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DOE OSTI2025

Application of machine learning interatomic potentials in heterogeneous catalysis

Heterogeneous catalysts are crucial in modern societies as they promote sustainability by enabling lower-energy pathways for various chemical reactions. While Density Functional Theory (DFT) computations can provide critical insights into how heterogeneous catalysts operate at the atomic level, they are limited by computational costs and unfavorable scaling with system size. Recently, machine learning interatomic potentials (MLIPs) have emerged as a promising alternative to DFT, offering near-DFT accuracy at significantly reduced cost. Here, in this perspective, we discuss the application of MLIPs in heterogeneous catalyst modeling as a surrogate for DFT. We detail how MLIPs have been applied in thermal catalysis to probe active sites, enable studying complex metallic and nanoporous catalysts, and investigate the reconstruction of catalytic surfaces. We review the use of MLIPs in electrocatalysis and photocatalysis, emphasizing their capabilities in studying transition metal oxide surfaces and solid–liquid interfaces. We also discuss the current limitations of MLIPs, particularly their challenges with transferability and description of non-local interactions. Finally, we conclude by identifying promising and underexplored domains in which MLIPs can further advance our understanding of heterogeneous catalysts.

Catalytic surfaces↗

DOE OSTI2021

Machine learning based inverse modeling of full-field strain distribution for mechanical characterization of a linear elastic and heterogeneous membrane

Heterogeneous membranes or films are thin and soft structures with spatial variations in material property and thickness. Mechanical behavior of heterogeneous membranes is not well understood, mainly due to the difficulty in obtaining accurate and reliable material property data. To understand the mechanical behavior of these materials, accurate and efficient characterization methods for heterogeneous membranes are needed. Here, in this paper, an inverse method based on machine learning is developed to efficiently extract mechanical properties from full-field strain distributions. This approach is demonstrated on a flat heterogeneous membrane with uniform thickness formed by up to four linear elastic synthetic materials in a grid arrangement, and deforming in a moderate strain range (true strain ~10%). The results show that the machine learning method achieves accuracy comparable to the traditional inverse finite element method, and is 6 orders of magnitude faster in the demonstrated case studies.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Compound pulse characteristics of a heterogeneous composite scintillator in a gamma-ray field

An important aspect of radiation detection in scintillators is the time dependence of emitted fluorescence, which results in characteristic measured pulse shape. In some materials, a relatively strong dependence of the scintillation pulse shape on stopping power exists, which can provide reliable identification of the incident particle. An alternative method to realize particle identification is by combining materials with different fluorescence lifetimes into heterogeneous structures. Such composite scintillators derive their properties from both the constituent material characteristics and the geometry of the composite structure. In composite scintillators with a high degree of heterogeneous loading, a superposition of fluorescence contributions originating in multiple materials, which is observed as single waveform with an intermediate pulse shape, may affect its ability to reject rays. We measure the time dependence of light output from a scintillator composed of 6 Li-containing glass shards and scintillating polyvinyl toluene and identify events that exhibit such compound behavior when exposed to rays and fast neutrons. We develop a modeling and simulation framework that reproduces the pulse shapes in heterogeneous scintillators and use it study the effect that the weight percentage of 6 Li glass has on rejection. The modeling framework is applied to the experimentally studied scintillator, finding a good agreement. Here, the developed modeling and simulation approach will help optimize the design of heterogeneous scintillators to meet the desired trade-o between neutron capture efficiency and -ray rejection.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

Chemical heterogeneity modulated zero thermal expansion alloy over super-wide temperature range

Chemical heterogeneity is usually avoided in solution chemistry, but it may still occur with sometimes dramatic effects on target materials and their properties. Here, we propose chemical heterogeneity as a counterintuitive strategy to design high-performance zero thermal expansion (ZTE) alloys. We apply this approach in a Hf-Ti-Fe alloy with excess Fe in the Hf/Ti sublattice and produce Hf/Ti concentration alternations at the micro level. Such chemical heterogeneity regulates local magnetic interactions in alloy and triggers a dispersed magnetic phase transition that modulates the thermal expansions at the micro level and hence results in a remarkable ZTE behavior over a super-wide temperature window from 10 to 480 K. This mechanism is supported by comprehensive studies on morphological microstructures, crystal and magnetic structures, and theoretical calculations. The strategy of local chemical heterogeneity opens up an avenue to design ZTE and the related functional materials directly via microstructure engineering.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Three Distinctive Steps for Heterogeneous Nucleation of Tunnel-Structured Mn Oxide on Quartz under Light Exposure

Natural manganese (Mn) oxide coatings, resulting from the heterogeneous nucleation on foreign substances, have garnered interest based on their importance in the reaction with organic substances and in environmental systems. However, the heterogeneous nucleation of the natural Mn oxide coatings still remains elusive. Here, via fast photochemical oxidation of Mn 2+ (aq), we show that Mn(IV) oxide nuclei form and aggregate on quartz in three distinct successive stages: (i) a nanocrystalline film of unaligned grain forms, (ii) nanoislands develop on the film, and (iii) nanorods form on the nanoislands. Each stage has different crystalline structures and forms by aligned attachment of nanoscale precursors on the preceding surface. Crystal lattice analyses confirm the crystalline development, from the short-range order of the Mn oxide film to the long-range order of the nanorods. Also, the heterogeneous nucleation observed in this work produced groutellite-like tunnel structures of Mn oxide on quartz. Furthermore, this revealed pathway of the heterogeneous nucleation can offer a new perspective on the variety of poorly crystalline structures of natural Mn oxides found in the environment, which can affect elemental redox cycles, contaminant sequestration and removal, and soil carbon storage.

Aligned attachment↗

DOE OSTI2023

Heterogenization of Homogeneous Ruthenium(II) Catalysts for Carbon-Neutral Dehydrogenation of Polyalcohols

Liquid organic hydrogen carrier (LOHC) systems are an excellent alternative to pressurized gas and liquid hydrogen storage technologies due to their high volumetric storage capacities and straightforward adaptation to existing infrastructure. Homogeneous catalysts are promising for the selective and reversible release of hydrogen from LOHC. However, separation from product mixtures and recycling inhibit their use, particularly when comprised of costly low-abundance elements, motivating the development of heterogeneous versions that are more easily recovered and reused. Here, we describe two methods for the heterogenization of molecular Ru catalysts that efficiently dehydrogenate the polyalcohol LOHCs ethylene glycol (EG) and 1,2-propanediol (1,2-PDO). The heterogeneous versions of these catalysts maintain catalytic activity for hydrogen production comparable to the homogeneous complexes, with up to 81% conversion and 99% selectivity. Further, DFT modeling indicates mechanistic similarities for the dehydrogenations of EG and 1,2-PDO, with the rate-limiting steps associated with protonation of the Ru–H bond to form H 2 and the alkoxide species coordinated to Ru(II), followed by β-hydride elimination to regenerate the Ru–H bond. Overall, the data suggest these heterogenized molecular catalysts have potential for practical use in polyalcohol-based LOHC systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Computational Investigation of the Role of Active Site Heterogeneity for aSupported Organovanadium(III) Hydrogenation Catalyst

A crucial consideration for supported heterogeneous catalysts is the nonuniformity of the active sites, particularly for supported organometallic catalysts. Standard spectroscopic techniques, such as X-ray absorption spectroscopy, reflect the nature of the most populated sites, which are often intrinsically structurally distinct from the most active catalytic sites. Additionally, with computational models, often, only a few representative structures are used to depict catalytic active sites on a surface, even though there are numerous observable factors of surface heterogeneity that contribute to the kinetically favorable active species. A previously reported study on the mechanism of a surface organovanadium-(III) catalyst [(SiO 2 )V III (Mes)(THF)] for styrene hydrogenation yielded two possible mechanisms: heterolytic cleavage and redox cycling. These two mechanistic scenarios are challenging to differentiate experimentally since the kinetic readouts of the catalyst are identical. To showcase the importance of modeling surface heterogeneity and its effect on catalytic activity, density functional theory (DFT) computational models of a series of potential active sites of [(SiO 2 )V III (Mes)(THF)] for the reaction pathways are applied in combination with kinetic Monte Carlo (kMC) simulations. Computed results were then compared to the previously reported experimental kinetic study: (1) DFT free-energy reaction pathways indicated the likely active site and pathway for styrene hydrogenation, a heterolytic cleavage pathway requiring a bare tripodal vanadium site. (2) From the kMC simulations, a mixture of different bond lengths from the support oxygen to the metal center was required to qualitatively describe the experimentally observed kinetic aspects of a supported organovanadium(III) catalyst for olefin hydrogenation. This work underscores the importance of modeling surface heterogeneity in computational catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Inorganic Sulfur Species Formed upon Heterogeneous OH Oxidation of Organosulfates: A Case Study of Methyl Sulfate

In this report recent studies reveal that organosulfates at the particle surface can be oxidized by gas-phase OH radicals with significant rates. Inorganic sulfur species, such as the bisulfate ion (HSO 4 - ) and sulfate ion (SO 4 2- ), can be formed upon these heterogeneous oxidation processes through the formation and subsequent reactions of sulfate radical anions (SO 4 •- ) in the particle phase. However, the amount of inorganic sulfur species produced in these heterogeneous oxidation reactions is not known. We investigate the heterogeneous OH oxidation of sodium methyl sulfate (CH 3 SO 4 Na), the smallest organosulfate detected in atmospheric particles, using an oxidation flow reactor at a relative humidity of 75%. We quantify the kinetics by measuring the decay of CH 3 SO 4 Na and the amount of HSO 4 - and SO 4 2- formed upon oxidation using ion chromatography. Kinetic measurements determine the heterogeneous OH reaction rate to be (5.72 ± 0.14) x 10 -13 cm 3 molecule -1 s -1 , with an effective OH uptake coefficient, γ eff , of 0.31 ± 0.06. The molar yield of inorganic sulfur species, defined as the total number of moles of HSO 4 - and SO 4 2- formed per mole of CH 3 SO 4 Na consumed upon oxidation, is found to be significant and has an average value of 0.62 ± 0.18 upon oxidation. A kinetic model is developed to describe the kinetics and inorganic sulfur species formation upon oxidation. Model simulations suggest that CH 3 SO 4 Na tends to decompose rapidly into formaldehyde and SO 4 •- , and the reaction of SO 4 •- with CH 3 SO 4 Na plays a significant role in both governing the kinetics and the formation of inorganic sulfur species.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Covalent organic frameworks in heterogeneous catalysis: recent advances and future perspective

Catalysis is ubiquitous in ~90% of chemical manufacturing processes and contributes up to 35% of global GDP. Hence, the development of advanced catalytic systems is of utmost importance for academia, industry, and government. Covalent organic frameworks (COFs) are a rapidly emerging class of crystalline porous materials that precisely integrate organic monomer units into extended periodic networks, offering a propitious platform for heterogeneous catalysis due to salient structural merits of ultralow density, high crystallinity, permanent porosity, structural tunability, functional diversity, and synthetic versatility. The past decade has witnessed an upsurge of interest in COFs for heterogeneous catalysis and this trend is expected to continue. In this review, we briefly introduce COF chemistry concerning the design principles, growth mechanism, and cutting-edge advances in structural evolution, linkage chemistry, and facile synthesis. Further, we then scrutinize four leading design strategies for COF catalysts, namely pristine COFs with catalytically active backbones, COFs as hosts for the inclusion of catalytic species, COF-based heterostructures, and COF-derived carbons for thermo-, photo-, and electrocatalysis. Next, we overview the most recent advances (mainly from 2020 to 2023) of COFs in heterogeneous catalysis, along with their fundamentals and advantages. Finally, we outline the current challenges and offer our perspectives on the future directions of COFs for heterogeneous catalysis.

36 MATERIALS SCIENCE↗

DOE OSTI2026

ZENN: A thermodynamics-inspired computational framework for heterogeneous data–driven modeling

Traditional entropy-based methods—such as cross-entropy loss in classification problems—have long been essential tools for representing the information uncertainty and physical disorder in data and for developing artificial intelligence algorithms. However, the rapid growth of data across various domains has introduced new challenges, particularly the integration of heterogeneous datasets with intrinsic disparities. To address this, we introduce a zentropy-enhanced neural network (ZENN), extending zentropy theory into the data science domain via intrinsic entropy, enabling more effective learning from heterogeneous data sources. ZENN simultaneously learns both energy and intrinsic entropy components, capturing the underlying structure of multisource data. To support this, we redesign the neural network architecture to better reflect the intrinsic properties and variability inherent in diverse datasets. We demonstrate the effectiveness of ZENN on classification tasks and energy landscape reconstructions, showing its superior generalization capabilities and robustness-particularly in predicting high-order derivatives. In image and text classification tasks, ZENN demonstrates superior generalization by introducing a learnable temperature variable that models latent multisource heterogeneity, allowing it to surpass state-of-the-art models on CIFAR-10/100, BBC News, and AG News. As a practical application in materials science, we employ ZENN to reconstruct the Helmholtz energy landscape of Fe3Pt using data generated from density functional theory and capture key material behaviors, including negative thermal expansion and the critical point in the temperature–pressure space. Overall, this work presents a zentropy-grounded framework for data-driven machine learning, positioning ZENN as a versatile and robust approach for scientific problems involving complex, heterogeneous datasets.

36 MATERIALS SCIENCE↗

DOE OSTI2024

IRIS: A Performance-Portable Framework for Cross-Platform Heterogeneous Computing

From edge to exascale, computer architectures are becoming more heterogeneous and complex. The systems typically have fat nodes, with multicore CPUs and multiple hardware accelerators such as GPUs, FPGAs, and DSPs. This complexity is causing a crisis in programming systems and performance portability. Several programming systems are working to address these challenges, but the increasing architectural diversity is forcing software stacks and applications to be specialized for each architecture. As we show, all of these approaches critically depend on their software framework for discovery, execution, scheduling, and data orchestration. To address this challenge, we believe that a more agile and proactive software framework is essential to increase performance portability and improve user productivity. To this end, we have designed and implemented IRIS: a performance-portable framework for cross-platform heterogeneous computing. IRIS can discover available resources, manage multiple diverse programming platforms (e.g., CUDA, Hexagon, HIP, Level Zero, OpenCL, OpenMP) simultaneously in the same execution, respect data dependencies, orchestrate data movement proactively, and provide for user-configurable scheduling. To simplify data movement, IRIS introduces a shared virtual device memory with relaxed consistency among different heterogeneous devices. IRIS also adds an automatic kernel workload partitioning technique using the polyhedral model so that it can resize kernels for a wide range of devices. Our evaluation on three architectures, ranging from Qualcomm Snapdragon to a Summit supercomputer node, shows that IRIS improves portability across a wide range of diverse heterogeneous architectures with negligible overhead.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Editorial: Cellular heterogeneity in plants

Multicellular eukaryotic organisms, such as plants, consist of various cell types. Despite possessing the same genetic information, each cell exhibits distinct utilization of this information, resulting in the development of unique molecular, physiological, and morphological properties as well as cellular heterogeneity within the organism. This cellular heterogeneity is needed to support plant development and adaptation to environmental changes. Identifying the mechanisms responsible for the differentiation of distinct cell types and precisely characterizing the molecular, biochemical, biophysical, and morphological characteristics of each cell type in various plant species remains a significant objective for plant scientists. Despite the biological importance of these cellular attributes, they have not been adequately described. In this Frontiers Research Topic, “Cellular Heterogeneity in Plants,” various scientific papers provide valuable new insights into the causes and consequences of cellular heterogeneity in plants.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Single-Cell Transcriptomic Analysis of Tumor-Derived Fibroblasts and Normal Tissue-Resident Fibroblasts Reveals Fibroblast Heterogeneity in Breast Cancer

Cancer-associated fibroblasts (CAFs) are a prominent stromal cell type in solid tumors and molecules secreted by CAFs play an important role in tumor progression and metastasis. CAFs coexist as heterogeneous populations with potentially different biological functions. Although CAFs are a major component of the breast cancer stroma, molecular and phenotypic heterogeneity of CAFs in breast cancer is poorly understood. In this study, we investigated CAF heterogeneity in triple-negative breast cancer (TNBC) using a syngeneic mouse model, BALB/c-derived 4T1 mammary tumors. Using single-cell RNA sequencing (scRNA-seq), we identified six CAF subpopulations in 4T1 tumors including: 1) myofibroblastic CAFs, enriched for α-smooth muscle actin and several other contractile proteins; 2) ‘inflammatory’ CAFs with elevated expression of inflammatory cytokines; and 3) a CAF subpopulation expressing major histocompatibility complex (MHC) class II proteins that are generally expressed in antigen-presenting cells. Comparison of 4T1-derived CAFs to CAFs from pancreatic cancer revealed that these three CAF subpopulations exist in both tumor types. Interestingly, cells with inflammatory and MHC class II-expressing CAF profiles were also detected in normal breast/pancreas tissue, suggesting that these phenotypes are not tumor microenvironment-induced. This work enhances our understanding of CAF heterogeneity, and specifically targeting these CAF subpopulations could be an effective therapeutic approach for treating highly aggressive TNBCs.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

A Comparison of Homogeneous and Heterogeneous Uranium Metal-Water Systems using Calculated and Experimental Critical Data

Heterogeneous effects of fissile units latticed in water has been documented in several forms in commonly referenced handbooks and guides. Many of these documents provide guidance for when heterogeneous systems are more reactive than their homogenous counterparts if controlling fissile mass or volume. This information provides insight into when heterogeneity should be considered for conservatism, however this information is not always displayed in a manner that is comparable to commonly referenced data, such as critical curves based on spherical systems. This paper aims to provide a juxtaposition of homogenous and heterogeneous uranium metal-water systems using both experimental and calculated critical data displayed in the format of commonly referenced critical curves. This format allows for easy comparison between the two systems against parameters that are often considered for single unit analysis such as: uranium density, fissile mass, system volume, and total system mass (fissile mass plus moderator mass). Calculated critical spherical systems provide an equal comparison between latticed geometry types as the latticed array can be cut off or restricted in the same manner in each series of models, which is not true for experimental values. Additionally, enrichment of the latticed units can be made uniform in the calculated systems, which is also difficult to achieve when referencing experimental data of varying latticed geometries. A comparison of calculated critical values and available experimental values is provided to show how these parameters can impact the critical spherical system result.

36 MATERIALS SCIENCE↗

DOE OSTI2022

A Comparison of Homogeneous and Heterogeneous Uranium Metal-Water Systems using Calculated and Experimental Critical Data

Heterogeneous effects of fissile units latticed in water has been documented in several forms in commonly referenced handbooks and guides. Many of these documents provide guidance for when heterogeneous systems are more reactive than their homogenous counterparts if controlling fissile mass or volume. This information provides insight into when heterogeneity should be considered for conservatism, however this information is not always displayed in a manner that is comparable to commonly referenced data, such as critical curves based on spherical systems. This paper aims to provide a juxtaposition of homogenous and heterogeneous uranium metal-water systems using both experimental and calculated critical data displayed in the format of commonly referenced critical curves. This format allows for easy comparison between the two systems against parameters that are often considered for single unit analysis such as: uranium density, fissile mass, system volume, and total system mass (fissile mass plus moderator mass). Calculated critical spherical systems provide an equal comparison between latticed geometry types as the latticed array can be physically cut off or restricted in the same manner in each series of models, which is not true for experimental values. Additionally, enrichment of the latticed units can be made uniform in the calculated systems, which is difficult to achieve when referencing experimental data of varying latticed geometries. A comparison of calculated critical values and available experimental values is provided to show how these parameters can impact the critical spherical system result.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Characterizing Temporal Heterogeneity by Quantifying Nanoscale Fluctuations in Amorphous Fe‐Ge Magnetic Films

Abstract Equilibrium phase transitions are influenced by fluctuations and often discussed within the framework of the Gibbs free energy, wherein the exchange of energy between system and thermal bath is stationary and all regions of the sample exhibit the same phase. Presence of spatial heterogeneity in the magnetic structures such as pinning centers, domain walls, topological defects, etc. may cause temporal heterogeneity that modifies the nature of the magnetic phase transition. This study reports that interplay of nanoscale thermodynamics with spatio‐temporal heterogeneity gives rise to complex phase transition pathways in amorphous Fe x Ge 1‐x thin films with temperature and Fe‐concentration ( x ). Coherent resonant soft X‐ray scattering experiments that have simultaneous spatial, temporal, and spectral sensitivity show that the origin of helical to paramagnetic phase transition in amorphous Fe‐Ge thin films lies in the appearance of enhanced‐fluctuation spots deep inside the ordered state. The fluctuations are heterogeneous, starting over a small fraction of the domains that increases and becomes isotropic over the entire film as the temperature increases or the Fe‐concentration decreases. The fluctuating‐fraction, when normalized to magnetization for different Fe‐concentrations, follows a single power law behavior, suggesting that the nature of the transition can be described in terms of the underlying spatio‐temporal fluctuations.

Singh, Arnab↗

DOE OSTI2020

Heterogeneous Nature of Electrocatalytic CO/CO 2 Reduction by Cobalt Phthalocyanines

Molecular catalysts for electrochemical CO 2 reduction have traditionally been studied in their dissolved states. However, the heterogenization of molecular catalysts has the potential to deliver much higher reaction rates and enable the reduction of CO 2 by more than two electrons. In light of the recently discovered reactivity of heterogenized cobalt phthalocyanine molecules to catalyze CO 2 reduction into methanol, direct comparison is needed to uncover the distinct catalytic activity and selectivity in homogeneous catalysis versus heterogeneous catalysis. In this work, soluble cobalt phthalocyanine derivatives were synthesized, and their catalytic activities in the homogeneous solutions were evaluated. The results show that the observed catalytic activities for both CO 2 -to-CO and CO-to-methanol conversions in aqueous solutions of the cobalt phthalocyanines are predominantly heterogeneous in nature through the adsorbed species on the electrode.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Dissecting the structural heterogeneity of proteins by native mass spectrometry

Abstract A single gene yields many forms of proteins via combinations of posttranscriptional/posttranslational modifications. Proteins also fold into higher‐order structures and interact with other molecules. The combined molecular diversity leads to the heterogeneity of proteins that manifests as distinct phenotypes. Structural biology has generated vast amounts of data, effectively enabling accurate structural prediction by computational methods. However, structures are often obtained heterologously under homogeneous states in vitro. The lack of native heterogeneity under cellular context creates challenges in precisely connecting the structural data to phenotypes. Mass spectrometry (MS) based proteomics methods can profile proteome composition of complex biological samples. Most MS methods follow the “bottom‐up” approach, which denatures and digests proteins into short peptide fragments for ease of detection. Coupled with chemical biology approaches, higher‐order structures can be probed via incorporation of covalent labels on native proteins that are maintained at the peptide level. Alternatively, native MS follows the “top‐down” approach and directly analyzes intact proteins under nondenaturing conditions. Various tandem MS activation methods can dissect the intact proteins for in‐depth structural elucidation. Herein, we review recent native MS applications for characterizing heterogeneous samples, including proteins binding to mixtures of ligands, homo/hetero‐complexes with varying stoichiometry, intrinsically disordered proteins with dynamic conformations, glycoprotein complexes with mixed modification states, and active membrane protein complexes in near‐native membrane environments. We summarize the benefits, challenges, and ongoing developments in native MS, with the hope to demonstrate an emerging technology that complements other tools by filling the knowledge gaps in understanding the molecular heterogeneity of proteins.

59 BASIC BIOLOGICAL SCIENCES↗