Optimal Experimental Design for Prediction Using Data Consistent Inversion
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Wildey, Timothy Michael↗
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Results for “inverse prediction”
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Computing Effects Of Hypervelocity Impacts On A Spacecraft
MLITEMP computer program is design software tool utilizing empirical equations to predict damage and thermal effects of impacts of hypervelocity particles on spacecraft. Three different techniques used: "inverse-R" prediction, polynomial-function prediction, and nondimensional-parameter prediction. Written in BASIC.
Rule, William K.↗
Current distribution monitoring enables quench and damage detection in superconducting fusion magnets
Abstract Fusion magnets made from high temperature superconducting ReBCO CORC ® cables are typically protected with quench detection systems that use voltage or temperature measurements to trigger current extraction processes. Although small coils with low inductances have been demonstrated, magnet protection remains a challenge and magnets are typically operated with little knowledge of the intrinsic performance parameters. We propose a protection framework based on current distribution monitoring in fusion cables with limited inter-cable current sharing. By employing inverse Biot-Savart techniques to distributed Hall probe arrays around CORC ® Cable-In-Conduit-Conductor (CICC) terminations, individual cable currents are recreated and used to extract the parameters of a predictive model. These parameters are shown to be of value for detecting conductor damage and defining safe magnet operating limits. The trained model is then used to predict cable current distributions in real-time, and departures between predictions and inverse Biot-Savart recreated current distributions are used to generate quench triggers. The methodology shows promise for quality control, operational planning and real-time quench detection in bundled CORC ® cables for compact fusion reactors.
47 OTHER INSTRUMENTATION↗
Use of Inverse Reinforcement Learning for Identity Prediction
We adopt Markov Decision Processes (MDP) to model sequential decision problems, which have the characteristic that the current decision made by a human decision maker has an uncertain impact on future opportunity. We hypothesize that the individuality of decision makers can be modeled as differences in the reward function under a common MDP model. A machine learning technique, Inverse Reinforcement Learning (IRL), was used to learn an individual's reward function based on limited observation of his or her decision choices. This work serves as an initial investigation for using IRL to analyze decision making, conducted through a human experiment in a cyber shopping environment. Specifically, the ability to determine the demographic identity of users is conducted through prediction analysis and supervised learning. The results show that IRL can be used to correctly identify participants, at a rate of 68% for gender and 66% for one of three college major categories.
Hayes, Roy↗
A spall and diffraction study of nanosecond pressure release across the iron ε-α phase boundary
The extreme response of polycrystalline iron at high pressures and high strain rates is revealed by means of high-power laser pulses. The compression portion of the pulse coupled with x-ray diffraction identifies the expected body-centered cubic (α) to hexagonal close packed (ε) displacive transformation. Upon release, observation shows that the complete reverse transformation takes approximately 8 ns and that the structure returns to its initial microstructural configuration, in a reversible transformation path. This is in good agreement with molecular dynamics (MD) simulations which predict an inverse dependence between transformation time and strain rate. The grain size is reduced from μm to nm range during compression and begins increasing back to the original grain size on decompression. The kinetics of the transition is dictated by heterogenous nucleation as it follows the Johnson-Mehl-Avrami-Kolmogorov equation with the appropriate time exponent of ~1. This is confirmed by MD simulations which also identify profuse twinning and dislocation generation. Here, the tensile pulse generated upon reflection at the free surface is captured by time-resolved free surface velocity measurements from which a peak tensile stress of 7 GPa is obtained, in stark contrast with its quasi-static value of ~200 MPa. At these strain rates, the strength of grain interiors, which is determined by twinning and slip exceeds the strength of the boundaries, and failure initiates preferentially in the latter.
36 MATERIALS SCIENCE↗
Generalizable machine learning potentials for quantum-accurate predictions of non-equilibrium behavior in 2D materials
Machine learning interatomic potentials (ML-IAPs) are emerging as transformative tools in materials modeling, promising quantum-level accuracy at a fraction of the computational cost. However, their ability to generalize beyond equilibrium configurations and to reliably capture defect- and temperature-driven behavior remains underexplored. Here, we develop and benchmark two state-of-the-art ML-IAPs, Spectral Neighbor Analysis Potential (SNAP) and Allegro, on a comprehensive dataset for monolayer MoSe₂. Using density functional theory (DFT) as the reference, we evaluate their performance in capturing stress–strain behavior, phase transition energetics, defect evolution, edge stability, and fracture toughness. Allegro, a deep equivariant neural network potential, surpasses both SNAP and the classical Tersoff potential in accuracy, efficiency, and transferability. Importantly, both ML potentials accurately reproduce experimental fracture measurements and ab initio predictions of inversion domain formation—phenomena well beyond their training sets. Our findings establish ML-IAPs as viable replacements for traditional force fields in the study of non-equilibrium mechanical phenomena, enabling large-scale, high-fidelity simulations in 2D materials and beyond. In conclusion, this work provides a broadly applicable framework for data-driven modeling of structural and functional transformations under extreme conditions.
2D materials↗
Synthesis and Characterization of Radio-Halogenated Talazoparib Analogues for Imaging and Radioligand Therapy
Abstract Talazoparib (TZ) is a potent poly(ADP-ribose) polymerase 1/2 (PARP1/2) inhibitor that uniquely traps PARP complexes at sites of single-strand DNA damage thereby offering opportunities for targeted radioligand therapy. Radiolabeled halogenated TZ derivatives were synthesized using boronic ester precursors to enable incorporation of diagnostic and therapeutic radionuclides: 18F for PET imaging, 77Br for Auger electron radiotherapy, and 211At for targeted alpha radiotherapy. Copper-mediated radio-halogenation afforded racemic 18F-TZ, 77Br-TZ, and 211At-TZ in sufficient radiochemical yields (4.3 ± 2.6%, n = 33; 29.0 ± 12.0%, n = 4; 3.6 ± 3.8%, n = 9, respectively), ∼99% radiochemical purity and proven stability under formulation conditions. Molecular dynamics simulations of halo-TZ derivatives predicted an inverse relationship between halogen size and PARP1 binding affinity. Indeed, cell uptake of radio-halogenated TZ analogues indicated selective uptake in a panel of cell types that correlated with PARP1 levels but was inversely related to the atomic radii of the halogen series. Despite modest specific activity and specific uptake, 77Br-TZ showed significant cytotoxicity. Further investigation of 18F-TZ with 77Br-TZ as a radiotheranostic pair will be facilitated by the synthetic schemes herein.
Muzzioli, Riccardo [The University of Texas MD And↗
Vibrational population distributions in nonequilibrium nozzle expansion flows
Experimental measurements and theoretical calculations of the vibrational population distribution in nonequilibrium nozzle expansion flows of gas mixtures are reported. These studies were directed toward determining whether vibrational energy exchange pumping could lead to laser action on the vibrational bands of a diatomic molecule. Three different types of experiments were conducted. These showed (1) that vibrational energy was preferentially transferred from N2 to CO in supersonic nozzle flows containing these gases; (2) that under some conditions this vibrational energy exchange pumping mechanism created population inversions in the vibrational levels of CO; and (3) that at large expansion ratios the magnitude of these population inversions was sufficient to sustain lasing in the nozzle. A theoretical model was developed to calculate vibrational state population distributions in gas dynamic expansions of a mixture of diatomic gases. Although only isothermal calculations have been completed, these data indicate that population inversions are predicted for conditions similar to those obtained in the nozzle expansion flows.
Watt, W. S.↗
Penecontemporaneous metamorphism, fragmentation, and reassembly of ordinary chondrite parent bodies
The thermal histories of ordinary chondrites and the canonical internal heating or onion shell models, which predict an inverse relation between the petrologic type of chondrites and the metallographic cooling rate, are reviewed. The thermal and accretional requirements of the 'metamorphosed planetesimal' model proposed by Scott and Rajan (1981) are analyzed, and an alternative model consistent with the metallographic cooling rate constraints is suggested in which ordinary chondrite parent bodies are collisionally fragmented and then rapidly reassembled before metamorphic heat has been dissipated.
Grimm, R. E.↗
Do large rate coefficients for ion-polar neutral reactions have a serious effect on chemical models of dense clouds?
In order to incorporate large ion-polar neutral rate coefficients into existing gas phase reaction networks, it is necessary to utilize simplified theoretical treatments because of the significant number of rate coefficients needed. The authors have used two simple theoretical treatments: the locked dipole approach of Moran and Hamill for linear polar neutrals and the trajectory scaling approach of Su and Chesnavich for nonlinear polar neutrals. The former approach is suitable for linear species because in the interstellar medium these are rotationally relaxed to a large extent and the incoming charged reactants can lock their dipoles into the lowest energy configuration. The latter approach is a better approximation for nonlinear neutral species, in which rotational relaxation is normally less severe and the incoming charged reactants are not as effective at locking the dipoles. The treatments are in reasonable agreement with more detailed long range theories and predict an inverse square root dependence on kinetic temperature for the rate coefficient. Compared with the locked dipole method, the trajectory scaling approach results in rate coefficients smaller by a factor of approximately 2.5.
Herbst, E.↗
Original structures, and fragmentation and reassembly histories of asteroids - Evidence from meteorites
The validity of an onion shell model (OSM) for chondrite parent asteroids was assessed using metallographic cooling rates (MCR) derived from the compositions of metallic Fe-Ni grains. The hypothesis evaluated was that the hottest materials in chondrites would have been buried the deepest and cooled the slowest. The survey covered breccia from regolith and 13 different chondrites. The MCRs agreed well with cooling rates predicted by fission-track thermometry and Ar-40/Ar-39 ages. The OSM predicts an inverse correlation between the cooling rate and the petrographic type. Low correlations found between the MCRs and petrographic type indicate that chondrite parent asteroids were not assembled with onion shell structures.
Taylor, G. Jeffrey↗
Part 1: Aspects of lithospheric evolution on Venus. Part 2: Thermal and collisional histories of chondrite parent bodies
The geological evolution of distinctly different kinds of solar system objects is addressed. Venus has been observed over the past decade by orbital radars on both American and Soviet spacecraft. These surface measurements provide clues to the structure and evolution of the lithosphere. The parent bodies of chondritic meteorites, thought to resemble asteroids, represent the other end of the size spectrum of terrestrial objects. Their early thermal and collisional histories may be constrained by the chemical and textural record preserved in meteorite samples. Impact craters on Venus have been observed by the Soviet Venera 15/16 spacecraft. A formalism is presented by which the size-frequency distribution of impact craters may be used to estimate upper bounds on the mean global rates of volcanic resurfacing and lithospheric recycling on that planet over the past several hundred million years. The impact crater density reported from Venera observations, if valid for the entire Venus surface, indicates a mean volcanic flux no greater than 2 cu km/y, corresponding to a maximum average rate of resurfacing of about 4 km/b.y. For the lowest estimated mean crater retention age of the surface of Venus imaged by Venera 15/16, the rate of lithospheric recycling on Venus does not exceed 1.5 sq km/y. Ordinary chondrite meteorites show textural and chemical patterns indicative of varying intensities of thermal metamorphism. The conventional onion-shell model, which envisions highly metamorphosed material in the core and less intensely heated rocks near the surface, predicts an inverse relation between peak temperature and cooking rate, but none has been observed. A metamorphosed-planetesimal model is devised to explain this discrepancy, whereby heating occurs in planetesimals a few kilometers in radius which then accrete to form 100-km-radius parent bodies. Cooling rates are then randomly controlled by burial depth. Thermal and collisional constraints are examined, and the model is found to be applicable only to highly insulating Al-26-rich planetesimals that remain closely aggregated upon accretion. An alternative model is presented, in which onion-shell parent bodies are collisionally fragmented during metamorphism and then gravitationally reassembled. If reassembly times are short, then cooling rates would be determined by burial depth in the reaccreted parent body. This model, unlike previous ones, can explain both coherent and incoherent cooling of Breccia clasts by collisions during or after metamorphism, respectively.
Grimm, Robert E.↗
Flow effects in a vertical CVD reactor
A model is presented to simulate the non-Boussinesq flow in a vertical, two-dimensional, chemical vapor deposition reactor under atmospheric pressure. Temperature-dependent conductivity, mass diffusivity, viscosity models, and reactive species mass transfer to the substrate are incorporated. In the limits of small Mach number and small aspect ratio, asymptotic expressions for the flow, temperature, and species fields are developed. Soret diffusion effects are also investigated. Analytical solutions predict an inverse relationship between temperature field and concentration field due to Soret effects. This finding is consistent with numerical simulations, assisting in the understanding of the complex interactions amongst the flow, thermal, and species fields in a chemically reacting system.
Young, G. W.↗
Gamma-ray Pulsars: Models and Predictions
Pulsed emission from gamma-ray pulsars originates inside the magnetosphere, from radiation by charged particles accelerated near the magnetic poles or in the outer gaps. In polar cap models, the high energy spectrum is cut off by magnetic pair production above an energy that is, dependent on the local magnetic field strength. While most young pulsars with surface fields in the range B = 10(exp 12) - 10(exp 13) G are expected to have high energy cutoffs around several GeV, the gamma-ray spectra of old pulsars having lower surface fields may extend to 50 GeV. Although the gamma-ray emission of older pulsars is weaker, detecting pulsed emission at high energies from nearby sources would be an important confirmation of polar cap models. Outer gap models predict more gradual high-energy turnovers of the primary curvature emission around 10 GeV, but also predict an inverse Compton component extending to TeV energies. Detection of pulsed TeV emission, which would not survive attenuation at the polar caps, is thus an important test of outer gap models. Next-generation gamma-ray telescopes sensitive to GeV-TeV emission will provide critical tests of pulsar acceleration and emission mechanisms.
Harding Alice K.↗
Adversarial autoencoder ensemble for fast and probabilistic reconstructions of few-shot photon correlation functions for solid-state quantum emitters
Second-order photon correlation measurements [g (2) (τ) functions] are widely used to classify single-photon emission purity in quantum emitters or to measure the multiexciton quantum yield of emitters that can simultaneously host multiple excitations – such as quantum dots – by evaluating the value of g (2) (τ = 0). Accumulating enough photons to accurately calculate this value is time consuming and could be accelerated by fitting of few-shot photon correlations. Here, we develop an uncertainty-aware, deep adversarial autoencoder ensemble (AAE) that reconstructs noise-free g (2) (τ) functions from noise-dominated, few-shot inputs. The model is trained with simulated g (2) (τ) functions that are facilely generated by Poisson sampling time bins. The AAE reconstructions are performed orders-of-magnitude faster, with reconstruction errors and estimates of g (2) (τ = 0) that are lower in variance and similar in accuracy compared to Maximum likelihood estimation and Levenberg-Marquardt least-squares fitting approaches, for simulated and experimentally measured few-shot g (2) (τ) functions (~100 two-photon events) of InP/ZnS/ZnSe and CdS/CdSe/CdS quantum dots. The deep-ensemble model comprises eight individual autoencoders, allowing for probabilistic reconstructions of noise-free g (2) (τ) functions, and we show that the predicted variance scales inversely with number of shots, with comparable uncertainties to computationally intensive Markov chain Monte Carlo sampling. Furthermore, this work demonstrates the advantage of machine learning models to perform uncertainty-aware, fast, and accurate reconstructions of simple Poisson-distributed photon correlation functions, allowing for on-the-fly reconstructions and accelerated materials characterization of solid-state quantum emitters.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
A Spectrochemical Series for Electron Spin Relaxation
Controlling the rate of electron spin relaxation in paramagnetic molecules is essential for contemporary applications in molecular magnetism and quantum information science. However, the physical mechanisms of spin relaxation remain incompletely understood, and new spectroscopic observables play an important role in evaluating spin dynamics mechanisms and structure–property relationships. Here, we use cryogenic magnetic circular dichroism (MCD) spectroscopy and pulse electron paramagnetic resonance (EPR) in tandem to examine the impact of ligand field (d–d) excited states on spin relaxation rates. We employ a broad scope of square-planar Cu(II) compounds with varying ligand field strength, including CuS 4 , CuN 4 , CuN 2 O 2 , and CuO 4 first coordination spheres. An unexpectedly strong correlation exists between spin relaxation rates and the average d–d excitation energy (R 2 = 0.97). The relaxation rate trends as the inverse 11th power of the excited-state energies, whereas simplified theoretical models predict only an inverse second power dependence. These experimental results directly implicate ligand field excited states as playing a critical role in the ground-state spin relaxation mechanism. Furthermore, ligand field strength is revealed to be a particularly powerful design principle for spin dynamics, enabling formation of a spectrochemical series for spin relaxation.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Magneto-opto-phononic inverse Faraday effect
Nonlinear frequency conversion processes, such as optical rectification, difference-frequency generation, and sum-frequency generation, are fundamental for producing electromagnetic radiation at diverse frequencies. In this work, we demonstrate that coherently excited infrared-active phonons can act as transducers for generating nonlinear magnetizations through phonon-magnon interactions, analogous to nonlinear optical frequency conversion. We derive analytical solutions for the time-dependent magnetizations arising from the second-order response to the electric field component of an ultrashort laser pulse. These solutions enable us to define second-order nonlinear magneto-electric susceptibilities, which describe rectification, impulsive excitation, and sum-frequency excitation of coherent magnons. Our theoretical framework naturally incorporates the conventional magneto-optic and phonon inverse Faraday effects and predicts a hybrid magneto-opto-phononic inverse Faraday effect involving photon-phonon-magnon scattering. This work highlights nonlinear phononics as a pathway for controlling magnetization in solids.
Landau-Lifschitz-Gilbert equation↗