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DOE OSTI2025

Benders Decomposition Using Graph Modeling and Multi-Parametric Programming

Benders decomposition is a widely used method for solving large and structured optimization problems, but its performance is affected by the repeated solution of subproblems. We propose a flexible and modular algorithmic framework for accelerating Benders decomposition. Specifically, we express the problem structure by using a graph-theoretic modeling abstraction in which nodes represent optimization subproblems and edges represent connectivity between subproblems. A key innovation of our approach is that we embed multiparametric programming (mp) surrogates for node subproblems, which maps the exact analytical map of the subproblem solution space. The use of mp surrogates allows us to replace subproblem solves with fast look-ups and function evaluations for primal and dual variables during the iterative Benders process. We formally show the equivalence between classical Benders cuts and those derived from the mp solution. We implement our framework in the open-source PlasmoBenders.jl software package. To demonstrate the capabilities of the proposed framework, we apply it to a two-stage stochastic programming problem, which aims to make optimal capacity expansion decisions under market uncertainty. We evaluate both single-cut and multicut variants of Benders decomposition and show that the use of mp surrogates achieves substantial speedups in subproblem solve time, while preserving the convergence guarantees of Benders decomposition. We highlight advantages in solution analysis and interpretability that is enabled by mp critical region tracking; specifically, we show that these reveal how decisions evolve geometrically across the Benders search. Our results aim to demonstrate that combining surrogate modeling with graph modeling offers a promising and extensible foundation for structure-exploiting decomposition. In addition, by decomposing the problem into more tractable subproblems, the proposed approach also aims to overcome scalability issues of mp. Finally, the use of mp surrogates provides a unifying and modular optimization framework that enables the representation of heterogeneous node subproblems as modeling objects with a homogeneous structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Hollow Au Nanosphere-Cu 2 O Core–Shell Nanostructures with Controllable Core Surface Morphology

Design of metal-semiconductor interfaces and heterostructures is of strong interest for various catalytic applications including photocatalysis. Here, a series of hollow Au nanosphere (HGN)-Cu 2 O core-shell nanostructures with varying core surface rugosities are synthesized and investigated for possible photocatalytic applications. HGN surface rugosity is tuned by pH modification during galvanic exchange, and carboxyl groups are utilized as coordination sites to deposit uniform Cu 2 O shells onto the gold surfaces. Final core-shell structures are verified by transmission electron microscopy (TEM), scanning electron microscopy (SEM), energy-dispersive X-ray spectrometry (EDS), and X-ray diffraction (XRD). Information regarding chemical state and electronic band structure is acquired by X-ray photoelectron spectroscopy (XPS) and ultraviolet photoelectron spectroscopy (UPS). Ultrafast transient absorption (TA) reveals that charge separation in bumpy HGN (bHGN)-Cu 2 O may effectively provide longer-lived photoexcited carriers, offering great potential for utilization in advanced photocatalytic processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Reactivity of Sulfur Vacancy-Rich MoS 2 to Water Dissociation

Exposed Mo atoms on the surface of MoS 2 can catalyze certain useful chemical reactions, including the dissociation of water to produce hydrogen. However, a comprehensive understanding of water reactivity on defective MoS 2 surfaces remains elusive. Here, we use in situ near ambient pressure X-ray photoelectron spectroscopy (NAP-XPS) to investigate water dissociation reactions on MoS 2 surfaces before and after Ar + ion beam bombardment. To make the surfaces reactive, we treated them with Ar + ion beam sputtering first, which created exposed Mo sites. Using ultraviolet photoelectron spectroscopy (UPS) and density of states calculations conducted using density functional theory (DFT), we verified that stripping the surface of sulfur atoms creates metallic surface states that can catalyze water dissociation. At elevated H 2 O pressures, XPS measurements combined with DFT calculations suggested the presence of four distinct surface species from dissociated water. Specifically, we found that oxides and hydroxides are prominent at the surface, while chemisorbed and physisorbed H 2 O molecules are also present. In conclusion, this study provides new insights that reveal the prospects of surface-engineered MoS 2 as a catalyst for water dissociation.

08 HYDROGEN↗

DOE OSTI2026

Photoelectron Spectroscopic Determination of the Interfacial Energetics of Metal Oxide Protection Layers on p-InP Photocathodes

The interfacial energetics between p-type InP and a series of metal oxides, including TiO 2 , Nb 2 O 5 , Ta 2 O 5 , and HfO 2 , were evaluated using X-ray photoelectron spectroscopy (XPS), ultraviolet photoelectron spectroscopy (UPS), and optical absorption spectroscopy. The energy of the conduction-band minimum ( E cb ) of TiO 2 and Nb 2 O 5 was more negative (i.e., further from the vacuum level) than the conduction-band minimum at the surface of InP ( E cb,s ), whereas E cb for Ta 2 O 5 and HfO 2 was more positive than E cb,s for InP. The data are consistent with the electrochemical behavior of p-InP coated with various metal oxide candidate protection layers, with TiO 2 and Nb 2 O 5 facilitating interfacial transfer of photogenerated minority-carrier electrons in p-InP photocathodes, and Ta 2 O 5 and HfO 2 blocking photogenerated electrons in p-InP from readily transferring across the oxide-coated photocathodes. The energy of the valence-band maximum ( E vb ) for all of the oxides was much more negative than E vb,s for InP, consistent with observations that these protection layers effectively block hole transport and consequently suppress oxidative degradation of the underlying p-InP photocathodes.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

DOE OSTI2023

Vapor Phase Infiltration Improves Thermal Stability of Organic Layers in Perovskite Solar Cells

Despite the rapid increase in power conversion efficiency (PCE) of perovskite solar cells (PSCs) over the past decade, stability remains a major roadblock to commercialization. Here, this work shows vapor phase infiltration (VPI) as a tool to create hybrid organic–inorganic layers that improve the stability of organic charge transport layers, such as hole-selective spiro-OMeTAD in PSCs and in other organic electronic devices. Using X-ray photoelectron spectroscopy (XPS), ultraviolet photoelectron spectroscopy (UPS), and grazing incident wide-angle X-ray scattering (GIWAXS), we identify that infiltration of TiO x via VPI hinders the crystallization of the spiro-OMeTAD layer by likely preventing the π–π stacking of the molecules. Infiltrated PSCs retained more than 80% of their original efficiency after an operando stability test of 200 h at 75 °C, double the efficiency retained by devices without infiltration, in which the efficiency rapidly decreases in the first 50 h. This work provides a blueprint for using VPI to stabilize organic charge transport layers via prevention of π–π stacking leading to deleterious crystallization that shortens device lifetimes.

14 SOLAR ENERGY↗

DOE OSTI2026

In Situ Imaging Reveals Efficient Charge Separation in Monolayer MoS 2 –WS 2 Type-II Heterojunctions

Covalently bonded in-plane two-dimensional (2D) transition metal dichalcogenide (TMD) heterojunctions with atomically sharp interfaces hold great promise for photocatalytic applications in solar energy conversion and environmental remediation; however, their spatially resolved charge distribution and transport, particularly under operando conditions, remain poorly understood. Here, we employ photoscanning electrochemical microscopy (photo-SECM) to directly visualize photoinduced charge separation in monolayer MoS 2 –WS 2 in-plane heterojunctions. Spatial separation of photogenerated carriers is observed, with electrons accumulating in MoS 2 and holes in WS 2 , leading to strongly asymmetric interfacial kinetics: Fc + reduction proceeds rapidly on MoS 2 (0.6 cm s –1 ), whereas Fc oxidation on WS 2 is significantly slower (0.008 cm s –1 ). High-resolution surface photovoltage microscopy (SPVM) enables a quantitative comparison of charge-separation capacity across architectures. The in-plane MoS 2 –WS 2 heterojunction shows the largest photovoltage contrast (−35 mV in MoS 2 , 20 mV in WS 2 ), exceeding the vertical heterojunction (−18 mV in MoS 2 , 11 mV in WS 2 ) and the individual monolayers (−12 mV for MoS 2 , – 1 mV for WS 2 ), establishing the following trend: in-plane > vertical > monolayers. Ultraviolet photoelectron spectroscopy (UPS) indicates that this directional charge separation is driven by intrinsic type-II band alignment, while photoluminescence (PL) imaging shows that the interface acts as a recombination center that limits efficient carrier extraction. These results provide direct experimental evidence of type-II-driven charge separation in in-plane heterojunctions and offer critical insights for interface design in high-efficiency photocatalytic and optoelectronic systems.

electrical properties↗

DOE OSTI2020

Designing accurate emulators for scientific processes using calibration-driven deep models

Abstract Predictive models that accurately emulate complex scientific processes can achieve speed-ups over numerical simulators or experiments and at the same time provide surrogates for improving the subsequent analysis. Consequently, there is a recent surge in utilizing modern machine learning methods to build data-driven emulators. In this work, we study an often overlooked, yet important, problem of choosing loss functions while designing such emulators. Popular choices such as the mean squared error or the mean absolute error are based on a symmetric noise assumption and can be unsuitable for heterogeneous data or asymmetric noise distributions. We propose Learn-by-Calibrating, a novel deep learning approach based on interval calibration for designing emulators that can effectively recover the inherent noise structure without any explicit priors. Using a large suite of use-cases, we demonstrate the efficacy of our approach in providing high-quality emulators, when compared to widely-adopted loss function choices, even in small-data regimes.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Fast Bayesian optimization of Needle-in-a-Haystack problems using zooming memory-based initialization (ZoMBI)

Abstract Needle-in-a-Haystack problems exist across a wide range of applications including rare disease prediction, ecological resource management, fraud detection, and material property optimization. A Needle-in-a-Haystack problem arises when there is an extreme imbalance of optimum conditions relative to the size of the dataset. However, current state-of-the-art optimization algorithms are not designed with the capabilities to find solutions to these challenging multidimensional Needle-in-a-Haystack problems, resulting in slow convergence or pigeonholing into a local minimum. In this paper, we present a Zooming Memory-Based Initialization algorithm, entitled ZoMBI, that builds on conventional Bayesian optimization principles to quickly and efficiently optimize Needle-in-a-Haystack problems in both less time and fewer experiments. The ZoMBI algorithm demonstrates compute time speed-ups of 400× compared to traditional Bayesian optimization as well as efficiently discovering optima in under 100 experiments that are up to 3× more highly optimized than those discovered by similar methods.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Evidence for the utility of quantum computing before fault tolerance

Quantum computing promises to offer substantial speed-ups over its classical counterpart for certain problems. However, the greatest impediment to realizing its full potential is noise that is inherent to these systems. The widely accepted solution to this challenge is the implementation of fault-tolerant quantum circuits, which is out of reach for current processors. Here we report experiments on a noisy 127-qubit processor and demonstrate the measurement of accurate expectation values for circuit volumes at a scale beyond brute-force classical computation. We argue that this represents evidence for the utility of quantum computing in a pre-fault-tolerant era. These experimental results are enabled by advances in the coherence and calibration of a superconducting processor at this scale and the ability to characterize and controllably manipulate noise across such a large device. We establish the accuracy of the measured expectation values by comparing them with the output of exactly verifiable circuits. In the regime of strong entanglement, the quantum computer provides correct results for which leading classical approximations such as pure-state-based 1D (matrix product states, MPS) and 2D (isometric tensor network states, isoTNS) tensor network methods break down. These experiments demonstrate a foundational tool for the realization of near-term quantum applications.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Parallel quantum annealing

Quantum annealers of D-Wave Systems, Inc., offer an efficient way to compute high quality solutions of NP-hard problems. This is done by mapping a problem onto the physical qubits of the quantum chip, from which a solution is obtained after quantum annealing. However, since the connectivity of the physical qubits on the chip is limited, a minor embedding of the problem structure onto the chip is required. In this process, and especially for smaller problems, many qubits will stay unused. We propose a novel method, called parallel quantum annealing, to make better use of available qubits, wherein either the same or several independent problems are solved in the same annealing cycle of a quantum annealer, assuming enough physical qubits are available to embed more than one problem. Although the individual solution quality may be slightly decreased when solving several problems in parallel (as opposed to solving each problem separately), we demonstrate that our method may give dramatic speed-ups in terms of the Time-To-Solution (TTS) metric for solving instances of the Maximum Clique problem when compared to solving each problem sequentially on the quantum annealer. Additionally, we show that solving a single Maximum Clique problem using parallel quantum annealing reduces the TTS significantly.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Identifying the secondary electron cutoff in ultraviolet photoemission spectra for work function measurements of non-ideal surfaces

Abstract Absolute values of work functions can be determined in ultraviolet photoemission spectroscopy (UPS) by measuring the minimum kinetic energy of secondary electrons generated by a known photon energy. However, some samples can produce spectra that are difficult to interpret due to additional intensity below the true secondary electron cutoff. Disordered absorbates on elemental metals add small intensity below the onset for the transition metal surfaces studied, which can be attributed to energy losses after photoelectrons are generated. In contrast, spectra from WO 3−x films can produce multiple onsets with comparable intensity which do not fit this model. False onsets (in the context of work function measurements) can be minimized by optimizing experimental detection parameters including limiting analyzer acceptance angles and pass energy. True work functions can be identified by examining the onsets as the sample bias is varied.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2020

Analysis of multi-electron, multi-step homogeneous catalysis by rotating disc electrode voltammetry: theory, application, and obstacles

Rotating disc electrode (RDE) voltammetry has been widely adopted for the study of heterogenized molecular electrocatalysts for multi-step fuel-forming reactions but this tool has never been comprehensively applied to their homogeneous analogues. Here, the utility and limitations of RDE techniques for mechanistic and kinetic analysis of homogeneous molecular catalysts that mediate multi-electron, multi-substrate redox transformations are explored. Using the ECEC' reaction mechanism as a case study, two theoretical models are derived based on the Nernst diffusion layer model and the Hale transformation. Current–potential curves generated by these computational strategies are compared under a variety of limiting conditions to identify conditions under which the more minimalist Nernst Diffusion Layer approach can be applied. Based on this theoretical treatment, strategies for extracting kinetic information from the plateau current and the foot of the catalytic wave are derived. RDEV is applied to a cobaloxime hydrogen evolution reaction (HER) catalyst under non-aqueous conditions in order to experimentally validate this theoretical framework and explore the feasibility of RDE as a tool for studying homogeneous catalysts. Importantly, analysis of the foot-of-the-wave via this theoretical framework provides rate constants for elementary reaction steps that agree with those extracted from stationary voltammetric methods, supporting the application of RDE to study homogeneous fuel-forming catalysts. Lastly, obstacles encountered during the kinetic analysis of cobaloxime, along with the voltammetric signatures used to diagnose this reactivity, are discussed with the goal of guiding groups working to improve RDE set-ups and help researchers avoid misinterpretation of RDE data.

08 HYDROGEN↗

DOE OSTI2021

Rationalizing energy level alignment by characterizing Lewis acid/base and ionic interactions at printable semiconductor/ionic liquid interfaces

Charge transfer and energy conversion processes at semiconductor/electrolyte interfaces are controlled by local electric field distributions, which can be especially challenging to measure. Furthermore, we leverage the low vapor pressure and vacuum compatibility of ionic liquid electrolytes to undertake a layer-by-layer, ultra-high vacuum deposition of a prototypical ionic liquid EMIM + (1-ethyl-3-methylimidazolium) and TFSI – (bis(trifluoromethylsulfonyl)-imide) on the surfaces of different electronic materials. We consider a case-by-case study between a standard metal (Au) and four printed electronic materials, where interfaces are characterized by a combination of X-ray and ultraviolet photoemission spectroscopies (XPS/UPS). For template-stripped gold surfaces, we observe through XPS a preferential orientation of the TFSI anion at the gold surface, enabling large electric fields (~10 8 eV m –1 ) within the first two monolayers detected by a large surface vacuum level shift (0.7 eV) in UPS.

14 SOLAR ENERGY↗

DOE OSTI2020

Chapter 12: Photoelectron Spectroscopy Methods in Solar Cell Research

Photoelectron spectroscopy (PES), also referred to as photoemission spectroscopy, is a direct experimental method for assessing the chemical and electronic properties of materials. The technique is becoming increasingly important in the research of photovoltaic (PV) devices--where, more specifically, X-ray photoelectron spectroscopy (XPS) is used primarily to measure the chemical properties such as composition and contamination of solar cell materials, whereas ultraviolet photoelectron spectroscopy (UPS) reveals key electronic properties such as work function and electronic energy-level positions. PES is a surface-sensitive technique ideally suited for the analysis of thin films and interfaces, either completed ones or during their formation process. Because the new generation of PV devices comprise a multitude of complex interfaces--each of which plays a critical role for performance and functionality--PES analysis of functional cell components has gained even more relevance.

photoelectron spectroscopy↗

DOE OSTI2024

Evidence of a toroidal magnetic field in the core of 3C 84

The spatial scales of relativistic radio jets, probed by relativistic magneto-hydrodynamic (RMHD) jet launching simulations and by most very long baseline interferometry (VLBI) observations differ by an order of magnitude. Bridging the gap between these RMHD simulations and VLBI observations requires selecting nearby active galactic nuclei (AGN), the parsec-scale region of which can be resolved. The radio source 3C 84 is a nearby bright AGN fulfilling the necessary requirements: it is launching a powerful, relativistic jet powered by a central supermassive black hole, while also being very bright. Using 22 GHz globe-spanning VLBI measurements of 3C 84 we studied its sub-parsec region in both total intensity and linear polarisation to explore the properties of this jet, with a linear resolution of ~0.1 parsec. We tested different simulation set-ups by altering the bulk Lorentz factor Γ of the jet, as well as the magnetic field configuration (toroidal, poloidal, helical). We confirm the persistence of a limb brightened structure, which reaches deep into the sub-parsec region. The corresponding electric vector position angles (EVPAs) follow the bulk jet flow inside but tend to be orthogonal to it near the edges. Our state-of-the-art RMHD simulations show that this geometry is consistent with a spine-sheath model, associated with a mildly relativistic flow and a toroidal magnetic field configuration.

3C 84 (NGC 1275)↗

DOE OSTI2024

ATLAS Data Analysis using a Parallel Workflow on Distributed Cloud-based Services with GPUs

A new type of parallel workflow is developed for the ATLAS experiment at the Large Hadron Collider, that makes use of distributed computing combined with a cloud-based infrastructure. This has been developed for a specific type of analysis using ATLAS data, one popularly referred to as Simulation-Based Inference (SBI). The JAX library is used for the parts of the workflow to compute gradients as well as accelerate program execution using just-in-time compilation, which becomes essential in a full SBI analysis and can also offer significant speed-ups in more traditional types of analysis.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Spectroscopic signature of negative electronic compressibility from the Ti core-level of titanium carbonitride MXene

Two-dimensional transition metal carbides, carbonitrides, and nitrides called MXenes exhibit high metallic conductivity, ion intercalation capability and reversible redox activity, prompting their applications in energy storage and conversion, electromagnetic interference (EMI) shielding, and electronics, among many other fields. It has been shown that replacement of about 50% of carbon atoms in the most popular MXene family member, titanium carbide (Ti 3 C 2 T x ), by nitrogen atoms, forming titanium carbonitride (Ti 3 CNT x ), leads to drastically different properties, such as very high negative charge in solution and extreme EMI shielding effectiveness, exceeding all known materials, even metals at comparable thicknesses. Here, by using ultraviolet photoemission spectroscopy (UPS), the electronic structures of Ti 3 CNT x and Ti 3 C 2 T x are systematically investigated and compared as a function of charge carrier density. We observe that, in contrast to Ti 3 C 2 T x , the Ti 3p core-level of Ti 3 CNT x exhibits a counterintuitive shift to a lower binding energy of up to approximately 250 meV upon increasing the electron density, which is a spectroscopic signature of negative electronic compressibility (NEC). These experimentally measured chemical potential shifts are well-captured by the density functional theory (DFT) calculation. The DFT results also further suggest that the hybridization of titanium-nitrogen bonding in Ti 3 CNT x helps promoting the available states of Ti atoms for receiving more electron above the Fermi level and leads to the observed NEC. Furthermore, our findings explain the differences in electronic properties between the two very important and widely studied MXenes and also suggest a new strategy to apply the NEC effect of Ti 3 CNT x in energy and charge storage applications.

2D materials↗

DOE OSTI2021

An in situ ambient and cryogenic transmission electron microscopy study of the effects of temperature on dislocation behavior in CrCoNi-based high-entropy alloys with low stacking-fault energy

Temperature is known to affect deformation mechanisms in metallic alloys. As temperature decreases, the stacking-fault energy in many face-centered cubic (fcc) alloys decreases, resulting in a change of deformation mode from dislocation slip to deformation twinning. Such an impact of temperature can be more complex in compositionally heterogeneous microstructures that exhibit, for example, local concentration fluctuation such as that in multi-principal element alloys. In this work, we compare the dislocation behavior and mechanical properties of a fcc Cr 20 Mn 10 Fe 30 Co 30 Ni 10 high-entropy alloy at ambient and liquid-nitrogen temperatures. We find that a network of stacking faults is formed by uniformly extended dislocations at ambient temperatures with low stacking-fault energy, whereas at lower temperatures, uneven dissociation of dislocations becomes significant, which results in severe dislocation pile-ups together with their pronounced entanglement. Our findings indicate that as the stacking-fault energy decreases with decreasing temperature, the heterogeneity of the distribution of elements becomes more dominant in tuning the local variation of lattice resistance. As a result, the change in dislocation behavior at low temperatures strongly affects microstructural evolution and consequently leads to significantly more pronounced work hardening.

36 MATERIALS SCIENCE↗