First principles insights into stability of defected MXenes in water
First principles molecular dynamics reveals how different types of defects on the Ti 3 C 2 T x MXene surface influence its interaction with water.
Chemistry↗
SEARCH · Engineering Papers
Results for “First principles”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Thermodynamically informed priors for uncertainty propagation in first-principles statistical mechanics
Here, this work demonstrates how first-principles statistical mechanics approaches within a Bayesian framework can quantify and propagate uncertainties to downstream thermodynamic calculations. To address the issue of Bayesian prior selection, knowledge of 0 K ground states in the material system of interest is incorporated into the prior. The effectiveness of this framework is shown by creating a phase diagram for the fcc zirconium nitride system, including confidence intervals on order-disorder transition temperatures.
Bayesian methods↗
First-principles study of the T center in silicon
The T center in silicon is a well-known carbon-based color center that has been recently considered for quantum technology applications. Using first-principles computations, we show that the excited state is formed by a defect-bound exciton made of a localized defect state occupied by an electron to which a hole is bound. The localized state is of strong carbon p character and reminiscent of the localization of the unpaired electron in the ethyl radical molecule. The radiative lifetime for the defect-bound exciton is calculated to be on the order of microseconds, much longer than for other quantum defects such as the nitrogen vacancy center in diamond and in agreement with experiments. The longer lifetime is associated with the small transition dipole moment as a result of the very different nature of the localized and delocalized states forming the defect-bound exciton. Finally, we use first-principles calculations to assess the stability of the T center. Here, we find the T center to be stable against decomposition into simpler defects when keeping the stoichiometry fixed. However, we identify that the T center is easily prone to (de)hydrogenation and so requires very precise annealing conditions (temperature and atmosphere) to be efficiently formed.
36 MATERIALS SCIENCE↗
Double-Atom Catalysts Featuring Inverse Sandwich Structure for CO 2 Reduction Reaction: A Synergetic First-Principles and Machine Learning Investigation
Electrocatalytic CO 2 reduction reactions (CO 2 RR) based on scalable and highly efficient catalysis provide an attractive strategy for reducing CO 2 emissions. Here in this work, we combined first-principles density functional theory (DFT) and machine learning (ML) to comprehensively explore the potential of double-atom catalysts (DACs) featuring an inverse sandwich structure anchored on defective graphene (gra) to catalyze CO 2 RR to generate C 1 products. We started with five homonuclear M 2 ⊥gra (M = Co, Ni, Rh, Ir, and Pt), followed by 127 heteronuclear MM'⊥gra (M = Co, Ni, Rh, Ir, and Pt, M' = Sc–Au). Stable DACs were screened by evaluating their binding energy, formation energy, and dissolution potential of metal atoms, as well as conducting first-principles molecular dynamics simulations with and without solvent water molecules. Based on DFT calculations, Rh 2 ⊥gra DAC was found to outperform the other four homonuclear DACs and the Rh-based single- and double-atom catalysts of noninverse sandwich structures. Out of the 127 heteronuclear DACs, 14 were found to be stable and have good catalytic performance. An ML approach was adopted to correlate key factors with the activity and stability of the DACs, including the sum of radii of metal and ligand atoms (d M–M' , d M–C , and d M'–C ), the sum and difference of electronegativity of two metal atoms (P M + P M' , P M – P M '), the sum and difference of first ionization energy of two metal atoms (I M + I M' , I M – I M '), the sum and difference of electron affinity of two metal atoms (A M + A M' , A M – A M '), and the number of d-electrons of the two metal atoms (Nd). The obtained ML models were further used to predict 154 potential electrocatalysts out of 784 possible DACs featuring the same inverse sandwich configuration. Overall, this work not only identified promising CO 2 RR DACs featuring the reported inverse sandwich structure but also provided insights into key atomic characteristics associated with high CO 2 RR activity.
30 DIRECT ENERGY CONVERSION↗
First-Principles Thermodynamic Assessments of Sr-Containing Secondary Phase Formation in La1-xSrxMnO3±δ Perovskites for Solid Oxide Cell Applications
Sr-secondary phase formation is a potentially significant degradation mode threatening solid-oxide cell (SOC) commercial viability. A first-principles thermodynamic study was performed for rhombohedral perovskite (La1-xSrx) MnO3±δ (LSM) to assess its stability against Sr secondary phase formation in SOC applications. In this work, the Sr secondary phase formation reaction free energies were determined by combining ab initio lattice dynamics calculations for the solid phases and an ab initio thermodynamics approach for the gas phases. Furthermore, this approach goes beyond previous thermodynamic modeling studies by integrating first-principles based point-defect equilibria into the analyses. The modeling results indicate an increased tendency to form SrO oxide from LSM upon decreasing the oxygen partial pressure. Additionally, enhancing factors to form the Sr-related secondary phase from the associated SrO activity in LSM are further quantified by considering the equilibrium of SrO reacting with contaminant gas species as a function of temperature and gas pressure.
Defect and phase stability↗
First principles thermal transport modeling in GaN and related materials
Gallium nitride is a wide bandgap material utilized in a variety of technologies, including high-power electronics and light-emitting diodes, partly due to its favorable thermal properties. This chapter describes modern first-principles-based modeling of phonons and lattice thermal conductivity (k) of GaN, III-nitrides and related materials. In particular, we describe the theoretical underpinnings of calculating phonon dispersions, intrinsic phonon interactions, and other lattice dynamical properties from quantum perturbation theory and density functional theory (DFT) methods. Description of how these methods are then coupled with the Peierls-Boltzmann transport (PBT) equation to determine phonon distributions and lifetimes relevant for thermal transport is given. These theoretical and numerical methods have demonstrated quantitative accuracy and predictive power for calculating pristine k and defect-limited k from first principles for a variety of materials. We present a review of the literature utilizing DFT-PBT methods to understand novel k behaviors in III-nitrides and related materials.
Lindsay, Lucas↗
First-principles thermodynamic assessment of Sr-containing secondary phase formation in strontium-substituted lanthanum manganites for solid oxide cell applications
Sr-secondary phase formation is a potentially significant degradation mode with direct impact upon solid-oxide cell (SOC) commercial viability. A first-principles based thermodynamic study was performed for La 1−x Sr x MnO 3±δ (LSM) perovskites to assess their stability against formation of different Sr-secondary phases, including SrO, SrCrO 4 , SrSO 4 , SrCO 3 , and Sr(OH) 2 , for SOC applications. The Sr-secondary phase formation reaction free energies were determined via a thermodynamic model by combining ab initio lattice dynamics calculations for the solid phases and ab initio thermodynamic data for the gas phases. The current approach expands the previously reported thermodynamic modeling studies by integrating first-principles based point defect equilibria into the thermodynamic analysis. The modeling results obtained using this new approach indicate an increased tendency to form the SrO oxide upon decreasing the oxygen partial pressure. Additionally, the enhancing factors to form the Sr-related secondary phase from the associated SrO activity in LSM are further quantified by considering the equilibrium of SrO reacting with the contaminant gas species as a function of temperature and pressure.
defect thermodynamics modeling↗
Exciton Lifetime and Optical Line Width Profile via Exciton–Phonon Interactions: Theory and First-Principles Calculations for Monolayer MoS 2
Exciton dynamics dictates the evolution of photoexcited carriers in photovoltaic and optoelectronic devices. However, interpreting their experimental signatures is a challenging theoretical problem due to the presence of both electron–phonon and many-electron interactions. Here, we develop and apply here a first-principles approach to exciton dynamics resulting from exciton–phonon coupling in monolayer MoS 2 and reveal the highly selective nature of exciton–phonon coupling due to the internal spin structure of excitons, which leads to a surprisingly long lifetime of the lowest-energy bright A exciton. Moreover, we show that optical absorption processes rigorously require a second-order perturbation theory approach, with photon and phonon treated on an equal footing, as proposed by Toyozawa and Hopfield. Such a treatment, thus far neglected in first-principles studies, gives rise to off-diagonal exciton–phonon self-energy, which is critical for the description of dephasing mechanisms and yields exciton line widths in excellent agreement with experiment.
77 NANOSCIENCE AND NANOTECHNOLOGY↗
Hall2De Simulations with a First-Principles Electron Transport Model Based on the Electron Cyclotron Drift Instability
Several years of work have combined plasma measurements in a laboratory Hall thruster and r-z numerical simulations with Hall2De to isolate the spatial variation of the anomalous collision frequency needed in Ohm’s law to produce the observed thruster behavior. This numerical solution is used here to test the validity of a first-principles model of the anomalous transport in these devices before such model is implemented self-consistently in r-z fluid codes like Hall2De. The first-principles model employs quasi-linear theory and is based on the hypothesis that the Electron Cyclotron Drift Instability (ECDI) excites ion acoustic turbulence that, in turn, enhances the effective collision frequency in these devices. We find that a model of the ECDI that assumes Maxwellian velocity distributions for electrons and singly-charged, main-beam, cold ions (Ti=0.07 eV) is insufficient to explain the expected variation of the anomalous collision frequency both in the interior and exterior of the acceleration channel. When warm ions (~0.5-3 eV) are accounted for, the ECDI model in the channel interior appears more promising but fails by orders of magnitude in the near plume region due to the much higher Landau damping of the ion acoustic waves there. This implies that either (a) some process allows the ECDI instability to remain uninhibited by classical Landau damping or, (b) that a different instability (or instabilities) altogether, also insusceptible to Landau damping, is/are active in this region. A previous hypothesis, that convection of wave energy generated by the ECDI in the channel plays a significant role in the near plume, is not supported by the results of the simulations.
Mikellides, Ioannis G.↗
Change of Electrical and Transport Properties of Nickel Oxide by Carrier Concentration and Temperature through First-Principle Calculations
Abstract Nickel is typically used as one of the main components in electrical contact devices or connectors. Nickel oxide (NiO) is usually formed on the surfaces of electrodes and can negatively impact system performance by introducing electrical contact resistance. The thermal, electrical, and transport properties of NiO, as a Mott insulator or a p-type semiconductor, can be altered by operating and environmental conditions such as temperature and stress/strain by contact. In this study, we investigate the fundamental material properties of NiO through the first-principle calculations. First, we obtain and compare the lattice parameter, magnetic moment, and electronic structure for NiO via the WIEN2K simulations with four different potentials (i.e., GGA, GGA + U, LSDA, and LSDA + U). Then, using the WIEN2K simulation results with LSDA + U potential that produces a highly accurate bandgap for NiO, we calculate the electrical conductivity and electrical part of the thermal conductivity of nickel and NiO as a function of temperature and carrier concentration through the BoltzTraP simulations. Systematic simulation results revealed that the electrical conductivity relative to the relaxation time for NiO increases with the carrier concentration, while it shows a slightly decreasing trend with temperature under a fixed carrier concentration. By contrast, the electrical part of the thermal conductivity shows an increasing trend considering carrier concentration and temperature.
Shah, Nayem Md. Reza↗
Comparing first-principles density functionals plus corrections for the lattice dynamics of YBa 2 Cu 3 O 6
The enigmatic mechanism underlying unconventional high-temperature superconductivity, especially the role of lattice dynamics, has remained a subject of debate. Theoretical insights have long been hindered due to the lack of an accurate first-principles description of the lattice dynamics of cuprates. Recently, using the r2SCAN meta-generalized gradient approximation (meta-GGA) functional, we have been able to achieve accurate phonon spectra of an insulating cuprate YBa 2 Cu 3 O 6 and discover significant magnetoelastic coupling in experimentally interesting Cu–O bond stretching optical modes [Ning et al., Phys. Rev. B 107, 045126 (2023)]. We extend this work by comparing Perdew–Burke–Ernzerhof and r2SCAN performances with corrections from the on-site Hubbard U and the D4 van der Waals (vdW) methods, aiming at further understanding on both the materials science side and the density functional side. We demonstrate the importance of vdW and self-interaction corrections for accurate first-principles YBa 2 Cu 3 O 6 lattice dynamics. Since r2SCAN by itself partially accounts for these effects, the good performance of r2SCAN is now more fully explained. Finally, in addition, the performances of the Tao–Mo series of meta-GGAs, which are constructed in a different way from the strongly constrained and appropriately normed (SCAN) meta-GGA and its revised version r2SCAN, are also compared and discussed.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Voltage-Dependent First-Principles Barriers to Li Transport within Li-Ion Battery Solid Electrolyte Interphases
Charging a Li-ion battery requires Li-ion transport between the cathode and the anode. This Li-ion transport is dependent on (among other factors) the electrostatic environment that the ion encounters within the solid electrolyte interphase (SEI), which separates the anode from the surrounding electrolyte. A previous first-principles work has illuminated the reaction barriers through likely atomistic SEI environments but has had difficulty accurately reflecting the larger electrostatic potential landscape that an ion encounters moving through the SEI. In this work, we apply the recently developed quantum continuum approximation (QCA) technique to provide an equilibrium electronic potentiostat for first-principles interface calculations. Using QCA, we calculate the potential barrier for Li-ion transport through LiF, Li 2 O, and Li 2 CO 3 SEIs along with LiF–LiF and LiF–Li 2 O grain boundaries, all paired with Li metal anodes. Here, we demonstrate that the SEI potential barrier is dependent on the electrochemical potentials of the anode in each system. Finally, we use these techniques to estimate the change in the diffusion barrier for a Li ion moving in a LiF SEI as a function of the anode potential. We find that properly accounting for interface and electronic voltage effects significantly lowers reaction barriers compared with previous literature results.
25 ENERGY STORAGE↗
Infrastructure first principles for the Anthropocene
Abstract There appears to be a growing decoupling between the conditions that infrastructures were designed for and today’s rapidly changing environments. Infrastructures today are largely predicated on the technologies, goals, and governance structures from a century ago. While infrastructures continue to deliver untold value, there is growing evidence that these critical, basic, and lifeline systems appear ill-equipped to confront the volatility, uncertainty, accelerating conditions, and complexity that define them and their changing environments. Innovative and disruptive first principles are needed to guide infrastructures in the Anthropocene. Drawing from emerging infrastructure research and disciplines that appear better able to confront disruption and change, a novel set of first principles are identified: (1) Plan for complex conditions and surprise; (2) Recouple with agility and flexibility; (3) Govern for exploration and instability; (4) Build consensus as control decentralizes; (5) Restructure to engage with porous boundaries; and, (6) Cyberthreat planning is now mission critical. These principles should guide infrastructure planning recognizing the changing nature and increasingly obsolete boundaries that have defined engineered systems in the modern era.
Chester, Mikhail (ORCID:0000000293542102)↗
E min : A First-Principles Thermochemical Descriptor for Predicting Molecular Synthesizability
Predicting the synthesizability of a new molecule remains an unsolved challenge that chemists have long tackled with heuristic approaches. Here, in this study, we report a new method for predicting synthesizability using a simple yet accurate thermochemical descriptor. We introduce E min , the energy difference between a molecule and its lowest energy constitutional isomer, as a synthesizability predictor that is accurate, physically meaningful, and first-principles based. We apply E min to 134,000 molecules in the QM9 data set and find that E min is accurate when used alone and reduces incorrect predictions of "synthesizable" by up to 52% when used to augment commonly used prediction methods. Our work illustrates how first-principles thermochemistry and heuristic approximations for molecular stability are complementary, opening a new direction for synthesizability prediction methods.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Accelerating the discovery of low-energy structure configurations: A computational approach that integrates first-principles calculations, Monte Carlo sampling, and Machine Learning
Finding Minimum Energy Configurations (MECs) is essential in fields such as physics, chemistry, and materials science, as they represent the most stable states of the systems. In particular, identifying such MECs in multi-component alloys considered candidate PFMs is key because it determines the most stable arrangement of atoms within the alloy, directly influencing its phase stability, structural integrity, and thermo-mechanical properties. However, since the search space grows exponentially with the number of atoms considered, obtaining such MECs using computationally expensive first-principles DFT calculations often results in a cumbersome task. To escape the above compromise between physical fidelity and computational efficiency, we have developed a novel physics-based data-driven approach that combines Monte Carlo sampling, first-principles DFT calculations, and Machine Learning to accelerate the discovery of MECs in multi-component alloys. More specifically, we have leveraged well-established Cluster Expansion (CE) techniques with Local Outlier Factor models to establish strategies that enhance the reliability of the CE method. In this work, we demonstrated the capabilities of the proposed approach for the particular case of a tungsten-based quaternary high-entropy alloy. However, the method is applicable to other types of alloys and enables a wide range of applications.
36 MATERIALS SCIENCE↗
First-Principles Theory of the Relativistic Magnetic Reconnection Rate in Astrophysical Pair Plasmas
In this paper, we develop a first-principles model for the relativistic magnetic reconnection rate in strongly magnetized pair plasmas. By considering the energy budget and required current density near the x-line, we analytically show that in the magnetically dominated relativistic regime, the x-line thermal pressure is significantly lower than the upstream magnetic pressure due to the extreme energy needed to sustain the current density, consistent with kinetic simulations. This causes the upstream magnetic field lines to collapse in, producing the open outflow geometry which enables fast reconnection. The result is important for understanding a wide range of extreme astrophysical environments, where fast reconnection has been evoked to explain observations such as transient flares and nonthermal particle signatures.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Phonon screening and dissociation of excitons at finite temperatures from first principles
The properties of excitons, or correlated electron–hole pairs, are of paramount importance to optoelectronic applications of materials. A central component of exciton physics is the electron–hole interaction, which is commonly treated as screened solely by electrons within a material. However, nuclear motion can screen this Coulomb interaction as well, with several recent studies developing model approaches for approximating the phonon screening of excitonic properties. While these model approaches tend to improve agreement with experiment, they rely on several approximations that restrict their applicability to a wide range of materials, and thus far they have neglected the effect of finite temperatures. Here, we develop a fully first-principles, parameter-free approach to compute the temperature-dependent effects of phonon screening within the ab initio GW -Bethe–Salpeter equation framework. We recover previously proposed models of phonon screening as well-defined limits of our general framework, and discuss their validity by comparing them against our first-principles results. We develop an efficient computational workflow and apply it to a diverse set of semiconductors, specifically AlN, CdS, GaN, MgO, and SrTiO 3 . We demonstrate under different physical scenarios how excitons may be screened by multiple polar optical or acoustic phonons, how their binding energies can exhibit strong temperature dependence, and the ultrafast timescales on which they dissociate into free electron–hole pairs.
Science & Technology - Other Topics↗
Machine Learning for First Principles Calculations of Material Properties for Ferromagnetic Materials
The investigation of finite temperature properties using Monte-Carlo (MC) methods requires a large number of evaluations of the system’s Hamiltonian to sample the phase space needed to obtain physical observables as function of temperature. DFT calculations can provide accurate evaluations of the energies, but they are too computationally expensive for routine simulations. To circumvent this problem, machine-learning (ML) based surrogate models have been developed and implemented on high-performance computing (HPC) architectures. In this paper, we describe two ML methods (linear mixing model and HydraGNN) as surrogates for first principles density functional theory (DFT) calculations with classical MC simulations. These two surrogate models are used to learn the dependence of target physical properties from complex compositions and interactions of their constituents. We present the predictive performance of these two surrogate models with respect to their complexity while avoiding the danger of overfitting the model. An important aspect of our approach is the periodic retraining with newly generated first principles data based on the progressive exploration of the system’s phase space by the MC simulation. The numerical results show that HydraGNN model attains superior predictive performance compared to the linear mixing model for magnetic alloy materials.
Eisenbach, Markus↗