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DOE OSTI2023

Protonic Ceramic Electrochemical Cells for Synthesizing Sustainable Chemicals and Fuels

Abstract Protonic ceramic electrochemical cells (PCECs) have been intensively studied as the technology that can be employed for power generation, energy storage, and sustainable chemical synthesis. Recently, there have been substantial advances in electrolyte and electrode materials for improving the performance of protonic ceramic fuel cells and protonic ceramic electrolyzers. However, the electrocatalytic materials development for synthesizing chemicals in PCECs has gained less attention, and there is a lack of systematic and fundamental understanding of the PCEC reactor design, reaction mechanisms, and electrode materials. This review comprehensively summarizes and critically evaluates the most up‐to‐date progress in employing PCECs to synthesize a wide range of chemicals, including ammonia, carbon monoxide, methane, light olefins, and aromatics. Factors that impact the conversion, selectivity, product yield, and energy efficiencies are discussed to provide new insights into designing electrochemical cells, developing electrode materials, and achieving economically viable chemical synthesis. The primary challenges associated with producing chemicals in PCECs are highlighted. Approaches to tackle these challenges are then offered, with a particular focus on deliberately designing electrode materials, aiming to achieve practically valuable product yield and energy efficiency. Finally, perspectives on the future development of PCECs for synthesizing sustainable chemicals are provided.

03 NATURAL GAS↗

DOE OSTI2023

Chemical structure–property relationships in nanocelluloses

Abstract Nanocelluloses, nanoscale cellulosic particles or fibrils, are an appealing class of nanomaterials with enormous potential for sustainable development. They have great promise to target some of the 17 Sustainable Development Goals outlined by the United Nations. Nanocelluloses are derived from the most abundant biopolymer in the world, cellulose, which have multiple hydroxyl groups on their surface, enabling a vast range of chemical modifications. The interplay between the chemical structure and physicochemical properties of nanocelluloses is crucial to engineering the next generation of green, functional nanomaterials. In this review paper, we provide a comprehensive account of the structure–property relationships in nanocelluloses, which may establish the basis for the design of precision bio‐based materials. Chemical modifications of nanocelluloses, including hydrolysis, oxidation, esterification, amidation, and polymer grafting, provide an array of chemical and physical properties that open opportunities in a diverse spectrum of applications. We review how chemical modifications affect the physicochemical properties of nanocelluloses, such as thermal stability, hydrophobicity, and dispersibility in nonpolar media. Understanding nanocellulose chemical structure–property relationships is integral to the development of sustainable material platforms based on the most renewable biopolymer on earth.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Chemical changes from N-doped graphene and Metal-Organic Frameworks to N-G/MOF composites for improved electrocatalytic activity

Integrating N doped graphene (N G) with Metal Organic Frameworks (MOFs) enhances catalytic activity for oxygen reduction reaction (ORR), often exceeding both the performances of their precursors and, in some cases, even PGM based catalysts. However, the factors driving this improved catalytic activity in N G/MOF composites remain unexplored, particularly from the perspective of the chemical changes. To investigate the chemical changes in N G and MOF upon their integration and the implications of these changes on ORR catalytic activity, an N G/MOF was synthesized from N G with a MOF (ZIF 8) following a mechanochemical wet ball milling process. The N G, ZIF 8, and N G/MOF samples were examined for changes in elemental composition, chemical state of carbon, different nitrogen and carbon bonds, and other chemical interactions. In the N G/MOF catalyst, compared to its N G and ZIF 8 precursors, the relative oxygen content increased, indicating the formation of additional oxygen containing groups. The C 1s peak shifted to a lower binding energy in N G/MOF, suggesting changes in the overall chemical or oxidation state of the carbon atoms. Besides, the increase in pyridinic N functional groups in N G/MOF points to the formation of additional active sites. Furthermore, the formation of C Zn bonds in N G/MOF suggests the probable emergence of single atom Zn sites, while the increase in C=O bonds points to the formation of carboxyl or carbonyl groups. These chemical changes could be linked to the enhanced electrocatalytic activity of the N G/MOF composite for ORR. In conclusion, this study may also be beneficial for other research focused on developing composite catalysts involving various N G and MOF materials.

25 ENERGY STORAGE↗

DOE OSTI2021

Chemical degradation of fly ash blended concrete with the seasonal variation of rainwater in a radioactive waste repository: A thermodynamic modeling approach

Highlights: • The thermodynamic model for the cementitious system was successfully developed. • The chemical degradation of concrete was greatly affected by rainwater types. • Inorganic carbon species in rainwater reduced the chemical resistance of concrete. • The durability of concrete to rainwater decreased with increasing fly ash content. This study presents a long-term degradation behavior of fly ash blended concrete in a vault type low- and intermediate-level radioactive waste (LILW) repository by thermodynamic equilibrium calculations using PHREEQC combined with CEMDATA18 database. Since rainwater plays a predominant role as leachate for the concrete waste container in the repository, the effect of chemical properties of seasonal rainwater on the chemical degradation of concrete was analyzed. In addition, the impact of the blending with fly ash on the chemical degradation was evaluated through a gradual replacement of ordinary Portland cement (OPC) by fly ash. Regardless of the replacement level, autumn rainwater showed the greatest influence on the concrete degradation owing to the presence of inorganic carbon species, which induce the carbonation. The resistance of concrete to chemical degradation by rainwater was persistently reduced due to the decreasing formation of portlandite and calcium silicate hydrate (C-S-H) with increasing replacement level.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Decarbonization of the Chemical Industry Through Electrification: Barriers and Opportunities

The chemical industry is a major source of economic productivity and employment globally and among the top 3 industrial sources of greenhouse gas (GHG) emissions, along with steel and cement. As global demand for chemical products continues to grow, there is an urgency to develop and deploy sustainable chemical production pathways and to reconsider continued investment in current emission-intensive production technologies. This perspective describes the challenges and opportunities to decarbonize the chemical industry via electrification powered by low-carbon electricity supply, both in the near term and long term, and it discusses four technological pathways ranging from the more mature direct substitution of heat with electricity and use of hydrogen to technologically less mature, yet potentially more selective, approaches based on electrochemistry and plasma. Finally, we highlight the key elements of integrating an electrified industrial process with the power sector to leverage process flexibility to reduce energy costs of chemical production and provide valuable power grid support services. Unlocking such plant-to-grid coordination and the four electrification pathways has significant potential to facilitate rapid and deep decarbonization of the chemical industry sector.

chemical synthesis↗

DOE OSTI2025

Thermo-mechanical deterioration and molecular degradation of 3D-printed methacrylate-based polymer in various chemical environments

The advancement of additive manufacturing (AM) has accelerated the development of stereolithographic (SLA) photo-curable resins, particularly methacrylate-based polymers, due to the ability to their high-resolution, robust mechanical properties, and suitability. However, their long-term performance in chemical environments remains poorly understood. This study investigates the extent and mechanisms of degradation on an SLA-printed methacrylate-based polymer subjected to various chemicals, including polar and non-polar solvents, as well as strongly acidic aqueous solutions over a 12-week accelerated aging period. A comprehensive analytical approach incorporating swelling kinetics, surface morphology, tensile and dynamic mechanical analysis (DMA), Fourier-transform infrared (FTIR) spectroscopy, and mass spectrometry (MS) was employed to characterize chemical absorption, structural integrity, and leached products. Results reveal that degradation severity is governed by both the polarity and reactivity of the chemical environment. Notably, exposure to 6 mol L -1 HNO₃ induced the most severe deterioration, with over threefold higher swelling compared to other media, and significant reductions in tensile strength, tensile modulus, and glass transition temperature (T g ). In contrast, specimens aged in non-polar solvents (xylene and dodecane) exhibited negligible chemical interaction and retained mechanical performance. FTIR and MS analyses identified acid-catalyzed hydrolysis of ester groups as prominent degradation pathways in acidic media, while diffusion-controlled plasticization prevailed in polar solvents. Furthermore, this study provides valuable insights into the chemical stability of SLA-printed polymers and develops predictive degradation profiles that are crucial for designing durable polymer systems for advanced industrial use.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Advances in electrosynthesis for a greener chemical industry

As nations unite to curb anthropogenic greenhouse gas emissions, the decarbonization of the chemical industry has been propelled to the forefront of scientific research. Renewable electricity will play a central role in this effort. In addition to powering chemical plants and allowing for the sustainable production of heat to drive thermocatalytic processes, renewable electricity also provides the chemical industry with opportunities to engage in the sustainability revolution and broadly reduce its environmental footprint through breakthrough innovations in direct electrochemical transformations. The electrification of chemical synthesis—electrosynthesis—is a promising route to promote sustainability without compromising economic competitiveness. Electrosynthesis uses electrons both as an energy source to drive reactions and as a green reagent for chemical reductions and oxidations under ambient conditions. Therefore, it holds tremendous potential (pun intended) to increase selectivity to desired products, open green reaction pathways for challenging transformations (e.g., Birch reduction, epoxidations, coupling reactions), and reduce chemical waste.

08 HYDROGEN↗

DOE OSTI2022

Chemical order-disorder nanodomains in Fe 3 Pt bulk alloy

Chemical ordering is a common phenomenon and highly correlated with the properties of solid materials. By means of the redistribution of atoms and chemical bonds, it invokes an effective lattice adjustment and tailors corresponding physical properties. To date, however, directly probing the 3D interfacial interactions of chemical ordering remains a big challenge. In this work, we deciphered the interlaced distribution of nanosized domains with chemical order/disorder in Fe 3 Pt bulk alloy. HAADF-STEM images evidence the existence of such nanodomains. The reverse Monte Carlo method with the X-ray pair distribution function data reveal the 3D distribution of local structures and the tensile effect in the disordered domains at the single-atomic level. The chemical bonding around the domain boundary changes the bonding feature in the disordered side and reduces the local magnetic moment of Fe atoms. This results in a suppressed negative thermal expansion and extended temperature range in Fe 3 Pt bulk alloy with nanodomains. Our study demonstrates a local revelation for the chemical order/disorder nanodomains in bulk alloy. The understanding gained from atomic short-range interactions within the domain boundaries provides useful insights with regard to designing new functional compounds.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Application of Gaussian Bayes classifier to differentiate chlorine-based chemical agents

The Portable Isotopic Neutron Spectroscopy (PINS) is a commercialized system developed by Idaho National Laboratory (INL) to examine chemical warfare agents (CWA) non-destructively, utilizing Prompt Gamma Neutron Activation Analysis (PGNAA) techniques. The PINS system takes advantage of a high-resolution gamma-ray spectrum from a mechanically-cooled high-purity germanium (HPGe) detector. One of the difficult technical challenges is to discriminate the chlorine-based chemical agents. Especially, CN, CNB, CNS and CG have similar chemical compositions to make it hard to discriminate them with a higher confidence. Current identification algorithms for PINS systems with 252-Cf sources have been improved and updated continuously as more field data became available, and new algorithms was studied to complement the current algorithms by adopting the Gaussian Bayes classifier. These new algorithms were intended to be applied to a subset of chlorine-based chemical agents, and their main goal is discriminate CN, CNB, CNS and CG with their ratios of the chlorine neutron inelastic 1763keV peak to the chlorine thermal neutron capture 1959keV peak, which is referred to as the “Cl i/c” or “clic” ratio in this study. The Cl i/c ratios were assumed to follow Gaussian distributions with the means and the standard deviations unique to their corresponding chemical agents. The prior probabilities of these four chemical agents were optimized with a collection of field data to achieve the best performance in terms of precision or positive predictive value (PPV). Finally, their posterior probabilities as functions of the Cl i/c ratio were implemented in the current version of PINS analysis software in order to be tested with more field data.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2021

Catalytic Fast Pyrolysis for Chemicals: Cooperative Research and Development, CRADA Number CRD-16-00637 (Final Report)

The purpose of this partnership between the ExxonMobil Chemical Company and NREL is to advance the state of the art for converting biomass to liquid hydrocarbons using catalytic fast pyrolysis (CFP), with particular emphasis on directing and improving yields of such liquid hydrocarbons for uses in commodity chemical markets. CFP of biomass is a promising route for the production of renewable fuels and chemicals, and the key driver for economic viability is carbon yield to valuable products. The majority of prior CFP work has been targeted at fuel production, but this CRADA seeks to pursue routes to chemical co-products, thereby enhancing the overall economic viability of CFP. This project is beneficial to the public because it advances a technology that could one day provide renewable fuels and chemicals to our economy, thus improving the sustainability of our transportation and chemical manufacturing sectors.

09 BIOMASS FUELS↗

DOE OSTI2021

Using Dissipative Particle Dynamics to Model Effects of Chemical Reactions Occurring within Hydrogels

Computational models that reveal the structural response of polymer gels to changing, dissolved reactive chemical species would provide useful information about dynamically evolving environments. However, it remains challenging to devise one computational approach that can capture all the interconnected chemical events and responsive structural changes involved in this multi-stage, multi-component process. Here, we augment the dissipative particle dynamics (DPD) method to simulate the reaction of a gel with diffusing, dissolved chemicals to form kinetically stable complexes, which in turn cause concentration-dependent deformation of the gel. Using this model, we also examine how the addition of new chemical stimuli and subsequent reactions cause the gel to exhibit additional concentration-dependent structural changes. Through these DPD simulations, we show that the gel forms multiple latent states (not just the “on/off”) that indicate changes in the chemical composition of the fluidic environment. Hence, the gel can actuate a range of motion within the system, not just movements corresponding to the equilibrated swollen or collapsed states. Moreover, the system can be used as a sensor, since the structure of the layer effectively indicates the presence of chemical stimuli.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Understanding the Role of Cesium on Chemical Complexity in Methylammonium-Free Metal Halide Perovskites

Mixed cesium- and formamidinium-based metal halide perovskites (MHPs) are emerging as ideal photovoltaic materials due to their promising performance and improved stability. While theoretical predictions suggest that a larger composition ratio of Cs (≈30%) aids the formation of a pure photoactive α-phase, high photovoltaic performances can only be realized in MHPs with moderate Cs ratios. In fact, elemental mixing in a solution can result in chemical complexities with non-equilibrium phases, causing chemical inhomogeneities localized in the MHPs that are not traceable with global device-level measurements. Thus, the chemical origin of the complexities and understanding of their effect on stability and functionality remain elusive. Herein, through spatially resolved analyses, the fate of local chemical structures, particularly the evolution pathway of non-equilibrium phases and the resulting local inhomogeneities in MHPs is comprehensively explored. It is illustrated that Cs-rich MHPs have substantial local inhomogeneities at the initial crystallization step, which do not fully convert to the α-phase and thereby compromise the optoelectronic performance of the materials. These fundamental observations allow the authors to draw a complete chemical landscape of MHPs including nanoscale chemical mechanisms, providing indispensable insights into the realization of a functional materials platform.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Atomistic Simulations of Thermal and Chemical Expansions of PrNi x Co 1‐x O 3‐δ Accelerated by Machine Learning Potentials

The electrodes and solid-state electrolytes in protonic ceramic electrochemical cells (PCECs) experience significant lattice expansions when exposed to high steam concentrations at elevated temperatures. In this paper, phonon calculations based on a new machine learning potential (MLP) are employed to elucidate the volume expansions of the proton-conducting PrNi x Co 1-x O 3-δ (PNC) lattices, manifested under a combined influence of oxygen vacancies (V$^{\cdot\cdot}_O$ ) and proton uptake (OH$^{\cdot}_O$ ) in the bulk at varying Ni/Co occupancies. It is revealed that the Ni/Co occupancy contributes to thermal and chemical expansions differently, where thermal expansions are related to Co occupancy. In contrast, chemical expansions are more closely associated with the Ni occupancy. Both V$^{\cdot\cdot}_O$ and OH$^{\cdot}_O$ lead to higher thermal expansions when compared to the pristine PNC. The temperature increase will negatively impact the hydration-induced chemical expansions. For combined thermal and chemical expansions, it is predicted that the strategies that boost the PCEC's electrochemical performance may harm the electrode–electrolyte interfacial stability, when the Ni occupancy is high, due to severe chemical expansions. Mitigating chemical expansions of the Ni-abundant PNC will benefit the interfacial stability. Finally, the presented computational methods for phonon calculations, based on emerging machine learning interatomic potential techniques are anticipated to have a lasting impact on future PCEC development.

computational prediction↗

DOE OSTI2021

Perseverance’s Scanning Habitable Environments with Raman and Luminescence for Organics and Chemicals (SHERLOC) Investigation

The Scanning Habitable Environments with Raman and Luminescence for Organics and Chemicals (SHERLOC) is a robotic arm-mounted instrument on NASA’s Perseverance rover. SHERLOC has two primary boresights. The Spectroscopy boresight generates spatially resolved chemical maps using fluorescence and Raman spectroscopy coupled to microscopic images (10.1 μm/pixel). The second boresight is a Wide Angle Topographic Sensor for Operations and eNgineering (WATSON); a copy of the Mars Science Laboratory (MSL) Mars Hand Lens Imager (MAHLI) that obtains color images from microscopic scales (~13 μm/pixel) to infinity. SHERLOC Spectroscopy focuses a 40 μs pulsed deep UV neon-copper laser (248.6 nm), to a ~100 μm spot on a target at a working distance of ~48 mm. Fluorescence emissions from organics, and Raman scattered photons from organics and minerals, are spectrally resolved with a single diffractive grating spectrograph with a spectral range of 250 to ~370 nm. Because the fluorescence and Raman regions are naturally separated with deep UV excitation (<250 nm), the Raman region ~ 800 – 4000 cm -1 (250 to 273 nm) and the fluorescence region (274 to ~370 nm) are acquired simultaneously without time gating or additional mechanisms. SHERLOC science begins by using an Autofocus Context Imager (ACI) to obtain target focus and acquire 10.1 μm/pixel greyscale images. Chemical maps of organic and mineral signatures are acquired by the orchestration of an internal scanning mirror that moves the focused laser spot across discrete points on the target surface where spectra are captured on the spectrometer detector. ACI images and chemical maps (< 100 μm/mapping pixel) will enable the first Mars in situ view of the spatial distribution and interaction between organics, minerals, and chemicals important to the assessment of potential biogenicity (containing CHNOPS). Single robotic arm placement chemical maps can cover areas up to 7x7 mm in area and, with the < 10 min acquisition time per map, larger mosaics are possible with arm movements. This microscopic view of the organic geochemistry of a target at the Perseverance field site, when combined with the other instruments, such as Mastcam-Z, PIXL, and SuperCam, will enable unprecedented analysis of geological materials for both scientific research and determination of which samples to collect and cache for Mars sample return.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Visualization of in-situ chemical flow through sand using neutron radiography

Chemical movement through soil is an important process in agriculture and ecology. Observing the spatial and temporal dynamics of these processes using conventional chemical ecology methods requires techniques that are destructive and/or lack resolution. Neutron radiography has the capability to allow chemical motion through sand/soil to be tracked with high spatial and temporal resolution, and we show that it allows for the motion of hydrophobic and hydrophilic chemicals to be distinguished. This technique can have an important impact on introducing neutron radiography to a wider community and into our understanding of chemical communication dynamics between plants and movement of applied chemicals in agricultural soils.

MORRIS, KATHRYN [Xavier University]↗

DOE OSTI2020

Modeling of Hidden Structures Using Sparse Chemical Shift Data from NMR Relaxation Dispersion

NMR relaxation dispersion measurements report on conformational changes occurring on the μs-ms timescale. Chemical shift information derived from relaxation dispersion can be used to generate structural models of weakly populated alternative conformational states. Current methods to obtain such models rely on determining the signs of chemical shift changes between the conformational states, which are difficult to obtain in many situations. Here, we use a “sample and select” method to generate relevant structural models of alternative conformations of the C-terminal-associated region of Escherichia coli dihydrofolate reductase (DHFR), using only unsigned chemical shift changes for backbone amides and carbonyls ( 1 H, 15 N, and 13 C'). We find that CS-Rosetta sampling with unsigned chemical shift changes generates a diversity of structures that are sufficient to characterize a minor conformational state of the C-terminal region of DHFR. The excited state differs from the ground state by a change in secondary structure, consistent with previous predictions from chemical shift hypersurfaces and validated by the x-ray structure of a partially humanized mutant of E. coli DHFR (N23PP/G51PEKN). The results demonstrate that the combination of fragment modeling with sparse chemical shift data can determine the structure of an alternative conformation of DHFR sampled on the μs-ms timescale. Such methods will be useful for characterizing alternative states, which can potentially be used for in silico drug screening, as well as contributing to understanding the role of minor states in biology and molecular evolution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Highlighting the Importance of Authentic Reference Chemicals in the Unambiguous Identification of Unknowns during Routine Sample Analysis─An OPCW Proficiency Test Case

The unequivocal identification of unknown chemicals during routine sample analysis is a constant occurrence in the field of analytical chemistry. The process can be painstakingly tedious, particularly in situations where a tentatively identified unknown may possess isomeric counterparts yielding identical accurate mass values and very similar mass spectra. In this work, we present the experimental process involved in the correct identification of 1,4-oxathiane 4,4-dioxide and differentiation from its constitutional isomer, 2-hydroxyethyl vinyl sulfone, when present in a silica gel matrix featured in the 54th Environmental Organisation for the Prohibition of Chemical Weapons (OPCW) proficiency test. After discovering that the library-generated mass spectrum for 2-hydroxyethyl vinyl sulfone in a preliminary gas chromatography–mass spectrometry (GC-MS) analysis did not match the one from an authentic reference chemical, we embarked on an unknown structure determination campaign involving GC-MS, liquid chromatography-tandem mass spectrometry (LC-MS-MS), and nuclear magnetic resonance (NMR) spectroscopy. All of the information obtained, coupled to the synthesis of an authentic reference chemical, was used to determine the identity of the unknown as 1,4-oxathiane 4,4-dioxide. The process described in this work highlights the important role played by authentic reference chemicals in the identification of unknown chemicals during routine sample analysis.

Chemistry↗

DOE OSTI2024

Neural network kinetics for exploring diffusion multiplicity and chemical ordering in compositionally complex materials

Diffusion involving atom transport from one location to another governs many important processes and behaviors such as precipitation and phase nucleation. The inherent chemical complexity in compositionally complex materials poses challenges for modeling atomic diffusion and the resulting formation of chemically ordered structures. Here, we introduce a neural network kinetics (NNK) scheme that predicts and simulates diffusion-induced chemical and structural evolution in complex concentrated chemical environments. The framework is grounded on efficient on-lattice structure and chemistry representation combined with artificial neural networks, enabling precise prediction of all path-dependent migration barriers and individual atom jumps. To demonstrate the method, we study the temperature-dependent local chemical ordering in a refractory NbMoTa alloy and reveal a critical temperature at which the B2 order reaches a maximum. The atomic jump randomness map exhibits the highest diffusion heterogeneity (multiplicity) in the vicinity of this characteristic temperature, which is closely related to chemical ordering and B2 structure formation. The scalable NNK framework provides a promising new avenue to exploring diffusion-related properties in the vast compositional space within which extraordinary properties are hidden.

36 MATERIALS SCIENCE↗