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At least 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Species-specific acoustic responses by bats to ultrasonic stimuli used for reducing bat-wind turbine interactions

An unintended consequence of wind energy generation is bat fatalities caused by wind turbine blade strikes. One potential approach to reduce collision risk is to use ultrasound to create an uncomfortable or disorienting airspace around wind turbine blades. Ultrasonic deterrents (UDs) have produced mixed results in experimental field studies at commercial wind energy facilities, with effectiveness varying by species and location. It is possible that some species can alter their normal echolocation characteristics to counter the signal of UDs. Our broad objective was to maximize the effectiveness of a UD by comparing changes in echolocation characteristics during three UD frequency emissions among species, between seasons, and between sex. We hypothesized that UD emissions with frequencies most similar to each species’ echolocation characteristics would be more likely to alter the bats’ echolocation, and bat responses would vary between seasons and sex for each species. We released wild-captured bats into a 60 m × 10 m × 4.4 m (length × width × height) flight cage located in San Marcos, Texas, USA, from July to October 2020 and March to May 2021 and monitored echolocation frequencies with ultrasonic microphones. We conducted trials on Brazilian free-tailed bats ( Tadarida brasiliensis ; n = 54), cave myotis ( Myotis velifer ; n = 44), red bats ( Lasiurus blossevilli , Lasiurus borealis ; n = 41), evening bats ( Nycticeius humeralis ; n = 32), and tricolored bats ( Perimyotis subflavus ; n = 8). We found that species with high-frequency echolocation calls altered their echolocation signatures more commonly during high-frequency UD emissions, whereas low-frequency bats altered their echolocation signatures more commonly during low-frequency UD emissions. Additionally, echolocation responses varied between seasons and sexes for several species. Variations in responses may be dependent on species migratory status, differences in mating behavior and mating season, hormonal differences between sexes and seasons, and/or constraints on echolocation adaptability. Our results offer insights into the variable effectiveness of UDs at reducing bat fatalities at wind turbines and provide information for potential adjustments to UDs for improved success.

17 WIND ENERGY↗
DOE OSTI2025

Joint Factorization of QCD and QED Radiation in Lepton-Hadron Scattering

The factorization theorem plays an important role in the analysis of high energy quantum chromodynamic (QCD) processes, separating the nonperturbative hadronic interaction into the universal parton distribution functions (PDFs) and fragmentation functions (FFs) and the process-dependent interactions into short distance perturbative calculations, with any interference power suppressed. With a virtual photon exchange, lepton-hadron deep inelastic scattering (DIS) provides an electromagnetic hard probe for the partonic structure of colliding hadrons and has played an important role in the development of QCD factorization. However, the collision induced QED radiation can change the momentum of the exchanged but unobserved virtual photon, making the photon-hadron frame, where the factorization formalism for DIS and semi-inclusive DIS (SIDIS) was derived, ill defined. A new analogous factorization approach has been introduced to separate the leading power process-independent QED radiative contributions to the single photon exchange by introducing lepton distribution functions (LDFs) and lepton fragmentation functions (LFFs), while process-dependent effects are perturbatively calculated with large logarithms removed [J. High Energ. Phys. 2021, 157 (2021)]. These LDFs and LFFs are considered global, as they appear in many different interactions, such as e+e-, DIS and SIDIS, so data from experiments can be used to fit and describe these functions across a wide range of lepton scattering. In this work, I will apply this new hybrid factorization approach to lepton-hadron DIS and SIDIS. For DIS, I derive the NLO short distance perturbative contribution to the cross section and demonstrate the effects the QED radiation has on the cross section using this approach using the CTEQ parameterization for the QCD functions. As part of the SIDIS analysis, I study the cross-section in two different kinematic regions: (1) the scattered lepton and observed hadron are not near back-to-back, and (2) they are close to back-to-back, where collinear QCD factorization works for (1) and TMD QCD factorization for (2) while collinear QED factorization works for both. As part of this work, I show the effects on the SIDIS cross section using fixed order calculations for the unpolarized structure function by first showing the effect of the radiative corrections on the main kinematic variables, especially how the internal transverse momentum is significantly correlated to the external angular dependence, and then the unpolarized structure function (or cross section) with matching between the descriptions for low and high transverse momentum. This work will impact the calculations for predictions for data from COMPASS and various Jefferson Lab experiments.

Cammarota, Justin [Univ. of Kentucky, Lexington, K↗
NASA NTRSDate not supplied

PM 2.5 Concentrations over Major Metropolitan Regions Inferred from Airborne High Spectral Resolution Lidar Measurements Using Machine Learning Regression

We use measurements of near-surface aerosol backscatter, extinction, and depolarization acquired by four NASA Langley Research Center airborne High Spectral Resolution Lidars (HSRLs) to develop a machine learning regression methodology to infer PM2.5 concentrations at the surface and aloft. These airborne HSRL measurements were acquired over major metropolitan regions in the United States and Asia during more than 170 flights since 2010. Hourly surface PM2.5 measurements from the EPA air quality system and similar networks in other countries acquired within 10 km and 15 minutes of these near-surface HSRL measurements are used to train models that compute PM2.5 concentrations from the HSRL measurements. We examine several regression methods and find that exponential Gaussian Process algorithms consistently give the best performance in terms of the lowest root-mean-square (RMS) errors and the highest correlations. Model performance varies significantly depending on various combinations of HSRL aerosol measurements (e.g., aerosol backscatter, extinction, depolarization, backscatter color ratios, lidar ratios, aerosol optical thickness) and retrievals (e.g., mixed layer height, aerosol type) used in the regressions. Models that use near-surface measurements of aerosol backscatter and aerosol intensive properties such as depolarization, backscatter color ratio, and lidar ratio typically give the best performance with RMS errors around 4 mg/m3 and correlation coefficients above 0.9. HSRL measurements were often acquired when the aircraft flew systematic “raster-scan” patterns for several hours over these cities. These flight patterns enabled measurements of the spatial, temporal, and vertical variabilities in the distributions of aerosol backscatter and aerosol intensive properties and allowed us to derive the corresponding variabilities in PM2.5 concentrations. We present examples of such variabilities over urban areas in the United States as well as Asia. We describe also how the distribution of surface PM2.5 varies with aerosol type and use these retrievals to examine model simulations of surface PM2.5 in these metropolitan regions. We also discuss how this methodology may be applied to measurements from satellite lidars such as CALIOP on CALIPSO and ATLID on EarthCARE.

lidar↗
DOE OSTI2025

Floating Photovoltaic Technical Potential: A Novel Geospatial Approach on Federally Controlled Reservoirs in the United States

Floating photovoltaic generation is a rapidly expanding sector of the solar energy industry, and understanding the quantity that can feasibly be installed is a crucial step to understand its role in future energy systems. This paper presents a novel spatially explicit methology of FPV potential for federally owned and managed reservoirs in the United States that uses site-specific attributes of reservoirs to estimate available area and potential generation capacity. The analysis finds that the proportion reservoir area that is found to be available for FPV development is similar to assumed values used in previous research on average, however there is a wide variability in this proportion on a site by site basis. Potential FPV generation capacity on these reservoirs is estimated to be in the range of 861 to 1,042 GWdc depending on input assumptions, likely representing a significant portion of future US solar generation needs. This work represents an advancement in methods used to estimate FPV potential that presents many natural extensions for further research.

floating solar↗
DOE OSTI2025

Manganese concentration influences nitrogen cycling in agricultural soil

Manganese (Mn) can modulate nitrogen (N) transformations in soil, yet its role in agroecosystems remains understudied. We conducted a 51-day microcosm incubation with agricultural soils differing in long-term N history (N 0 , no added N; N 1 , added 225 kg N ha −1 for a duration of 27 years) and amended with soluble Mn at 0 (M 0 ), 50 (M 1 ), or 250 (M 2 ) mg kg −1 and Glyceria striata (Lam.) residue. In N 1 soils, Mn additions (both M 1 and M 2 ) lowered total mineral N by 25 % relative to N 1 M 0 at day 51 and reduced 51-day cumulative N₂O by 32 % (N 1 M 1 ) and 42 % (N 1 M 2 ) vs. N 1 M 0 , whereas effects in N 0 were negligible. Mn also depressed ammonia-oxidizing bacterial amoA gene transcripts at day 15 in N 1 M 2 vs. N 1 M 0 (2.5 fold change). This reduction was likely due to increased N loss via complete denitrification to N₂ through microbial pathways such as nitrate/nitrite-dependent manganese oxidation (NDMO), where bacteria directly used the added Mn 2+ to reduce nitrate (NO 3 − ) and nitrite (NO 2 − ) to N 2 or as Mn dependent-ammonia oxidation (Mnammox) where bacteria oxidized ammonium (NH 4 + ) to N 2 , using Mn oxides as electron acceptors that formed from the oxidation of the added Mn. Other contributing mechanisms may include Mn-induced N immobilization, toxicity, and changes in the microbial community. These mechanistic results indicate that background Mn availability and redox dynamics can shape nitrification–denitrification pathways under N-rich conditions. In conclusion, we highlight how native Mn pools and redox state may help explain observed variability in N losses and greenhouse gas production across agricultural soils.

Decomposition↗
DOE OSTI2022

Detecting anomalous sequences in electronic health records using higher-order tensor networks

Detecting anomalous sequences is an integral part of building and protecting modern large-scale health information technology (HIT) systems. These HIT systems generate a large volume of records of patients’ state and significant events, which provide a valuable resource to help improve clinical decisions, patient care processes, and other issues. However, detecting anomalous sequences in electronic health records (EHR) remains a challenge in healthcare applications for several reasons, including imbalances in the data, complexity of relationships between events in the sequence, and the curse of dimensionality. Conventional anomaly detection methods use the finite sequence of events to discriminate sequences. They fail to incorporate salient event details under variable higher-order dependencies (e.g., duration between events) that can provide better discrimination of sequences in their models. To address this problem, we propose event sequence and subsequence anomaly detection algorithms that (1) use network-based representations of interactions in the data, (2) account for variable higher-order dependencies in the data, and (3) incorporate events duration for adequate discrimination of the data. The proposed approach identifies anomalies by monitoring the change in the graph after the test sequence is removed from the network. The change is quantified using graph distance metrics so that dramatic changes in the network can be attributed to the removed sequence. Furthermore, the proposed subsequence algorithm recommends plausible paths and salient information for the detected anomalous subsequences. Our results show that the proposed event sequence anomaly detection algorithm outperforms the baseline methods for both synthetic data and real-world EHR data.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
NASA NTRS1984

Ground-state-energy theorem and the virial theorem of a many-particle system in d dimensions

The equivalence of Pauli's ground-state-energy theorem and the virial theorem is demonstrated for a many-particle system interacting with an interparticle potential in d dimensions at zero and finite temperatures. Pauli's theorem has an integral form in which the variable is the coupling constant e-squared, while the virial theorem has a differential form in which the variable has the number density n. The essence of the equivalence proof consists in changing the variable from n to e-squared by noting the dependence of the excess free energy on dimensionless quantities for zero-temperature and classical cases.

Iwamoto, N.↗
NASA NTRS1988

Mechanics of fatigue crack closure

Papers are presented on plasticity induced crack closure, crack closure in fatigue crack growth, the dependence of crack closure on fatigue loading variables, and a procedure for standardizing crack closure levels. Also considered are a statistical approach to crack closure determination, the crack closure behavior of surface cracks under pure bending, closure measurements on short fatigue cracks, and crack closure under plane strain conditions. Other topics include fatigue crack closure behavior at high stress ratios, the use of acoustic waves for the characterization of closed fatigue cracks, and the influence of fatigue crack wake length and state of stress on crack closure.

Newman, J. C., Jr.↗
NASA NTRS1993

Variable temperature pressure broadening of the 4(1,4)-3(2,1) transition of H2O by O2 and N2

The O2 and N2 pressure-broadening parameters of the 4(1,4)-3(2,1) rotational transition in the ground vibrational state of H2O have been measured in the temperature range between 100 and 520 K. Above 250 K the measurements were made in an equilibrium cell. Below 250 K a cell, which uses collisional cooling to circumvent the temperature limits imposed by the vapor pressure of the sample gas, was used. The data were fitted to an exponential temperature-dependence for data above 150 K with resultant n values of 0.81(3) for O2 and 0.70(3) for N2, where the entries in parentheses represent the error in the last significant figure of the parameter. Below 150 K the measured pressure-broadening parameters are smaller than those calculated using these values of n.

Goyette, Thomas M.↗
NASA NTRS1989

Internal state variable approach for predicting stiffness reductions in fibrous laminated composites with matrix cracks

A mathematical model utilizing the internal state variable concept is proposed for predicting the upper bound of the reduced axial stiffnesses in cross-ply laminates with matrix cracks. The axial crack opening displacement is explicitly expressed in terms of the observable axial strain and the undamaged material properties. A crack parameter representing the effect of matrix cracks on the observable axial Young's modulus is calculated for glass/epoxy and graphite/epoxy material systems. The results show that the matrix crack opening displacement and the effective Young's modulus depend not on the crack length, but on its ratio to the crack spacing.

Lee, Jong-Won↗
NASA NTRS1947

On the one-dimensional theory of steady compressible fluid flow in ducts with friction and heat addition

Steady, diabatic (nonadiabatic), frictional, variable-area flow of a compressible fluid is treated in differential form on the basis of the one-dimensional approximation. The basic equations are first stated in terms of pressure, temperature, density, and velocity of the fluid. Considerable simplification and unification of the equations are then achieved by choosing the square of the local Mach number as one of the variables to describe the flow. The transformed system of equations thus obtained is first examined with regard to the existence of a solution. It is shown that, in general, a solution exists whose calculation requires knowledge only of the variation with position of any three of the dependent variables of the system. The direction of change of the flow variables can be obtained directly from the transformed equations without integration. As examples of this application of the equations, the direction of change of the flow variables is determined for two special flows. In the particular case when the local Mach number m = 1, a special condition must be satisfied by the flow if a solution is to exist. This condition restricts the joint rate of variation of heating, friction, and area at m = 1. Further analysis indicates that when a solution exists at this point it is not necessarily unique. Finally it is shown that the physical phenomenon of choking, which is known to occur in certain simple flow situations, is related to restrictions imposed on the variables by the form of the transformed equations. The phenomenon of choking is thus given a more general significance in that the transformed equations apply to a more general type of flow than has hitherto been treated. (author)

HIGH-SPEED↗
DOE OSTI2025

Energy Independence of the Collins Asymmetry in 𝑝 ↑⁢ 𝑝 Collisions

The STAR experiment reports new, high-precision measurements of the transverse single-spin asymmetries for 𝜋 ± within jets, namely the Collins asymmetries, from transversely polarized 𝑝 ↑⁢ 𝑝 collisions at $\sqrt{s}$ = 510 GeV. The energy-scaled distribution of jet transverse momentum, 𝑥 T = 2⁢𝑝 T, jet /$\sqrt{s}$, shows a remarkable consistency for Collins asymmetries of 𝜋 ± in jets between $\sqrt{s}$ = 200 GeV and 510 GeV. This indicates that the Collins asymmetries are nearly energy independent, with, at most, a very weak scale dependence in 𝑝 ↑ ⁢𝑝 collisions. These results extend to high-momentum scales (𝑄 2 ≤ 3400 GeV 2 ) and enable unique tests of evolution and universality in the transverse-momentum-dependent formalism, thus providing important constraints for the Collins fragmentation functions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Conceptual Design of Pulverized Coal Electricity Generating Units for Flexible Operation

This National Energy Technology Laboratory (NETL) study addresses the conceptual design of greenfield pulverized coal (PC) plants intended for flexible rather than high capacity factor baseload operation. The United States has plentiful, low-cost natural gas resources - studies of aggressive decarbonization scenarios of the US energy sector suggest that the variability of carbon-free power can be economically addressed using dispatchable natural gas-fueled generation. Globally, natural gas resources are not as plentiful or low cost; consequently, some regions of the world are anticipated to continue to rely upon coal generation, even as they pursue decarbonization efforts. To support the increased utilization of variable renewable generation in these coal-dependent regions, plant designs must target low-capacity factor coal plants with increased emphasis on flexibility attributes such as start-up times, ramp rates, minimum load, and part-load heat rates. While much work has been performed on the improvement of the flexibility for existing coal plants originally designed for baseload service, little public literature exists on clean sheet design for flexible operation. This conceptual design study aims to define the features, performance characteristics, and costs for greenfield coal plants intended for flexible operation. Quantifying these characteristics provides critical information required by utility owners, grid planners, energy market modelers, and energy policy decision makers in coal-dependent regions of the world to better understand how coal-fired power plants can support a transition to low carbon generation.

20 FOSSIL-FUELED POWER PLANTS↗
NASA NTRS1992

Materials, structures, and devices for high-speed electronics

Advances in materials, devices, and instrumentation made under this grant began with ex-situ null ellipsometric measurements of simple dielectric films on bulk substrates. Today highly automated and rapid spectroscopic ellipsometers are used for ex-situ characterization of very complex multilayer epitaxial structures. Even more impressive is the in-situ capability, not only for characterization but also for the actual control of the growth and etching of epitaxial layers. Spectroscopic ellipsometry has expanded from the research lab to become an integral part of the production of materials and structures for state of the art high speed devices. Along the way, it has contributed much to our understanding of the growth characteristics and material properties. The following areas of research are summarized: Si3N4 on GaAs, null ellipsometry; diamondlike carbon films; variable angle spectroscopic ellipsometry (VASE) development; GaAs-AlGaAs heterostructures; Ta-Cu diffusion barrier films on GaAs; GaAs-AlGaAs superlattices and multiple quantum wells; superconductivity; in situ elevated temperature measurements of III-V's; optical constants of thermodynamically stable InGaAs; doping dependence of optical constants of GaAs; in situ ellipsometric studies of III-V epitaxial growth; photothermal spectroscopy; microellipsometry; and Si passivation and Si/SiGe strained-layer superlattices.

Woollam, John A.↗
NASA NTRS2009

The Principle of Energetic Consistency

A basic result in estimation theory is that the minimum variance estimate of the dynamical state, given the observations, is the conditional mean estimate. This result holds independently of the specifics of any dynamical or observation nonlinearity or stochasticity, requiring only that the probability density function of the state, conditioned on the observations, has two moments. For nonlinear dynamics that conserve a total energy, this general result implies the principle of energetic consistency: if the dynamical variables are taken to be the natural energy variables, then the sum of the total energy of the conditional mean and the trace of the conditional covariance matrix (the total variance) is constant between observations. Ensemble Kalman filtering methods are designed to approximate the evolution of the conditional mean and covariance matrix. For them the principle of energetic consistency holds independently of ensemble size, even with covariance localization. However, full Kalman filter experiments with advection dynamics have shown that a small amount of numerical dissipation can cause a large, state-dependent loss of total variance, to the detriment of filter performance. The principle of energetic consistency offers a simple way to test whether this spurious loss of variance limits ensemble filter performance in full-blown applications. The classical second-moment closure (third-moment discard) equations also satisfy the principle of energetic consistency, independently of the rank of the conditional covariance matrix. Low-rank approximation of these equations offers an energetically consistent, computationally viable alternative to ensemble filtering. Current formulations of long-window, weak-constraint, four-dimensional variational methods are designed to approximate the conditional mode rather than the conditional mean. Thus they neglect the nonlinear bias term in the second-moment closure equation for the conditional mean. The principle of energetic consistency implies that, to precisely the extent that growing modes are important in data assimilation, this term is also important.

Cohn, Stephen E.↗
DOE OSTI2020

Single-ion magnetism in the extended solid-state: insights from X-ray absorption and emission spectroscopy

Large single-ion magnetic anisotropy is observed in lithium nitride doped with iron. The iron sites are two-coordinate, putting iron doped lithium nitride amongst a growing number of two coordinate transition metal single-ion magnets (SIMs). Uniquely, the relaxation times to magnetisation reversal are over two orders of magnitude longer in iron doped lithium nitride than other 3d-metal SIMs, and comparable with high-performance lanthanide-based SIMs. To understand the origin of these enhanced magnetic properties a detailed characterisation of electronic structure is presented. Access to dopant electronic structure calls for atomic specific techniques, hence a combination of detailed single-crystal X-ray absorption and emission spectroscopies are applied. Together K-edge, L 2,3 -edge and Kβ X-ray spectroscopies probe local geometry and electronic structure, identifying iron doped lithium nitride to be a prototype, solid-state SIM, clean of stoichiometric vacancies where Fe lattice sites are geometrically equivalent. Extended X-ray absorption fine structure and angular dependent single-crystal X-ray absorption near edge spectroscopy measurements determine Fe I dopant ions to be linearly coordinated, occupying a D 6h symmetry pocket. The dopant engages in strong 3dπ-bonding, resulting in an exceptionally short Fe–N bond length (1.873(7) Å) and rigorous linearity. It is proposed that this structure protects dopant sites from Renner–Teller vibronic coupling and pseudo Jahn–Teller distortions, enhancing magnetic properties with respect to molecular-based linear complexes. The Fe ligand field is quantified by L 2,3 -edge XAS from which the energy reduction of 3d z 2 due to strong 4s mixing is deduced. Quantification of magnetic anisotropy barriers in low concentration dopant sites is inhibited by many established methods, including far-infrared and neutron scattering. We deduce variable temperature L 3 -edge XAS can be applied to quantify the J = 7/2 magnetic anisotropy barrier, 34.80 meV (~280 cm –1 ), that corresponds with Orbach relaxation via the first excited, M J = ±5/2 doublet. The results demonstrate that dopant sites within solid-state host lattices could offer a viable alternative to rare-earth bulk magnets and high-performance SIMs, where the host matrix can be tailored to impose high symmetry and control lattice induced relaxation effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Neural chaos: A spectral stochastic neural operator

Building surrogate models for operators with uncertainty quantification capabilities is essential for many engineering applications where randomness–such as variability in material properties, boundary conditions, and initial conditions–is unavoidable. Polynomial Chaos Expansion (PCE) is widely recognized as a go-to method for constructing stochastic surrogates in both intrusive and non-intrusive ways, and it has recently been used in the context of operator learning. However, its application becomes challenging for complex or high-dimensional processes, as achieving accuracy requires higher-order polynomials, which can increase computational demand and/or the risk of overfitting. Furthermore, PCE requires specialized treatments to manage random variables that are not independent, and these treatments may be problem-dependent or may fail with increasing complexity. Here, in this work, we adopt the same formalism as the spectral expansion used in PCE; however, we replace the classical polynomial basis functions with neural network (NN) basis functions to leverage their expressivity. To achieve this, we propose an algorithm that identifies NN-parameterized basis functions in a purely data-driven manner, without any prior assumptions about the joint distribution of the random variables involved, whether independent or dependent, or about their marginal distributions. The proposed algorithm identifies each NN-parameterized basis function sequentially, ensuring they are orthogonal with respect to the data distribution. The basis functions are constructed directly on the joint stochastic variables without requiring a tensor product structure or assuming independence of the random variables. This approach may offer greater flexibility for complex stochastic models, while simplifying implementation compared to the tensor product structures typically used in PCE to handle random vectors. This is particularly advantageous given the current state of open-source packages, where building and training neural networks can be done with just a few lines of code and extensive community support. We demonstrate the effectiveness of the proposed scheme through several numerical examples of varying complexity and provide comparisons with classical PCE.

Polynomial chaos expansion↗
DOE OSTI2026

Structural Propensities in Cs2MBiX6 (M=Na, Ag; X=Cl, Br) Bismuth Halide Double Perovskites

A previously unreported low-temperature phase transition in the bismuth halide double perovskite Cs2AgBiCl6 is reported, thereby establishing trends in the structural ground state across Cs2NaBiCl6, Cs2AgBiCl6, and Cs2AgBiBr6. Using the combined toolkit of variable-temperature synchrotron X-ray and neutron powder diffraction, Raman spectroscopy, and density-functional theory–based electronic structure modeling, we demonstrate a cubic Fm¯3m → tetragonal I4/m transition upon cooling with distinct onset temperatures. Neutron powder diffraction refinements permit the unambiguously assignment of the low-temperature phase of Cs2NaBiCl6 to I4/m, correcting prior reports of an I4/mmm ground state. Cs2AgBiCl6 is also found to transforms to a structure crystallizing in the I4/m space group at low temperatures. Temperaturedependent Raman data and density-functional theory-based modeling capture the softening and freezing of out-of-phase octahedral-tilt modes and quantify relative instabilities. Solid-state nuclear magnetic resonance spectroscopy at room temperature completes the characterization and helps underpin the subtle differences in covalency across the compounds. Trends in the phase transition temperature Ts and tilt magnitudes emerge from coupled effects of halide identity, M(I)–site bonding character, and a mismatch between interatomic distances. These results establish the structure– dynamics–bonding framework for tuning tilt-driven instabilities in halide double perovskites.

Tian, Haowen↗