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At least 757 records · Page 42

Consequences of product inhibition in the quantification of kinetic parameters

While the potential for product inhibition in catalytic reactions is well known, the impact of neglected inhibition on measured kinetic parameters is often overlooked. The presence of product inhibition, most often caused by the competitive adsorption of products with reactants on catalytic active sites, is difficult to determine a priori for an arbitrary catalytic system. The significance of product inhibition relies on the concentration of the products, their adsorption thermodynamics on catalytically relevant sites, and process parameters such as temperature and pressure. When inhibition is significant, however, apparent activation energies and reaction orders vary from the differential-reactor apparent activation energy by a factor of 1/(1 - δ), where δ is the total inhibition order (e.g., the factor (1 - δ) = 1.6 for a system with product inhibition of -0.6 order). This is illustrated here with the kinetics of NO oxidation over Cu ion clusters (Cu x O y ) in Cu-SSZ-13, for which the product NO 2 inhibits the forward reaction. Furthermore, in the presence of inhibition, when only reactants are fed to a flow reactor or placed in a batch reactor, there is often no practical conversion that is low enough to guarantee differential behavior. Inclusion of products in the feed solves this problem, allowing accurate determination of kinetic parameters such as apparent reaction orders and activation energies. We also demonstrate that evaluation of the necessity of co-feeding products to assure measurement of differential-reactor data in a given catalytic system is straightforward from a plot of the log of the rate (or conversion) versus the log of the space time in a flow reactor or elapsed time in a batch reactor. We encourage inclusion of this test in all kinetic analyses that are reasonably approximated by power law rate expressions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Clinical characteristics and aetiological analysis of 133 patients for pulmonary embolism combined with haemoptysis

Abstract Background In the patients with pulmonary embolism (PE), PE itself can cause haemoptysis and other reasons can also cause haemoptysis. Therefore, the clinical characteristics and the causes of haemoptysis are lacking. Methods A retrospective analysis was performed that involved screening 583 PE patients and determining that haemoptysis occurred in 141 cases. Of these, eight cases were omitted due to anticoagulation‐related haemoptysis or unavailable data, leaving 133 cases that were enrolled in final analysis (127 acute and 6 chronic case of PE). We classified the acute PE patients who combined with diseases which can cause haemoptysis to non‐simple group (n = 61) and those without these diseases to simple group (n = 66). Results The incidence of haemoptysis in PE patients was 23.75%. In the simple group, the amount of haemoptysis ≤ 5 mL was 80.30% (53/66) and ≤ 20 mL was 90.91% (60/66). In the non‐simple group who combined with lung cancer, the amount of haemoptysis ≤ 5 mL was 68.4% (26/38) and ≤ 20 mL was 86.8% (33/38). Further analyses revealed that the amount of haemoptysis in the non‐simple group was larger than that in the simple group (median 5 [5‐125] vs. 5 [5‐5], p < 0.001; volume ≥ 100 mL: 29.5% vs. 6.1%, p < 0.001). Among all the PE patients, chronic thromboembolic pulmonary hypertension (CTEPH), PE combined with tuberculosis (TB) and PE combined with bronchiectasis were independent risk factors for the amount of haemoptysis ≥ 100 mL (OR = 15.00, (95% CI: 2.235‐100.652); 12.00, (3.101‐46.437); 60.00, (6.552‐549.441), respectively). Conclusions The haemoptysis caused by acute PE or PE combined with lung cancer was mild and was characterised by blood in sputum. PE combined with TB, bronchiectasis and CTEPH are associated with moderate to massive haemoptysis, with a greater risk of haemoptysis ≥ 100 mL.

Zou, Yong Wei↗

Neutrino physics beyond the current paradigm

An exciting program of international neutrino experiments aims to complete our understanding of three-neutrino mixing in the Standard Model (SM), which has had great success in describing world neutrino data. However, there exist a number of short-baseline neutrino anomalies that do not fit into this simple picture and could be pointing us instead to phenomena beyond the Standard Model (BSM). Neutrinos and neutrino experiments are excellent laboratories to search for BSM physics for a number a reasons. First, neutrinos mass itself is evidence of BSM physics as it implies the addition of new fields to the SM. In addition, neutrino properties are not well-constrained and allow sizable, new interactions. Finally, accelerator- and reactor-based short-baseline neutrino experiments bring high luminosity sources of photons, nuclear, and meson decays near large, sensitive detectors and can therefore probe a variety of dark sector models. In this talk, I will give an overview of worldwide accelerator- and reactor-based short-baseline neutrino experiments and their efforts to search for physics beyond the current paradigm.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

SAGE Intrusion Detection System: Sensitivity Analysis Guided Explainability for Machine Learning.

This report details the results of a three-fold investigation of sensitivity analysis (SA) for machine learning (ML) explainability (MLE): (1) the mathematical assessment of the fidelity of an explanation with respect to a learned ML model, (2) quantifying the trustworthiness of a prediction, and (3) the impact of MLE on the efficiency of end-users through multiple users studies. We focused on the cybersecurity domain as the data is inherently non-intuitive. As ML is being using in an increasing number of domains, including domains where being wrong can elicit high consequences, MLE has been proposed as a means of generating trust in a learned ML models by end users. However, little analysis has been performed to determine if the explanations accurately represent the target model and they themselves should be trusted beyond subjective inspection. Current state-of-the-art MLE techniques only provide a list of important features based on heuristic measures and/or make certain assumptions about the data and the model which are not representative of the real-world data and models. Further, most are designed without considering the usefulness by an end-user in a broader context. To address these issues, we present a notion of explanation fidelity based on Shapley values from cooperative game theory. We find that all of the investigated MLE explainability methods produce explanations that are incongruent with the ML model that is being explained. This is because they make critical assumptions about feature independence and linear feature interactions for computational reasons. We also find that in deployed, explanations are rarely used due to a variety of reason including that there are several other tools which are trusted more than the explanations and there is little incentive to use the explanations. In the cases when the explanations are used, we found that there is the danger that explanations persuade the end users to wrongly accept false positives and false negatives. However, ML model developers and maintainers find the explanations more useful to help ensure that the ML model does not have obvious biases. In light of these findings, we suggest a number of future directions including developing MLE methods that directly model non-linear model interactions and including design principles that take into account the usefulness of explanations to the end user. We also augment explanations with a set of trustworthiness measures that measure geometric aspects of the data to determine if the model output should be trusted.

97 MATHEMATICS AND COMPUTING↗

How Useful are Conventional I–Vs for Performance Calibration of Single- and Two-Junction Perovskite Solar Cells? A Statistical Analysis of Performance Data on ≈200 Cells from 30 Global Sources

As perovskite photovoltaics (PV) advance from the laboratory to commercial prototypes, their accurate and reliable performance testing is becoming increasingly important. The well-documented dynamic response of perovskite solar cells to an external applied voltage has led to the development of steady-state performance measurement methods; however, these methods have not been widely adopted by the perovskite PV community. A key reason for this is that steady-state measurement methods take tens of minutes to complete, as opposed to conventional "fast" current-voltage (I-V) measurements usually lasting a few seconds. Fast I-Vs arise from a snapshot, almost always not a steady-state condition of the device; however, given their widespread use, the question arises: how do performance parameters of perovskite PV compare when measured with fast I-V and with a steady-state method? Results compiled from approximately 200 perovskite PV cells, including single junction, and two-terminal perovskite-perovskite and perovskite-Si tandems, show that fast I-Vs can provide a useful measure of the open-circuit voltage of the devices, while the short-circuit current and the overall efficiency can be widely misestimated. Here, the implications of these findings on performance testing protocols are discussed and possible options for fast and accurate testing of perovskite PV are proposed.

14 SOLAR ENERGY↗

Imaging pyrometry for most color cameras using a triple pass filter

A simple combination of the Planck blackbody emission law, optical filters, and digital image processing is demonstrated to enable most commercial color cameras (still and video) to be used as an imaging pyrometer for flames and explosions. The hardware and data processing described take advantage of the color filter array (CFA) that is deposited on the surface of the light sensor array present in most digital color cameras. In this work, a triple-pass optical filter incorporated into the camera lens allows light in three 10-nm wide bandpass regions to reach the CFA/light sensor array. These bandpass regions are centered over the maxima in the blue, green, and red transmission regions of the CFA, minimizing the spectral overlap of these regions normally present. A computer algorithm is used to retrieve the blue, green, and red image matrices from camera memory and correct for remaining spectral overlap. A second algorithm calibrates the corrected intensities to a gray body emitter of known temperature, producing a color intensity correction factor for the camera/filter system. The Wien approximation to the Planck blackbody emission law is used to construct temperature images from the three color (blue, green, red) matrices. A short pass filter set eliminates light of wavelengths longer than 750 nm, providing reasonable accuracy (±10%) for temperatures between 1200 and 6000 K. The effectiveness of this system is demonstrated by measuring the temperature of several systems for which the temperature is known.

47 OTHER INSTRUMENTATION↗

To grind or not to grind? The influence of mechanical and thermal treatments on the $\mathrm{Cu/Zn}$ disorder in $\mathrm{Cu}$ 2 $\mathrm{ZnSn}$($\mathrm{S}$ x $\mathrm{Se}$ 1-x ) 4 monograins

We report that Kesterite-type based thin film solar cell technologies are mainly based on polycrystalline absorber layers. A promising low cost alternative technology uses Cu 2 ZnSn(S x Se 1-x ) 4 (CZTSSe) monograins (single crystals of 20–100 μm size) which are fixed in a polymer matrix to form a flexible solar cell. The Cu/Zn disorder is discussed as a possible reason for band tailing causing voltage losses limiting the efficiency of CZTSSe-based devices. The experimental determination of the order parameter Q which is a quantitative measure of Cu/Zn disorder, requires a differentiation between the isoelectronic cations Cu + and Zn 2+ . An in-depth analysis of neutron diffraction data allows the determination of type and concentration of intrinsic point defects including a distinction between Cu and Zn. Neutron diffraction requires large sample volumes, thus monograins offer the unique possibility to correlate structural disorder in CZTSSe with device performance parameters. In this study we tackle the influence of grinding the monograins on stoichiometry deviations, the Cu/Zn disorder as well as intrinsic point defects and optoelectronic properties of CZTSSe monograins. Moreover, an easy methodology based on Raman scattering spectroscopy is proposed for the assessment of Cu/Zn disorder in the CZTSSe compounds.

14 SOLAR ENERGY↗

Transformative Materials for High-Efficiency Thermochemical Production of Solar Fuels (Final Report)

Metal oxide-based two-step solar thermochemical (STC) H 2 O and CO 2 -splitting cycles are a promising route to convert solar thermal energy into fuels. The metal oxide materials are reduced at high temperatures (Step 1), and then at low (but still elevated) temperatures, the reduced oxide is used to split H 2 O or CO 2 (Step 2). However, current applications of these cycles are limited by the efficiency of the metal oxide materials. A lower temperature for reduction is desirable, but that brings a concomitant reduction in the driving force for gas splitting. So, designing novel, high-efficiency materials is challenging. Here, we devised and performed a joint computational-experimental project, combined with materials design strategies and high-throughput approaches with the goal to quickly discover and demonstrate novel thermochemical materials with superior properties. Our approach involves an active feedback loop between experimental and computational research. We have use our previously developed materials design map, to efficiently screen results from high-throughput first- principles computation to predict new compositions and subsequently to experimentally study the properties of novel, predicted materials. Experimental measurements of the thermodynamic properties of selected materials serve as a critical benchmark, not only in evaluating the STCH properties of synthesized compounds, but also serving as a validation dataset for computational approaches. We experimentally explored a set of predicted ABO3 perovskites and focus on obtaining high quality thermodynamic properties for validation of computational prediction of enthalpy and entropy of reduction. These thermodynamic quantities play a major role in designing materials with reduced temperatures of reduction but sufficient gas-splitting rates. Finding good validation between experimental and computational data for enthalpies of reduction, we turn to promising ABO3 materials modified by A and B site substitutions, opening an enormous combinatorial space of materials. We use our high-throughput approach to “tune in” the desired solar thermochemical (STC) properties for STC. This vast composition space can only be reasonably explored using the high-throughput approaches, both computational and experimental, of this proposal. Several promising novel oxide materials have been predicted, synthesized, and verified using our materials design approach.

08 HYDROGEN↗

Chitosan-Based Scaffolds for the Treatment of Myocardial Infarction: A Systematic Review

Cardiovascular diseases (CVD), such as myocardial infarction (MI), constitute one of the world’s leading causes of annual deaths. This cardiomyopathy generates a tissue scar with poor anatomical properties and cell necrosis that can lead to heart failure. Necrotic tissue repair is required through pharmaceutical or surgical treatments to avoid such loss, which has associated adverse collateral effects. However, to recover the infarcted myocardial tissue, biopolymer-based scaffolds are used as safer alternative treatments with fewer side effects due to their biocompatibility, chemical adaptability and biodegradability. For this reason, a systematic review of the literature from the last five years on the production and application of chitosan scaffolds for the reconstructive engineering of myocardial tissue was carried out. Seventy-five records were included for review using the “preferred reporting items for systematic reviews and meta-analyses” data collection strategy. It was observed that the chitosan scaffolds have a remarkable capacity for restoring the essential functions of the heart through the mimicry of its physiological environment and with a controlled porosity that allows for the exchange of nutrients, the improvement of the electrical conductivity and the stimulation of cell differentiation of the stem cells. In addition, the chitosan scaffolds can significantly improve angiogenesis in the infarcted tissue by stimulating the production of the glycoprotein receptors of the vascular endothelial growth factor (VEGF) family. Therefore, the possible mechanisms of action of the chitosan scaffolds on cardiomyocytes and stem cells were analyzed. For all the advantages observed, it is considered that the treatment of MI with the chitosan scaffolds is promising, showing multiple advantages within the regenerative therapies of CVD.

60 APPLIED LIFE SCIENCES↗

Implementation of an Orographic Drag Scheme Considering Orographic Anisotropy in All Flow Directions in the Earth System Model CAS‐ESM 2.0

Abstract A reasonable representation of orographic anisotropy in earth system models is vital for improving weather and climate modeling. In this study, we implement the orographic drag scheme, including 3‐D orographic anisotropy (3D‐AFD), into the Chinese Academy of Sciences Earth System Model version 2 (CAS‐ESM 2.0). Three groups of simulations named sensitivity run, medium‐range forecast, and seasonal forecast respectively are conducted using the updated CAS‐ESM model and validated against station observation and reanalysis data. These simulations are run using the three schemes—3D‐AFD scheme, the 3D orographic anisotropy scheme for the eight‐direction (3D‐8x), and the 2D isotropic scheme (2D)—to compare their performance in CAS‐ESM 2.0. Sensitivity runs show that the 3D‐AFD provide more continuous transition of calculated drag as function of wind direction than the 3D‐8x, while the drag calculated using the 2D scheme show no variation with change of wind direction. Enhanced drag in the medium range and seasonal forecast using the updated CAS‐ESM alleviates part of the winter wind speed bias over the Tibetan Plateau (TP) and the cold bias over TP and the Siberian polar region. It is shown that the 3D‐AFD scheme alleviates more bias than that of the 3D‐8x scheme (by wind speed reduction of 1 ∼ 2 m/s and temperature of 1 ∼ 2 K) especially in the seasonal forecast. The results suggest that reasonable representation of the orographic anisotropy is important in climate modeling.

Xie, Jinbo↗

Stimulated Raman Scattering Microscopy: Real-Time In-Situ Physical and Chemical Characterization of Reverse Osmosis Desalination Membrane Scaling

We introduce a stimulated Raman scattering (SRS) methodology designed for rapid, real-time, and in situ monitoring of RO membrane scaling adapted for bench-scale desalination flow cells. The methodology can provide new insights into membrane scaling dynamics by offering time-resolved reflection imaging of inorganic crystal growth, coupled with chemical identification from Raman spectral data. These capabilities allow for direct local measurement of the membrane surface area covered by different scalants as well as an approximation of the scalant volume using three-dimensional, integrated Raman intensity. The 2D and 3D SRS results obtained from CaSO 4 scaling experiments are compared to and are in reasonable agreement with those provided by confocal microscopy. The real-time physical and chemical characterization capabilities presented here could be extended to study combinations of inorganic, organic, and biological fouling. Overall, the SRS methodology represents an advancement in real-time sensing of membrane fouling that offers the potential for improved operation, lower cost, and more resilient RO membrane systems for sustainable water management.

42 ENGINEERING↗

Validation of MARS-F modeling of plasma response to RMPs using internal measurements on DIII-D

The linear resistive plasma response model is validated against the plasma internal measurement data from DIII-D edge-localized mode (ELM) control experiments with applied resonant magnetic perturbation (RMP). Considered are DIII-D discharges where the n = 1, 2, and 3 (n is the toroidal mode number) RMP field was applied. Experimental data for the plasma boundary displacement, as well as the three-dimensional (3D) pressure perturbation in the edge pedestal region, are deduced from the vertical Thomson scattering (TS) system and the horizontal charge exchange recombination (CER) system on DIII-D. The linear response model produces results that are in reasonable quantitative agreement with the DIII-D internal measurements. The plasma boundary displacement of up to 15 mm is modeled, with the pedestal pressure perturbation reaching 3 kPa. As an important insight, the larger plasma displacement measured by the vertical TS system, as compared to that measured by the horizontal CER system, is due to the contribution from the tangential component of the plasma displacement to the former. This mixing of displacement components is also found to influence the sensitivity of the CER measurement comparisons. The results of this study provide further confidence in the linear resistive plasma response model for analyzing ELM control experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Particle Physics Division Lifting Fixtures Database Restructure

In this project, a thorough investigation is conducted to determine the current placements of all lifting fixtures within the Particle Physics Division (PPD) buildings - as well as whether which ones are still operable. Briefly, the reasoning as to why these lifting fixtures must be found and the database must be updated is covered in the beginning sections of the report. Many tools and fixtures get moved around and forgotten about, and Fermilab’s systems have been updated more than a few times throughout the years, so data can get lost and forgotten about. Considering that many of these lifting fixtures have not been used in years or there is missing, impertinent information that is required by Fermilab’s modern standards and safety regulations. Lifting fixtures found at each site are measured, photographed, and logged; later analyzed to determine if they are under PPD’s purview or another department so that the respective authorities can be notified. Once maximum information is found for all the fixtures they are formatted to 2025 Fermilab standards in an easily accessible digital list for PPD employees.

Creedon, Carroll [Unlisted, US, IL]↗

Methodological challenges and new perspectives of shifting vegetation phenology in eddy covariance data

While numerous studies report shifts in vegetation phenology, in this regard eddy covariance (EC) data, despite its continuous high-frequency observations, still requires further exploration. Furthermore, there is no general consensus on optimal methodologies for data smoothing and extracting phenological transition dates (PTDs). Here, we revisit existing methodologies and present new prospects to investigate phenological changes in gross primary productivity (GPP) from EC measurements. First, we present a smoothing technique of GPP time series through the derivative of its smoothed annual cumulative sum. Second, we calculate PTDs and their trends from a commonly used threshold method that identifies days with a fixed percentage of the annual maximum GPP. A systematic analysis is performed for various thresholds ranging from 0.1 to 0.7. Lastly, we examine the relation of PTDs trends to trends in GPP across the years on a weekly basis. Results from 47 EC sites with long time series (> 10 years) show that advancing trends in start of season (SOS) are strongest at lower thresholds but for the end of season (EOS) at higher thresholds. Moreover, the trends are variable at different thresholds for individual vegetation types and individual sites, outlining reasonable concerns on using a single threshold value. Relationship of trends in PTDs and weekly GPP reveal association of advanced SOS and delayed EOS to increase in immediate primary productivity, but not to the trends in overall seasonal productivity. Drawing on these analyses, we emphasise on abstaining from subjective choices and investigating relationship of PTDs trend to finer temporal trends of GPP. Our study examines existing methodological challenges and presents approaches that optimize the use of EC data in identifying vegetation phenological changes and their relation to carbon uptake.

54 ENVIRONMENTAL SCIENCES↗

First-principles electronic structure in second-moment calculation of mode frequencies: Failure of quasiharmonic approximation in silicon

Using first-principles electronic structure calculations (local density approximation), we present second-moment calculations of the temperature dependence of the vibrational normal mode frequencies in Si up to 1500 K . The method is based on simple ensemble averages of displacements and forces and is easy to implement. These efficient calculations incorporate all interactions nonperturbatively, implicitly including all high order force constants, in contrast to typical perturbative approaches. Also in this work, we propose and apply to our classical calculations an estimated quantum correction that could be used for classical approaches other than the moments method. We compare our results to available experiments, including recent inelastic neutron scattering data and conclude that the second-moment gives the frequency shift to within a factor of 2 in contrast to quasiharmonic approaches that fail by an order of magnitude to predict the anharmonic shift. Noting the relative simplicity and speed of the calculations, we conclude that the second-moment approximation reasonably accounts for anharmonicity in a system that has been very closely studied experimentally and may reliably be applied in an exploratory way to more complex systems. Finally, we suggest that further improvement on the results could be obtained by incorporating the fourth moment, which can be implemented with little additional cost.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Nuclear suppression of coherent J / ψ photoproduction in heavy-ion ultraperipheral collisions and leading twist nuclear shadowing

We determine the nuclear suppression factor S Pb ( x ) , where x = M J / ψ 2 / W γ p 2 with M J / ψ the J / ψ mass and W γ p the photon-nucleon energy, for the cross section of coherent J / ψ photoproduction in heavy-ion ultraperipheral collisions at the Large Hadron Collider and Relativistic Heavy Ion Collider by performing the χ 2 fit to all available data on the cross section d σ A A → J / ψ A A / d y as a function of the J / ψ rapidity y and the photoproduction cross section σ γ A → J / ψ A ( W γ p ) as a function of W γ p . We find that while the d σ A A → J / ψ A A / d y data alone constrain S Pb ( x ) for x ≥ 10 − 3 , the combined d σ A A → J / ψ A A / d y and σ γ A → J / ψ A ( W γ p ) data allow us to determine S Pb ( x ) in the wide interval 10 − 5 < x < 0.05 . In particular, the data favor S Pb ( x ) , which decreases with a decrease of x in the 10 − 4 < x < 0.01 interval and can be both decreasing or constant for x < 10 − 4 . Identifying S Pb ( x ) with the ratio of the gluon distributions in Pb and the proton R g ( x , Q 0 2 ) = g A ( x , Q 0 2 ) / [ A g p ( x , Q 0 2 ) ] , we demonstrate that the leading twist approximation for nuclear shadowing provides a good description of all the data on d σ A A → J / ψ A A / d y and σ γ A → J / ψ A ( W γ p ) as well as on the experimental values for S Pb ( x ) derived from σ γ A → J / ψ A ( W γ p ) . We also show that modern nuclear parton distributions reasonably reproduce S Pb ( x ) as well. Published by the American Physical Society 2024

Guzey, V. (ORCID:0000000223938507)↗

Plateau Phenomenon in Gradient Descent Training of RELU Networks: Explanation, Quantification, and Avoidance

The ability of neural networks to provide ‘best in class’ approximation across a wide range of applications is well-documented. Nevertheless, the powerful expressivity of neural networks comes to naught if one is unable to effectively train (choose) the parameters defining the network. In general, neural networks are trained by gradient descent type optimization methods,a stochastic variant thereof. In practice, such methods result in the loss function decreases rapidly at the beginning of training but then, after a relatively small number of steps, significantly slow down. The loss may even appear to stagnate over the period of a large number of epochs, only to then suddenly start to decrease fast again for no apparent reason. This so-called plateau phenomenon manifests itself in many learning tasks. The present work aims to identify and quantify the root causes of plateau phenomenon.analysis is carried out in the setting of univariate ReLU networks. No assumptions are made on the number of neurons relative to the number of training data, and our results hold for both the lazy and adaptive regimes. Here, the main findings are: plateaux correspond to periods during which activation patterns remain constant, where activation pattern refers to the number of data points that activate a given neuron; quantification of convergence of the gradient flow dynamics; and, characterization stationary points in terms solutions of local least squares regression lines over subsets of the training data. Based on these conclusions, we propose a new iterative training method, the Active Neuron Least Squares (ANLS), characterised by the explicit adjustment of the activation pattern at each step, which is designed to enable a quick exit from a plateau. Illustrative numerical examples are included throughout.

97 MATHEMATICS AND COMPUTING↗

BrickQA: Bridging the Semantic Gap in Building Operations with Dynamic Graph Exploration

While standardized ontologies like the Brick schema address data heterogeneity in Building Automation Systems (BAS), accessing this semantic data remains a challenge as domain experts often lack the expertise to formulate complex SPARQL queries. To bridge this gap, we present BrickQA, a Large Language Model (LLM)-based framework that translates natural language into executable SPARQL queries through structured query decomposition, dynamic schema exploration, and inline validation. BrickQA utilizes an iterative reasoning agent to actively navigate graph topology through dynamic exploration actions without requiring exhaustive context injection or model fine-tuning. This approach effectively mitigates hallucinations, particularly in large-scale building knowledge graphs. Empirical evaluation on BuildingQA, a standardized benchmark, demonstrates that BrickQA significantly outperforms ReAct baselines, delivering a 0.291–0.355 absolute F1 improvement while achieving 3 × –12.7 × higher token cost-efficiency. Beyond these metrics, the framework maintains structural fidelity across heterogeneous buildings and remains resilient to ambiguous queries without requiring site-specific fine-tuning. Furthermore, a case study on operational analytics validates the framework’s capability to handle temporal and aggregation constraints, effectively transforming abstract semantic models into actionable facility management insights.1

Ko, Yun-Dam↗