Engineering topics

Lordi, Vincenzo

Publications and source records attributed to Lordi, Vincenzo.

At least 19 records

DOE OSTI2026

Shake-up and shake-off spectra in the electron capture decay of atomic $^7$Be

The most stringent laboratory-based experimental limits on the existence of sub-MeV sterile neutrinos are currently set by decay spectroscopy of radioactive $^7$Be embedded into superconducting sensors. The systematic uncertainties are dominated by the modeling of the electron shake-up and shake-off spectra that are not based on state-of-the-art atomic theory and do not include electron correlations or relativistic effects. We have used the multiconfiguration Dirac-Fock formalism to obtain correlated wavefunctions ab initio and compute all single and double shake processes in the electron capture decay of atomic $^7$Be. The simulations can explain some but not all of the observed spectral features, likely because the wave functions are modified by the Ta sensor material that the $^7$Be is embedded into. The new models also show that the L/K electron capture ratio of $^7$Be in Ta has previously been slightly underestimated revising the previous value of 0.070(7) to a new value of 0.0756(20).

Atomic Physics (physics.atom-ph)↗

DOE OSTI2024

The Data Acquisition System for Phase-III of the BeEST Experiment

The BeEST experiment is a precision laboratory search for physics beyond the standard model that measures the electron capture decay of 7 Be implanted into superconducting tunnel junction (STJ) detectors. For Phase-III of the experiment, we constructed a continuously sampling data acquisition system to extract pulse shape and timing information from 16 STJ pixels offline. Four additional pixels are read out with a fast list-mode digitizer, and one with a nuclear MCA already used in the earlier limit-setting phases of the experiment. Here, we present the performance of the data acquisition system and discuss the relative advantages of the different digitizers.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

Spectroscopy-guided discovery of three-dimensional structures of disordered materials with diffusion models

Spectroscopy techniques such as x-ray absorption near edge structure (XANES) provide valuable insights into the atomic structures of materials, yet the inverse prediction of precise structures from spectroscopic data remains a formidable challenge. In this study, we introduce a framework that combines generative artificial intelligence models with XANES spectroscopy to predict three-dimensional atomic structures of disordered systems, using amorphous carbon (a-C) as a model system. In this work, we introduce a new framework based on the diffusion model, a recent generative machine learning method, to predict 3D structures of disordered materials from a target property. For demonstration, we apply the model to identify the atomic structures of a-C as a representative material system from the target XANES spectra. We show that conditional generation guided by XANES spectra reproduces key features of the target structures. Furthermore, we show that our model can steer the generative process to tailor atomic arrangements for a specific XANES spectrum. Finally, our generative model exhibits a remarkable scale-agnostic property, thereby enabling generation of realistic, large-scale structures through learning from a small-scale dataset (i.e. with small unit cells). Our work represents a significant stride in bridging the gap between materials characterization and atomic structure determination; in addition, it can be leveraged for materials discovery in exploring various material properties as targeted.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Interpretable, extensible linear and symbolic regression models for charge density prediction using a hierarchy of many-body correlation descriptors

Here, density functional theory (DFT) is routinely used to make electronic structure predictions for high-throughput screening of materials and molecules for technologically relevant areas, like the identification of better catalysts, electronic materials, and drug discovery. However, the DFT formalism is limited by (a) its poor (quadratic-to-quartic) scaling, and (b) the need to perform repeated eigenvalue computations of the electronic Hamiltonian as part of its self-consistent field (SCF) iteration procedure to obtain the converged ground state electron density, ρ (r). Approaches that directly predict ρ (r) of a structure with high accuracy can accelerate conventional SCF calculations and can also be used in linearly scaling methods such as orbital-free DFT. To this end, we present a procedure to predict the ground state electron density of molecular and periodic three-dimensional systems directly from the atomic structure with a particular emphasis on physical interpretability. In our framework, ρ (r) is modeled using many-body correlation descriptors that accurately capture the effects of local atomic arrangements in the neighborhood of a grid point. Our use of a linear regression scheme to fit to charge density data enables transparent analysis of the relative contributions of various types of local atomic correlations. By systematically including increasingly complex correlations, our model is shown to accurately predict ρ (r) for a variety of chemically and electronically diverse systems — amorphous Ge, Al(001) slab, crystalline Ga 2 O 3 , molecular benzene, and polyethylene. We then demonstrate a symbolic regression-based protocol to construct easily computable, interpretable features from lower-order correlations that significantly improves our electron density predictions with effectively no increase in the computational cost.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Accuracy, transferability, and computational efficiency of interatomic potentials for simulations of carbon under extreme conditions

Large-scale atomistic molecular dynamics (MD) simulations provide an exceptional opportunity to advance the fundamental understanding of carbon under extreme conditions of high pressures and temperatures. However, the fidelity of these simulations depends heavily on the accuracy of classical interatomic potentials governing the dynamics of many-atom systems. Here, this study critically assesses several popular empirical potentials for carbon, as well as machine learning interatomic potentials (MLIPs), in their ability to simulate a range of physical properties at high pressures and temperatures, including the diamond equation of state, its melting line, shock Hugoniot, uniaxial compressions, and the structure of liquid carbon. Empirical potentials fail to accurately predict the behavior of carbon under high pressure–temperature conditions. In contrast, MLIPs demonstrate quantum accuracy, with Spectral Neighbor Analysis Potential (SNAP) and atomic cluster expansion (ACE) being the most accurate in reproducing the density functional theory results. ACE displays remarkable transferability despite not being specifically trained for extreme conditions. Furthermore, ACE and SNAP exhibit superior computational performance on graphics processing unit-based systems in billion atom MD simulations, with SNAP emerging as the fastest. In addition to offering practical guidance in selecting an interatomic potential with a fine balance of accuracy, transferability, and computational efficiency, this work also highlights transformative opportunities for groundbreaking scientific discoveries facilitated by quantum-accurate MD simulations with MLIPs on emerging exascale supercomputers.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Ice Phase Classification Made Easy with Score-Based Denoising

Accurate identification of ice phases is essential for understanding various physicochemical phenomena. However, such classification for structures simulated with molecular dynamics is complicated by the complex symmetries of ice polymorphs and thermal fluctuations. For this purpose, both traditional order parameters and data-driven machine learning approaches have been employed, but they often rely on expert intuition, specific geometric information, or large training data sets. In this work, we present an unsupervised phase classification framework that combines a score-based denoiser model with a subsequent model-free classification method to accurately identify ice phases. Further, the denoiser model is trained on perturbed synthetic data of ideal reference structures, eliminating the need for large data sets and labeling efforts. The classification step utilizes the smooth overlap of atomic position (SOAP) descriptors as the atomic fingerprint, ensuring Euclidean symmetries and transferability to various structural systems. Our approach achieves a remarkable 100% accuracy in distinguishing ice phases of test trajectories using only seven ideal reference structures of ice phases as model inputs. This demonstrates the generalizability of the score-based denoiser model in facilitating phase identification for complex molecular systems. The proposed classification strategy can be broadly applied to investigate structural evolution and phase identification for a wide range of materials, offering new insights into the fundamental understanding of water and other complex systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

High pressure melt line of nickel using a generalized embedded atomic method potential

As the second most abundant metal in the Earth's core, nickel plays an important role in determining the structure and temperature of the Earth's core. Yet, the melt line of Ni at pressures corresponding to the Earth's core has not been explored in the literature. Many previous experimental and simulation efforts have reported the melting point of Ni at pressures below 100 GPa, but there exist large discrepancies, most of which have persisted due to various experimental and simulation bottlenecks in handling extreme pressure and temperature conditions. We adopted the generalized embedded atom method, which overcomes the limitations of existing interatomic potentials, to probe phase stability and phase boundaries of Ni at pressures between 50 and 500 GPa. Further, the potential was validated by comparing the cold curves, phonon dispersion curves, and enthalpies of fusion with ab initio density functional theory calculations. Our analysis shows that face centered cubic (FCC) is stable, and the hexagonal close packed (HCP) and body centered cubic (BCC) phases are metastable close to the melt line. Melting temperatures at different pressures were obtained from two-phase co-existence simulations and take the following functional form: $T$ m = $1969.23+19.15P-0.012P$ 2 . In contrast to iron, differences between the melting points of the stable and metastable phases of Ni are less than 250 K at 300 GPa, and the difference in melting points of the metastable BCC and HCP phases changes sign at 500 GPa, which implies that the phase transition mechanisms during solidification can be very complex.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Melting point of iron at high pressure: An assessment of uncertainties and effect of electronic temperature

An accurate calculation of the melting point of iron at various pressures in the Earth's core is important for understanding the core structure, geodynamo, and the Earth's history. Previous studies have assessed the melt line of iron at these extreme conditions using various experimental measurement techniques as well as both ab initio and classic molecular dynamics simulations. However, experimental measurements have uncertainties up to several hundred Kelvin, and inconsistencies remain among simulation results. Here in this work, we propose an iterative framework that couples density functional theory (DFT) calculations and molecular dynamics simulations performed using an ensemble of interatomic potentials to assess the effect of electronic temperature on the melting point. We systematically validate the potentials by comparing lattice constants and phonon dispersion curves at 0 K and enthalpy differences between liquid and HCP, FCC, BCC phases of iron close to the melt line at 300 GPa with DFT. Our results show that HCP iron melts at 6144 K (at 300 GPa), BCC phase is thermodynamically unstable, and FCC is metastable at this temperature. The melting points of FCC and BCC phases at 300 GPa are 5858 and 5647 K, respectively.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

Simulating noise on a quantum processor: interactions between a qubit and resonant two-level system bath

Material defects fundamentally limit the coherence times of superconducting qubits, and manufacturing completely defect-free devices is not yet possible. Therefore, understanding the interactions between defects and a qubit in a real quantum processor design is essential. We build a model that incorporates the standard tunneling model, the electric field distributions in the qubit, and open quantum system dynamics, and draws from the current understanding of two-level system (TLS) theory. Specifically, we start with one million TLSs distributed on the surface of a qubit and pick the 200 systems that are most strongly coupled to the qubit. We then perform a full Lindbladian simulation that explicitly includes the coherent coupling between the qubit and the TLS bath to model the time dependent density matrix of resonant TLS defects and the qubit. We find that the 200 most strongly coupled TLSs can accurately describe the qubit energy relaxation time. This work confirms that resonant TLSs located in areas where the electric field is strong can significantly affect the qubit relaxation time, even if they are located far from the Josephson junction (JJ). Similarly, a strongly-coupled resonant TLS located in the JJ does not guarantee a reduced qubit relaxation time if a more strongly coupled TLS is far from the JJ. In addition to the coupling strengths between TLSs and the qubit, the model predicts that the geometry of the device and the TLS relaxation time play a significant role in qubit dynamics. Our work can provide guidance for future quantum processor designs with improved qubit coherence times.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Dangling Bonds as Possible Contributors to Charge Noise in Silicon and Silicon–Germanium Quantum Dot Qubits

Spin qubits based on Si and Si 1–x Ge x quantum dot architectures exhibit among the best coherence times of competing quantum computing technologies, yet they still suffer from charge noise that limit their qubit gate fidelities. Identifying the origins of these charge fluctuations is therefore a critical step toward improving Si quantum-dot-based qubits. Here, we use hybrid functional calculations to investigate possible atomistic sources of charge noise, focusing on charge trapping at Si and Ge dangling bonds (DBs). We evaluate the role of global and local environment in the defect levels associated with DBs in Si, Ge, and Si 1–x Ge x alloys, and consider their trapping and excitation energies within the framework of configuration coordinate diagrams. We additionally consider the influence of strain and oxidation in charge-trapping energetics by analyzing Si and GeSi DBs in SiO 2 and strained Si layers in typical Si 1–x Ge x quantum dot heterostructures. Our results identify that Ge dangling bonds are more problematic charge-trapping centers both in typical Si 1–x Ge x alloys and associated oxidation layers, and they may be exacerbated by compositional inhomogeneities. In conclusion, these results suggest the importance of alloy homogeneity and possible passivation schemes for DBs in Si-based quantum dot qubits and are of general relevance to mitigating possible trap levels in other Si, Ge, and Si 1–x Ge x -based metal-oxide-semiconductor stacks and related devices.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Material Effects on Electron-Capture Decay in Cryogenic Sensors

Several current searches for physics beyond the standard model are based on measuring the electron-capture (EC) decay of radionuclides implanted into cryogenic high-resolution sensors. The sensitivity of these experiments has already reached the level where systematic effects related to atomic state energy changes from the host material are a limiting factor. One example is a neutrino mass study based on the nuclear EC decay of 7 Be to 7 Li inside cryogenic Ta-based sensors. Here, to understand the material effects at the required level, we use density-functional theory to model the electronic structure of lithium atoms in different atomic environments of the polycrystalline Ta absorber film. The calculations reveal that the Li 1s binding energies can vary by more than 2 eV due to insertion at different lattice sites, at grain boundaries, in disordered Ta, and in the vicinity of various impurities. However, the total range of Li 1s shifts does not exceed 4 eV, even for extreme amorphous disorder. Furthermore, when investigating the effects on the Li 2s levels, we find broadening of more than 5 eV due to hybridization with the Ta band structure. Material effects are shown to contribute significantly to peak broadening in Ta-based sensors that are used to search for physics beyond the standard model in the EC decay of 7 Be, but they do not explain the full extent of observed broadening. Understanding these in-medium effects will be required for current- and future-generation experiments that observe low-energy radiation from the EC decay of implanted isotopes to evaluate potential limitations on the measurement sensitivity.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Super-Resolution Airy Disk Microscopy of Individual Color Centers in Diamond

Super-resolution imaging techniques enable nanoscale microscopy in fields such as physics, biology, and chemistry. However, many super-resolution techniques require specialized optical components, such as a helical-phase mask. In this work, we present a novel technique, super-resolution Airy disk microscopy, that can be used in a standard confocal microscope without any specialized optics. We demonstrate this technique, in combination with ground state depletion, to image and control nitrogen-vacancy (NV) centers in bulk diamond below the diffraction limit. A greater than 14-fold improvement in resolution compared to the diffraction limit is achieved, corresponding to a spatial resolution of 16.9(8) nm for a 1.3 NA microscope with 589 nm light. We make use of our enhanced spatial resolution to control the spins states of individual NV centers separated from each other by less than the diffraction limit, including pairs sharing the same orientation that are indistinguishable with a conventional electron spin resonance measurement.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Changes in electric field noise due to thermal transformation of a surface ion trap

Here, we aim to illuminate how the microscopic properties of a metal surface map to its electric field noise characteristics. In our system, prolonged heat treatments of a metal film can induce a rise in the magnitude of the electric field noise generated by the surface of that film. We refer to this heat-induced rise in noise magnitude as a thermal transformation. The underlying physics of this thermal transformation process is explored through a series of heating, milling, and electron treatments performed on a single surface ion trap. Between these treatments, 40 Ca + ions trapped 70 μm above the surface of the metal are used as detectors to monitor the electric field noise at frequencies close to 1 MHz. An Auger spectrometer is used to track changes in the composition of the contaminated metal surface. With these tools we investigate contaminant deposition, chemical reactions, and atomic restructuring as possible drivers of thermal transformations.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Role of ripples in altering the electronic and chemical properties of graphene

Ripples of graphene are known to manipulate electronic and hydrogenation properties of graphitic materials. More detailed work is needed to elucidate the structure–property relationship of these systems. In this work, the density functional theory is used to compute the energy and electronic structure of the graphene models with respect to variable curvatures and hydrogen adsorption sites. The magnitude of finite bandgap opening depends on the orientation of ripples, and the hydrogen adsorption energy depends on the local curvature of graphene. An adsorbed hydrogen alters the local curvature, resulting in relatively weakened adsorption on the neighboring three sites, which gives a rationale to experimentally observed dynamic equilibrium stoichiometry (H:C = 1:4) of hydrogenated graphene. The surface diffusion transition state energy of adsorbed hydrogen is computed, which indicates that the Eley–Rideal surface recombination mechanism may be important to establish the dynamic equilibrium, instead of the commonly assumed Langmuir–Hinshelwood mechanism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

1 / ω electric-field noise in surface ion traps from correlated adsorbate dynamics

Ion traps are promising architectures for implementing quantum computers, but they suffer from excessive “anomalous” ion motional heating that limit their overall coherence and practicality for scalable quantum computing. The exact microscopic origins of anomalous heating remain an open question, but experiments point to adsorbates on trap electrodes as one likely source. Many different models of anomalous heating have been proposed, but these models have yet to pinpoint the atomistic origin of the experimentally observed 1/ω electric-field noise scaling seen in ion traps at frequencies between 0.1–10 MHz. In this work, we show that a model based on previously proposed surface-induced dipole fluctuations on adsorbates, but which also incorporates interparticle interaction dynamics through molecular dynamics simulations of up to multiple monolayers of adsorbates, gives rise to 1/ω frequency scaling at the MHz frequencies typically employed in ion traps. Overall, these results demonstrate that moderate-to-high densities of adsorbates can give rise to a set of activated motions that produce the 1/ω noise observed in ion traps and that collective adsorbate motions produce the observed noise spectra that a noninteracting model does not capture.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Probing Charge Dynamics in Diamond with an Individual Color Center

Control over the charge states of color centers in solids is necessary to fully utilize them in quantum technologies. However, the microscopic charge dynamics of deep defects in wide-band-gap semiconductors are complex, and much remains unknown. We utilize a single-shot charge-state readout of an individual nitrogen-vacancy (NV) center to probe the charge dynamics of the surrounding defects in diamond. We show that the NV center charge state can be converted through the capture of holes produced by optical illumination of defects many micrometers away. With this method, we study the optical charge conversion of silicon-vacancy (SiV) centers and provide evidence that the dark state of the SiV center under optical illumination is SiV 2– . These measurements illustrate that charge carrier generation, transport, and capture are important considerations in the design and implementation of quantum devices with color centers and provide a novel way to probe and control charge dynamics in diamond.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2021

Advances and opportunities in materials science for scalable quantum computing

We report that by harnessing unique quantum mechanical phenomena, such as superposition and entanglement, quantum computers offer the possibility to drastically outperform classical computers for certain classes of problems. The realization of this potential, however, presents a substantial challenge, because noise and imperfections associated with the materials used to fabricate devices can obscure the delicate quantum mechanical effects that enable quantum computing. Hence, progress in synthesis, characterization, and modeling of materials for quantum computing have driven many exciting advances in recent years and will become increasingly important in the years to come. As progressively more complex, multi-qubit systems come online, and as significant government and industrial investment drives research forward, new challenges and opportunities for materials science continue to emerge. The articles in this issue survey the current state of materials science progress and obstacles for some leading quantum computing platforms; opportunities for deeper involvement by materials scientists abound. Ultimate realization of the full potential of quantum computers will require a multidisciplinary effort spanning many traditional areas of expertise.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Analysis of defects in In 2 O 3 :H synthesized in presence of water vapor and hydrogen gas mixture

Using hybrid functional-based density functional theory calculations, we analyze the structure and kinetics of defects formed in two competing synthesis routes to prepare hydrogen-doped In 2 O 3 films, using a hydrogen and oxygen gas mixture vs synthesis in the presence of water vapor. For both of these synthesis routes, we find that H + is the dominant defect species: when the Fermi level is close to the conduction band, H + has a lower formation energy than other intrinsic or extrinsic defects. Our results also suggest that water molecules spontaneously split into H + (which occupies octahedral voids) and OH – interstitials (which occupies vacant oxygen lattice sites or oxygen vacancies). From the analysis of the binding energies between these different defects, we conclude that these defects do not cluster and are most likely to stay spatially distributed throughout the films. In addition, the sum of formation energies of an oxygen (i.e., O$^{2–}_i$) and a H + interstitial is close to the formation energy of a OH – interstitial, meaning that water molecules are completely split into 2H + and O$^{2–}_i$ at the synthesis conditions. Further, in the presence of H 2 + O 2 gas mixture, oxygen interstitials occupy oxygen vacancies while hydrogen interstitials occupy vacant oxygen lattice sites and form bonds with lattice oxygens. Our analysis of the defect equilibria suggests that the hydrogen content in films synthesized in the presence of water vapor is higher than films synthesized in the presence of a hydrogen gas mixture. At high dopant concentrations, a hydrogen bond network is formed in the system and this leads to large distortions in the lattice.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗