to Peridynamic Theory

Phosphogypsum-based materials have gained much attention in the field of road infrastructure from the economic and sustainable perspectives. The Three-point bending test, the Four-point bending test and the Semi-circular bending test are three typical test methods applied for fracture energy measurement. However, the optimal test method for fracture energy evaluation has not been determined for phosphogypsum-based materials. To contribute to the gap, this study aims to analyze and compare the three test methods for fracture energy evaluation of phosphogypsum materials based on the peridynamic theory. For this purpose, the load–displacement, vertical displacement–Crack Mouth Opening Displacement (CMOD) and fracture energy of the phosphogypsum-based materials were measured and calculated from the three test methods. The simulated load–displacement and vertical displacement–CMOD by PD numerical models, with different fracture energy as inputs, were compared to the corresponding tested values according to simulation error results. The results showed that the Four-point bending test led to minimized errors lower than 0.189 and indicators lower than 0.124, demonstrating the most optimal test method for the fracture energy measurement of phosphogypsum-based material. The results of this study can provide new methodological references for the selection of material fracture energy measurement tests.

Optimization of fast output from SiPM array for pulse shape discrimination techniques at high counting rates

Plastic scintillators with pulse shape discrimination (PSD) capability, when combined with silicon photo-multipliers (SiPMs), enable the development of compact neutron detectors with lower power consumption and insensitivity to magnetic fields. However, the SiPM array has a significantly large pulse width of the output signal, which leads to discrimination difficulties at high counting rates. There are two outputs of a SiPM array: a standard output for energy measurement and a fast output for timing measurement. The pulse width of the standard output signal is in the range of hundreds nanoseconds, while the pulse width of the other one is in the range of tens nanoseconds. Fast output signals have traditionally been considered suitably for fast timing, however utilizing them for PSD has been little explored. In our previous work, we successfully implemented PSD by using fast output signals from a SiPM. Despite the obvious negative overshoot in fast signals, we achieved PSD of fast signals by using longer sampling times. However, this approach was still limited at high counting rates. This study proposes a compensation network for fast output signals, which is composed of a compensation unit consisting of a resistor and a capacitor. This design effectively compensates the overshoot of the fast output and shortens the pulse width from 60 ns to 44 ns. Additionally, it highlights the frequency amplitude differences between the neutron and gamma signals from fast output in the high-frequency component, thus improving the PSD capability of the fast output.

Optical simulation of a quantum cooling engine powered by entangled measurements

Traditional refrigeration is driven either by external forces or by the information-feedback mechanism. Surprisingly, quantum measurement and collapse, typically viewed as detrimental, can also power a quantum cooling engine without requiring any feedback mechanism. In this work, we perform a proof-of-principle demonstration of quantum measurement cooling (QMC) powered by entangled measurements using a highly controllable linear optical simulator. The simulator can simulate qubits with different energy-level spacings and their thermalizing processes at different temperatures, and also allows for arbitrary projections of two qubits at different energy levels. We show the effect of changes in energy levels and measurement bases on the cooling process and demonstrate the robustness of QMC. These results reveal the special role of entangled measurements in quantum thermodynamics, indicate that quantum measurement is not always detrimental but can be a valuable thermodynamic resource. Our setup also offers a highly controllable simulation platform for multiqubit quantum engines.

Advancing industrial building energy measurement and verification (M&V) with deep learning: Evaluating data size and feature selection impact

This study explores the potential of advancing industrial building energy Measurement and Verification (M&V) using Deep Learning techniques, with a focus on the impact of data size and feature selection methods on model performance. Traditional M&V practices in the industry require extensive datasets, typically spanning 24 months, to ensure accurate energy savings verification post energy conservation measures (ECMs). This research challenges the norm by investigating whether a condensed four-month dataset could suffice for reliable M&V, thereby accelerating the verification process which is crucial for industrial applications. Utilizing a dataset with 30-minute intervals, the study first applies multi-linear regression across twelve feature selection methods to identify the most effective techniques based on a comprehensive set of performance metrics including Training Time, RMSE, MAE, R-squared, CVRMSE, NMBE, Mean MSE (via k-fold cross-validation), and the Standard Deviation of MSE (over 10-fold cross-validation). The top three methods—LASSO regression, Sequential Feature Selector, and Recursive Feature Elimination—were further analyzed as input features for a Deep Neural Network (DNN) model. The DNN’s performance was evaluated across varying data sizes (20 %, 40 %, 50 %, 60 %, 80 %, and 100 %) and configurations ranging from one to ten hidden layers. The findings reveal that LASSO regression, when integrated with DNN, consistently outperforms in terms of CVRMSE and NMBE metrics across different data sizes and model complexities. Notably, increasing the dataset size from 20 % to 80 % markedly improves the model’s predictive accuracy, underscoring the significance of larger datasets in enhancing DNN generalization and performance. Additionally, the study highlights a critical trade-off in DNN architecture: while models with fewer hidden layers (1–3) show greater performance variability in smaller datasets, increasing the number of layers does not linearly translate to better performance, illustrating the nuanced balance between model complexity and efficacy. This research contributes to the energy M&V field by demonstrating that shorter duration datasets, previously considered insufficient, can indeed provide accurate energy savings verification when analyzed with advanced deep learning techniques. This advancement not only paves the way for quicker, more efficient M&V processes in industrial settings but also offers valuable insights into the optimization of DNN models for energy data analysis.

Spatiotemporal walk-off and improved focusing of plasma THz sources.

High-field THz sources with peak field strengths exceeding MV/cm are essential for nonlinear THz spectroscopy and coherent control of matter on ultrafast time scales. Two-color femtosecond laser plasma sources employing long filamentation have been reported as providing single-cycle, >MV/cm fields, with multi-decade spanning bandwidth and polarization control, making them promising sources for such experiments. In this work, we report the observation of spatiotemporal spreading of the THz pulse when standard off-axis parabolic mirrors are used for collection and focusing of long filament plasma-based THz pulses. This produces a flying focus for THz light, with the axial focal region propagating at a velocity of 1/3 the speed of light. The THz emission is then subsequently spread over a temporal width of ∼10 ps, approximately 100 times the THz pulse duration detected by electro-optic sampling at any single point along the focus. The consequences of this non-ideal focusing are a potential and drastic overestimation of the peak THz electric field based on energy measurements, as well as significant phase noise arising from beam pointing fluctuations. We show that this spatiotemporal spreading can be minimized using a simple axicon lens that perfectly collimates the extended filament source, resulting in improved spatial and temporal focusing of the THz pulse.

Substrate controlled hydrophobicity of the Y2O3 films

The development of hydrophobic surfaces is an important factor for clean energy production from solar arrays, enabling their operation at the highest possible efficiencies for the longest possible time, without the need for physical intervention. This work reports the development of hydrophobic Y2O3 thin films on a range of transparent glass substrates. The growth of the Y2O3 films from the mono-hydrate yttrium (III) complex of 1,3-diphenyl-1,3-propanedione [Y(dbm)3(H2O)] is studied using the aerosol-assisted chemical vapor deposition (AACVD) technique. The qualitative evaluation of the deposited films and their hydrophobicity is assessed using several materials characterization techniques, such as scanning electron microscopy, grazing incident X-ray diffraction, Fourier-transform infrared, X-Ray photoelectron spectroscopy, in addition to a surface free energy and water contact angle measurements. This work demonstrates experimentally a relationship between the Y2O3 wettability and its physico-chemical characteristics in terms of surface energy, chemical composition, and morphology which is controlled by the type of glass support used. The water contact angle of the hydrophobic Y2O3 coating grown on the F-doped tin oxide glass reached 128°; currently the first deposited on transparent glass. This film exhibits the highest WCA reported up to date without the need for performing post-reaction surface treatment processes. The hydrophobic nature of the transparent Y2O3 films marks a significant leap forward in the field of anti-soiling coatings suitable for photovoltaic technology.

Effects of surface treatments for the adhesion improvement between Cu and SiCN in BEOL interconnect

This study focuses on the enhancement of interfacial reliability between Cu interconnects and silicon carbon nitride (SiCN) capping layers in semiconductor packaging structures through pre-deposition surface treatments. We compare three distinct treatments combined with H2 plasma, NH3 plasma, and SiH4 gas inflow, evaluating their effectiveness through quantitative measurement of interfacial adhesion energy using a double cantilever beam (DCB) fracture mechanics test. The results exhibit a remarkable adhesion energy improvement of over 1150 % with the addition of SiH4 gas treatment. Thorough investigations reveal that the mechanism of the exceptional adhesion enhancement is attributed to unique chemical bonding and fracture behavior. In other words, Si atoms in the SiH4 gas treatment incorporate onto Cu surfaces with specific crystallographic orientations, resulting in significantly stronger Cu–Si bonding in selective regions compared to other bondings. Moreover, the crystallographic-orientation-dependent bonding characteristic induces crack kinking at grain boundaries, dissipating the crack propagation energy. This work will provide crucial insight into enhancing the interfacial reliability and manufacturing yield of semiconductor devices.

Measurement ofenergy availability in highly trained male endurance athletes and examination of its associations with bone health and endocrine function.

Despite the introduction of Relative Energy Deficiency in Sport (RED-s) in 2014, there is evidence to suggest that male endurance athletes still present with a high prevalence of low energy availability (LEA). Previous findings suggest that energy availability (EA) status is strongly correlated with impairments in endocrine function such as reduced leptin, triiodothyronine (T3), and insulin, and elevated bone loss. This study aimed to report the current EA status, endocrine function and bone health of highly trained Irish male endurance athletes. In this cross-sectional study, participants (n = 3 triathletes; n = 10 runners) completed a 7-day testing period during the competition season using lab-based measures, to ascertain EA status, hormone level and rates of bone metabolism. Serum blood samples were obtained to assess hormone levels and markers of bone metabolism. Mean EA was < 30kcal/kg lean body mass (LBM)/day in 76.9% of athletes. There was a strong association between LEA and low carbohydrate intake, and lower LBM. Mean levels of insulin, IGF-1 and leptin were significantly lower than their reference ranges. Elevated mean concentrations of β-CTX and a mean P1NP: β-CTX ratio < 100, indicated a state of bone resorption. The EA level, carbohydrate intake, hormone status and bone metabolism status of highly trained male endurance athletes are a concern. Based on the findings of this study, more frequent assessment of EA across a season is recommended to monitor the status of male endurance athletes, in conjunction with nutritional education specific to EA and the associated risks.

From 3D to 5D tracking: SMX ASIC-based double-sided micro-strip detectors for comprehensive space, time, and energy measurements

We present the recent development of a lightweight detector capable of accurate spatial, timing, and amplitude resolution of charged particles. The technology is based on double-sided double-metal p+ – n – n+ micro-strip silicon sensors, ultra-light long aluminum-polyimide micro-cables for the analogue signal transfer, and a custom-developed SMX read-out ASIC capable of measurement of the time (Δt ≲ 5 ns) and amplitude. Dense detector integration enables a material budget > 0.3 % X 0. A sophisticated powering and grounding scheme keeps the noise under control.In addition to its primary application in Silicon Tracking System of the future CBM experiment in Darmstadt, our detector will be utilized in other research applications.

An investigation of acoustic cues to tonal registers and voicing in Donglei Kama).

The Kam language has experienced historical tonal splits, resulting in the development of a complex tonal system. However, there is still limited knowledge regarding the acoustic characteristics associated with aspiration-based tone splitting. This study aims to investigate the acoustic cues related to the tonal registers and laryngeal configurations in Donglei Kam, a dialect of Southern Kam. Sixteen native speakers of Donglei Kam participated, producing lexical tones. Statistical analyses were conducted to examine the acoustic distinctions between tonal registers, using measurements of voice onset time, spectral tilt, noise, and energy. The results indicated that Donglei Kam retained a two-way contrast of aspiration, albeit with a trend toward gradual loss. Additionally, a breathy voice was detected in the Ciyin tonal register, characterized by elevated spectral tilt values and spectral noise throughout the vowels. Moreover, machine learning classifiers effectively identified tonal registers using voice-quality data, suggesting that the phonation contrast between breathy and modal voice could contribute to the tonal split alongside pitch contrast. In summary, these findings enhance our understanding of the acoustic implementation of breathiness in Kam and offer valuable insights into the role of laryngeal contrast in tonal splits.

Berry curvature signatures in chiroptical excitonic transitions

The topology of the electronic band structure of solids can be described by its Berry curvature distribution across the Brillouin zone. We theoretically introduce and experimentally demonstrate a general methodology based on the measurement of energy- and momentum-resolved optical transition rates, allowing to reveal signatures of Berry curvature texture in reciprocal space. By performing time- and angle-resolved photoemission spectroscopy of atomically thin WSe 2 using polarization-modulated excitations, we demonstrate that excitons become an asset in extracting the quantum geometrical properties of solids. We also investigate the resilience of our measurement protocol against ultrafast scattering processes following direct chiroptical transitions.

ASSESSMENT OF THE LEVEL OF ENERGY EFFICIENCY OF A SCHOOL TAKING INTO ACCOUNT THE USE OF LOCAL RENEWABLE ENERGY SOURCES

Energy efficiency is one of the key topics that have become very relevant in recent years. In buildings, as the final consumers of energy, the greatest potential for energy saving is concentrated. And at the same time, an important component of energy efficiency is the optimal use of energy resources, where the lion's share falls on the consumption of thermal energy. In this context, heating schedules become an important tool for achieving this goal. In this article, the authors investigate the energy efficiency of different heating and ventilation modes for a school located in two climatic zones of Ukraine: I (Kyiv) and II (Odesa). Using the Design-Builder software, which is based on the EnergyPlus model, the authors model five intermittent modes for the heating and ventilation system. The authors also compare the energy efficiency of different heat sources: a boiler on biofuel, a heat pump and a solar panel. It was found that the introduction of heating modes according to the schedules allows to reduce energy consumption for heating by 10 % to 20 % depending on the mode and climatic zone, and the use of renewable energy sources based on the introduction of intermittent heating and ventilation modes for the school shows efficiency at 79 %-80 %. The authors also analyze the impact of thermomodernization of enclosing structures on the energy efficiency of buildings. The conclusion on the introduction of intermittent heating modes for non-insulated buildings is an extremely effective measure for energy saving, and the impact of the measure on energy saving of the building will be noticeable even after thermal insulation. The implementation of all improvements allows reducing energy consumption for heating by 90 %.