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At least 1,639 records · Page 91
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Investigating the Crosslinking, Degradation, and Adhesion Behavior of Photovoltaic Encapsulants Under Thermal Accelerated Aging

Degradation of photovoltaic (PV) module encapsulant characteristics that lead to mechanical embrittlement and delamination remains a cause of failure in solar installations. A multiscale reliability model connecting the encapsulant mechanical and fracture properties to the degraded molecular structure and interfacial bonding to adjacent solar cell and glass substrates was previously published. The model, developed primarily for poly(ethylene-co-vinyl acetate) acetate (EVA) encapsulants, remains to be experimentally validated. Determining the degradation and crosslinking kinetics of alternative encapsulants, such as polyolefin elastomer (POE) and EVA/POE/EVA composites (EPE), can generalize the model. In this work, we subject fully cured EVA, POE, and EPE encapsulants to accelerated thermal aging to determine how high temperatures impact reaction kinetics. An increase in gel content (crosslinking) and decrease in crystallinity of the encapsulants under hot-aerobic (90 degrees C, 22% RH) and hot-anaerobic (90 degrees C, sealed in N 2 air) aging were observed, even in the absence of UV and crosslinking initiators. Fourier transform infrared spectroscopy (FTIR)-attenuated total reflectance analysis showed insignificant encapsulant degradation, demonstrating the critical role of UV and moisture in accelerating degradation. Adhesion testing performed on coupon-level specimens (cell/encapsulant/glass laminates) showed decreases in adhesion energy, Gc , from 5000 h of hot-dry (90 degrees C, ~1% RH) and hot-humid (90 degrees C, 60% RH) aging. POE coupons demonstrated the best stability, followed by EPE then EVA. For EVA and POE, hot-humid aged coupons experienced a larger decrease in Gc due to enhanced hydrolytic degradation. Hot-dry aging condition demonstrated that thermal degradation of the interface could be significant even if the encapsulant experiences negligible degradation in the absence of UV and elevated humidity.

accelerated aging↗
DOE OSTI2013

Materials Challenges in Nuclear Energy

Nuclear power currently provides about 13% of the worldwide electrical power, and has emerged as a reliable baseload source of electricity. A number of materials challenges must be successfully resolved for nuclear energy to continue to make further improvements in reliability, safety and economics. The operating environment for materials in current and proposed future nuclear energy systems is summarized, along with a description of materials used for the main operating components. Materials challenges associated with power uprates and extensions of the operating lifetimes of reactors are described. The three major materials challenges for the current and next generation of water-cooled fission reactors are centered on two structural materials aging degradation issues (corrosion and stress corrosion cracking of structural materials and neutron-induced embrittlement of reactor pressure vessels), along with improved fuel system reliability and accident tolerance issues. The major corrosion and stress corrosion cracking degradation mechanisms for light water reactors are reviewed. The materials degradation issues for the Zr alloy clad UO2 fuel system currently utilized in the majority of commercial nuclear power plants is discussed for normal and off-normal operating conditions. Looking to proposed future (Generation IV) fission and fusion energy systems, there are 5 key bulk radiation degradation effects (low temperature radiation hardening and embrittlement, radiation-induced and modified solute segregation and phase stability, irradiation creep, void swelling, and high temperature helium embrittlement) and a multitude of corrosion and stress corrosion cracking effects (including irradiation-assisted phenomena) that can have a major impact on the performance of structural materials.

nuclear fuels↗
DOE OSTI2012

Electron Irradiation of Conjunctival Lymphoma-Monte Carlo Simulation of the Minute Dose Distribution and Technique Optimization

Purpose: External beam radiotherapy is the only conservative curative approach for Stage I non-Hodgkin lymphomas of the conjunctiva. The target volume is geometrically complex because it includes the eyeball and lid conjunctiva. Furthermore, the target volume is adjacent to radiosensitive structures, including the lens, lacrimal glands, cornea, retina, and papilla. The radiotherapy planning and optimization requires accurate calculation of the dose in these anatomical structures that are much smaller than the structures traditionally considered in radiotherapy. Neither conventional treatment planning systems nor dosimetric measurements can reliably determine the dose distribution in these small irradiated volumes. Methods and Materials: The Monte Carlo simulations of a Varian Clinac 2100 C/D and human eye were performed using the PENELOPE and PENEASYLINAC codes. Dose distributions and dose volume histograms were calculated for the bulbar conjunctiva, cornea, lens, retina, papilla, lacrimal gland, and anterior and posterior hemispheres. Results: The simulated results allow choosing the most adequate treatment setup configuration, which is an electron beam energy of 6 MeV with additional bolus and collimation by a cerrobend block with a central cylindrical hole of 3.0 cm diameter and central cylindrical rod of 1.0 cm diameter. Conclusions: Monte Carlo simulation is a useful method to calculate the minute dose distribution in ocular tissue and to optimize the electron irradiation technique in highly critical structures. Using a voxelized eye phantom based on patient computed tomography images, the dose distribution can be estimated with a standard statistical uncertainty of less than 2.4% in 3 min using a computing cluster with 30 cores, which makes this planning technique clinically relevant.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2017

Modular structure of highly ordered eudialyte and its place among hydrated minerals of rastsvetaevite family

The crystal structure of a representative of eudialyte group, which was found by A.P. Khomyakov at the Rasvumchorr mountain of the Khibiny alkaline massif (Kola Peninsula), has been studied by X-ray diffraction. The trigonal unit-cell parameters are found to be a = 14.2328(5) Å, c = 60.217(2) Å, V = 10564.08(3) Å3, sp. gr. R3m. The structure has been refined with the isotropic and anisotropic approximation displacement parameters to the total reliability factor R = 5.6%, based on 2989 reflections with |F| > 4σ(F). The idealized formula (Z = 3) is determined as [(H{sub 3}O){sub 11}Na{sub 10}K5]Cа{sub 12}(Na{sub 3}Fe{sub 2}Mn)Si{sub 4}Zr{sub 6}(Si{sub 48}O{sub 144})(OH,Cl){sub 5}(H{sub 2}O){sub 5}. The unit cell of the mineral is doubled due to the presence of two modules of different composition and structure in it (alluaivite-and kentbrooksite-like ones) and the formation of a polyhedral cluster in the kentbrooksite module. A comparison with two hydrated minerals having a modular structure shows that these minerals, being similar in their chemical composition, differ in the cation ordering over the sites of the two modules. The sample under study contains potassium in only one module, while oxonium groups are distributed in both modules but over different sites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Spin and orbital magnetism of coinage metal trimers (Cu{sub 3}, Ag{sub 3}, Au{sub 3}): A relativistic density functional theory study

We have demonstrated electronic structure and magnetic properties of Cu{sub 3}, Ag{sub 3} and Au{sub 3} trimers using a full potential local orbital method in the framework of relativistic density functional theory. We have also shown that the non-relativistic generalized gradient approximation for the exchange-correlation energy functional gives reliable magnetic properties in coinage metal trimers compared to experiment. In addition we have indicated that the spin-orbit coupling changes the structure and magnetic properties of gold trimer while the structure and magnetic properties of copper and silver trimers are marginally affected. A significant orbital moment of 0.21μ{sub B} was found for most stable geometry of the gold trimer whereas orbital magnetism is almost quenched in the copper and silver trimers.

36 MATERIALS SCIENCE↗
NASA NTRS1972

A comparison of reliability and conventional estimation of safe fatigue life and safe inspection intervals

Both the conventional and reliability analyses for determining safe fatigue life are predicted on a population having a specified (usually log normal) distribution of life to collapse under a fatigue test load. Under a random service load spectrum, random occurrences of load larger than the fatigue test load may confront and cause collapse of structures which are weakened, though not yet to the fatigue test load. These collapses are included in reliability but excluded in conventional analysis. The theory of risk determination by each method is given, and several reasonably typical examples have been worked out, in which it transpires that if one excludes collapse through exceedance of the uncracked strength, the reliability and conventional analyses gave virtually identical probabilities of failure or survival.

Hooke, F. H.↗
DOE OSTI2023

Reliability modeling in a predictive maintenance context: A margin-based approach

Current system reliability methods (typically based on fault trees or reliability block diagrams) can effectively propagate reliability data from the asset to the system level in order to identify system critical points. However, employed asset reliability data are an approximated integral representation of the past industrywide operational experience, and they neglect the present asset health status (available, for example, from online monitoring data and diagnostic assessments) and forecasted health projection (when available from prognostic models). Asset health should be informed solely by that specific asset’s current and historical performance data and should not be an approximated integral representation of the past industrywide operational experience (as currently performed by system reliability models through Bayesian updating processes). Sensor data, diagnostic assessments, and prognostic assessments are in fact not considered in plant reliability models used to inform system engineers on the most critical assets. In addition, the propagation of quantitative health data from the asset to the system level is a challenge given the diverse nature and structure of health data elements (e.g., vibration spectra, temperature readings, expected failure time). Ideally, in a predictive maintenance context, system reliability models should support decision making by propagating available health information from the asset to the system level in order to provide a quantitative snapshot of system health and identify the most critical assets. Here, this paper is directly addressing these two goals by proposing a different approach for reliability modeling that relies on asset diagnostic and prognostic assessments, along with monitoring data to measure asset health. The propagation of health data from the asset to the system level is performed through fault tree models not in probability terms, but in terms of margin where margin is the “distance” between the present status and an undesired event (e.g., failure or unacceptable performance). Through a cause-effect lens, while classical reliability models target the effect associated with asset performance, a margin-based approach focuses on the cause of an undesired asset performance (i.e., its health). Hence, thinking of reliability in terms of margins implies decision-making based on causal reasoning. We will show how fault tree models can be solved using a margin language and how this process can effectively assist system engineers to identify the most critical assets.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2016

SparseMaps—A systematic infrastructure for reduced-scaling electronic structure methods. III. Linear-scaling multireference domain-based pair natural orbital N-electron valence perturbation theory

Multi-reference (MR) electronic structure methods, such as MR configuration interaction or MR perturbation theory, can provide reliable energies and properties for many molecular phenomena like bond breaking, excited states, transition states or magnetic properties of transition metal complexes and clusters. However, owing to their inherent complexity, most MR methods are still too computationally expensive for large systems. Therefore the development of more computationally attractive MR approaches is necessary to enable routine application for large-scale chemical systems. Among the state-of-the-art MR methods, second-order N-electron valence state perturbation theory (NEVPT2) is an efficient, size-consistent, and intruder-state-free method. However, there are still two important bottlenecks in practical applications of NEVPT2 to large systems: (a) the high computational cost of NEVPT2 for large molecules, even with moderate active spaces and (b) the prohibitive cost for treating large active spaces. In this work, we address problem (a) by developing a linear scaling “partially contracted” NEVPT2 method. This development uses the idea of domain-based local pair natural orbitals (DLPNOs) to form a highly efficient algorithm. As shown previously in the framework of single-reference methods, the DLPNO concept leads to an enormous reduction in computational effort while at the same time providing high accuracy (approaching 99.9% of the correlation energy), robustness, and black-box character. In the DLPNO approach, the virtual space is spanned by pair natural orbitals that are expanded in terms of projected atomic orbitals in large orbital domains, while the inactive space is spanned by localized orbitals. The active orbitals are left untouched. Our implementation features a highly efficient “electron pair prescreening” that skips the negligible inactive pairs. The surviving pairs are treated using the partially contracted NEVPT2 formalism. A detailed comparison between the partial and strong contraction schemes is made, with conclusions that discourage the strong contraction scheme as a basis for local correlation methods due to its non-invariance with respect to rotations in the inactive and external subspaces. A minimal set of conservatively chosen truncation thresholds controls the accuracy of the method. With the default thresholds, about 99.9% of the canonical partially contracted NEVPT2 correlation energy is recovered while the crossover of the computational cost with the already very efficient canonical method occurs reasonably early; in linear chain type compounds at a chain length of around 80 atoms. Calculations are reported for systems with more than 300 atoms and 5400 basis functions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

UQpy: A general purpose Python package and development environment for uncertainty quantification

In this paper, we present the UQpy software toolbox, an open-source Python package for general uncertainty quantification (UQ) in mathematical and physical systems. The software serves as both a user-ready toolbox that includes many of the latest methods for UQ in computational modeling and a convenient development environment for Python programmers advancing the field of UQ. The paper presents an introduction to the software's architecture and existing capabilities, divided in the code in a set of modules centered around different UQ tasks such as sampling methods, generation of random processes and random fields, probabilistic inverse modeling, reliability analysis, surrogate modeling, and active learning. The paper also highlights the importance of the RunModel module, which is used to drive simulations in the uncertainty analyses performed in UQpy. This module conveniently allows the user to define computational models directly in Python, or to run simulations from a third-party software in serial or in parallel. To illustrate the various capabilities, two examples are tracked throughout the paper and analyzed repeatedly for various UQ tasks. The first is a Python model solving a nonlinear structural dynamics problem, used to illustrate UQpy's capabilities in sampling and forward propagation of high dimensional random vectors (stochastic processes), and probabilistic inference. The second model is a third-party Abaqus finite element model solving the thermomechanical response of a beam structure. This example is used to illustrate UQpy's capabilities in variance reduction sampling techniques, reliability analysis, surrogate modeling and active learning techniques.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Theoretical study of IR and photoelectron spectra of small gallium-arsenide clusters

Relative stabilities of small Ga{sub n}As{sub m} clusters, as well as their structural electronic and vibrational properties, were computed and analysed using a CCSD(T) reference method since experimental data in this area are sparse or unknown. With the aim of investigating larger clusters, we explored several DFT functionals and basis sets able to mimic the reliable CCSD(T) approach. Among them, the PBE0/SBKJC+sp,d appears as the most efficient to describe the structural and vibrational properties since average differences of about 0.042Å and 5.1cm{sup −1} were obtained for bond lengths and fundamental vibrational frequencies, respectively for the first small clusters [1] of the series found from our GSAM method [2]. As further test, this model is used in order to investigate and revisit an experimental IR spectrum of Ga{sub n}As{sub m} mixture previously published by Li et al. [3]. More complicated is the difficulty which arises in the electronic description due to the presence of numerous low lying electronic states nearly degenerated to correctly describe the electronic structure. The case of Ga{sub 2}As will be discussed and the photoelectron spectra of the Ga{sub 2}As anion reanalyzed on the ground of our calculations [4] comparatively to the experimental spectra obtained by Neumark and co-workers [5].

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2017

PRESAGE: Protecting Structured Address Generation against Soft Errors

Modern computer scaling trends in pursuit of larger component counts and power efficiency have, unfortunately, lead to less reliable hardware and consequently soft errors escaping into application data ("silent data corruptions"). Techniques to enhance system resilience hinge on the availability of efficient error detectors that have high detection rates, low false positive rates, and lower computational overhead. Unfortunately, efficient detectors to detect faults during address generation (to index large arrays) have not been widely researched. We present a novel lightweight compiler-driven technique called PRESAGE for detecting bit-flips affecting structured address computations. A key insight underlying PRESAGE is that any address computation scheme that flows an already incurred error is better than a scheme that corrupts one particular array access but otherwise (falsely) appears to compute perfectly. Enabling the flow of errors allows one to situate detectors at loop exit points, and helps turn silent corruptions into easily detectable error situations. Our experiments using PolyBench benchmark suite indicate that PRESAGE-based error detectors have a high error-detection rate while incurring low overheads.

Sharma, Vishal C.↗
DOE OSTI2018

Potential benefit of amorphization in the retention of gaseous species in irradiated pyrochlores

Understanding the structure-property relationship for materials destined for irradiation extremes is a key step in developing materials with reliable, long-term performance. One crucial relationship is the ability of a material to withstand or accommodate amorphization, as this dictates its potential use as a nuclear waste form. Pyrochlores are one such class of materials for consideration as waste forms and there has been significant work examining how both the crystal structure and chemistry impacts amorphization resistance, leading to the important conclusion that the amorphization resistance of pyrochlores (A 2 B 2 O 7 ) is very sensitive to the nature of the B cations. For example, pyrochlores with B=Ti amorphize much more readily than B=Zr compounds. However, there are still questions regarding how these types of materials respond to prolonged or high-dose irradiation conditions. Gd 2 Ti 2 O 7 (GTO) and Gd 2 Zr 2 O 7 (GZO) pyrochlores were implanted with 400 keV Kr++ ions at room temperature to calculated peak damages of 119 and 135 displacements per atom (dpa), respectively. As expected, GTO amorphized completely under irradiation. However, discrete bubbles of Kr coalesced within the amorphous matrix without micro-cracking or spallation. In contrast, GZO transforms to a disordered fluorite structure under irradiation with no indications of localized amorphization. But, the accumulation of Kr within the host material leads to sub-grain structures, extended defects, and the development of micro-cracks. Thus, while GTO readily amorphizes even under low dose irradiations, the resistance of the amorphous GTO matrix to micro cracking and gas release, even in the presence of large bubble formation, suggests an enhanced propensity to retain gaseous species. Finally, consideration of long-term dose accumulation effects in nuclear waste forms would suggest reconsideration of amorphization processes in pyrochlores and related materials as a potential beneficial effect for immobilization and long-term storage of actinide materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Precision Measurement of the Neutron Magnetic Form Factor via the Ratio Method at Jefferson Lab Hall A

Protons and neutrons, collectively known as nucleons, are composed of quarks and gluons. The Sachs electromagnetic form factors encode information about the spatial distributions of charge and magnetization in the nucleon, particularly at low momentum transfer. In particular, the neutron magnetic form factor (GMn) provides crucial information about the distribution of magnetization inside the neutron and helps constrain theoretical models of nucleon structure. Quasi-elastic electron scattering from deuterium was measured up to Q^2=13.5 GeV^2 using the Super BigBite Spectrometer in Hall A at Jefferson Lab. In this work, the neutron magnetic form factor GMn was extracted at Q^2 = 3.0 GeV^2 and Q^2=4.5 GeV^2 using the Ratio Method. These results represent a subset of the full dataset collected in this experiment, which extended to significantly higher Q^2. The extracted GMn values agree with the existing global fit within approximately two standard deviations at Q^2=3.0 and show excellent agreement at Q^2=4.5. The measurements achieved systematic uncertainties of about 2% and statistical uncertainties below 0.5%, among the most precise determinations of GMn at these kinematics. These results demonstrate the robustness of the experimental technique and provide an important validation point for future extractions at higher Q^2, where data remain scarce. In addition, the GRINCH heavy gas Cherenkov detector—a key component of the experimental apparatus—was commissioned and achieved an electron detection efficiency of approximately 97%, supporting reliable particle identification. Together, the analysis presented here advances both our understanding of nucleon structure and the validation of the experimental methods and instrumentation used to access it.

Satnik, Maria [College of William and Mary, Willia↗
DOE OSTI2015

Exploring the Random Phase Approximately for materials chemistry and physics

This proposal focuses on improved accuracy for the delicate energy differences of interest in materials chemistry with the fully nonlocal random phase approximation (RPA) in a density functional context. Could RPA or RPA-like approaches become standard methods of first-principles electronic-structure calculation for atoms, molecules, solids, surfaces, and nano-structures? Direct RPA includes the full exact exchange energy and a nonlocal correlation energy from the occupied and unoccupied Kohn-Sham orbitals and orbital energies, with an approximate but universal description of long-range van der Waals attraction. RPA also improves upon simple pair-wise interaction potentials or vdW density functional theory. This improvement is essential to capture accurate energy differences in metals and different phases of semiconductors. The applications in this proposal are challenges for the simpler approximations of Kohn-Sham density functional theory, which are part of the current “standard model” for quantum chemistry and condensed matter physics. Within this project we already applied RPA on different structural phase transitions on semiconductors, metals and molecules. Although RPA predicts accurate structural parameters, RPA has proven not equally accurate in all kinds of structural phase transitions. Therefore a correction to RPA can be necessary in many cases. We are currently implementing and testing a nonempirical, spatially nonlocal, frequency-dependent model for the exchange-correlation kernel in the adiabatic-connection fluctuation-dissipation context. This kernel predicts a nearly-exact correlation energy for the electron gas of uniform density. If RPA or RPA-like approaches prove to be reliably accurate, then expected increases in computer power may make them standard in the electronic-structure calculations of the future.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Three-dimensional phenotyping of peach tree-crown architecture utilizing terrestrial laser scanning

Tree training systems for temperate fruit have been developed throughout history by pomologists to improve light interception, fruit yield, and fruit quality. These training systems direct crown and branch growth to specific configurations. Quantifying crown architecture could aid the selection of trees that require less pruning or that naturally excel in specific growing/training system conditions. Regarding peaches [Prunus persica (L.) Batsch], access tools such as branching indices have been developed to characterize tree-crown architecture. However, the required branching data (BD) to develop these indices are difficult to collect. Traditionally, BD have been collected manually, but this process is tedious, time-consuming, and prone to human error. These barriers can be circumnavigated by utilizing terrestrial laser scanning (TLS) to obtain a digital twin of the real tree. TLS generates three-dimensional (3D) point clouds of the tree crown, wherein every point contains 3D coordinates (x, y, z). To facilitate the use of these tools for peach, we selected 16 young peach trees scanned in 2021 and 2022. These 16 trees were then modeled and quantified using the open-source software TreeQSM. As a result, “in silico” branching and biometric data for the young peach trees were calculated to demonstrate the capabilities of TLS phenotyping of peach tree-crown architecture. The comparison and analysis of field measurements (in situ) and in silico BD, biometric data, and quantitative structural model branch uncertainty data were utilized to determine the reconstructive model’s reliability as a source substitute for field measurements. Mean average deviation when comparing young tree (YT) height was approx. 5.93%, with crown volume was approx. 13.26% across both 2021 and 2022. All point clouds of the YTs in 2022 showed residuals lower than 12 mm to cylinders fitted to all branches, and mean surface coverage greater than 40% for both the trunk and primary branching orders.

09 BIOMASS FUELS↗
DOE OSTI2017

Radiation Dose–Dependent Hippocampal Atrophy Detected With Longitudinal Volumetric Magnetic Resonance Imaging

Purpose: After radiation therapy (RT) to the brain, patients often experience memory impairment, which may be partially mediated by damage to the hippocampus. Hippocampal sparing in RT planning is the subject of recent and ongoing clinical trials. Calculating appropriate hippocampal dose constraints would be improved by efficient in vivo measurements of hippocampal damage. In this study we sought to determine whether brain RT was associated with dose-dependent hippocampal atrophy. Methods and Materials: Hippocampal volume was measured with magnetic resonance imaging (MRI) in 52 patients who underwent fractionated, partial brain RT for primary brain tumors. Study patients had high-resolution, 3-dimensional volumetric MRI before and 1 year after RT. Images were processed using software with clearance from the US Food and Drug Administration and Conformité Européene marking for automated measurement of hippocampal volume. Automated results were inspected visually for accuracy. Tumor and surgical changes were censored. Mean hippocampal dose was tested for correlation with hippocampal atrophy 1 year after RT. Average hippocampal volume change was also calculated for hippocampi receiving high (>40 Gy) or low (<10 Gy) mean RT dose. A multivariate analysis was conducted with linear mixed-effects modeling to evaluate other potential predictors of hippocampal volume change, including patient (random effect), age, hemisphere, sex, seizure history, and baseline volume. Statistical significance was evaluated at α = 0.05. Results: Mean hippocampal dose was significantly correlated with hippocampal volume loss (r=−0.24, P=.03). Mean hippocampal volume was significantly reduced 1 year after high-dose RT (mean −6%, P=.009) but not after low-dose RT. In multivariate analysis, both RT dose and patient age were significant predictors of hippocampal atrophy (P<.01). Conclusions: The hippocampus demonstrates radiation dose–dependent atrophy after treatment for brain tumors. Quantitative MRI is a noninvasive imaging technique capable of measuring radiation effects on intracranial structures. This technique could be investigated as a potential biomarker for development of reliable dose constraints for improved cognitive outcomes.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Modelling single atom catalysts for water splitting and fuel cells: A tutorial review

Here, in this tutorial review, we report the state-of-the-art of the modeling approaches of Single Atom Catalysts (SAC) for water splitting and fuel cells reactions. The discussion applies for Hydrogen Evolution Reaction (HER), Oxygen Reduction Reaction (OER), Hydrogen Oxidation Reaction (HOR), and Oxygen Reduction Reaction (ORR). The main scope of this work is to underline the relevant aspects of SACs modelling. On the one hand, the review could help computational chemists aiming to start the study of SACs. On the other hand, experimentalists could find the critical analysis of DFT results of interest to understand better the strengths and weaknesses of simulations, and how to interpret computational results. After an introductory section of SACs, we start by briefly presenting the state-of-the-art methodologies. Then, we analyze the critical aspects for a reliable prediction of the electronic properties, and we discuss the robustness of the structural models and ways to validate them. Furthermore, we discuss the main approaches to predict catalytic activity and selectivity, which is the final goal of the computational catalysis. We conclude this review with a critical analysis of the current challenges in the field, and the main limitations of the modeling approaches that are described.

25 ENERGY STORAGE↗