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At least 397 records · Page 22

Origins of anisotropic transport in the electrically switchable antiferromagnet Fe 1/3 NbS 2

Recent experiments on the antiferromagnetic intercalated transition metal dichalcogenide Fe 1/3 NbS 2 have demonstrated reversible resistivity switching by application of orthogonal current pulses below its magnetic ordering temperature, making Fe 1/3 NbS 2 promising for spintronics applications. Here, we perform density functional theory calculations with Hubbard U corrections of the magnetic order, electronic structure, and transport properties of crystalline Fe 1/3 NbS 2 , clarifying the origin of the different resistance states. The two experimentally proposed antiferromagnetic ground states, corresponding to in-plane stripe and zigzag ordering, are computed to be nearly degenerate. In-plane cross sections of the calculated Fermi surfaces are anisotropic for both magnetic orderings, with the degree of anisotropy sensitive to the Hubbard U value. The in-plane resistance, computed within the Kubo linear response formalism using a constant relaxation time approximation, is also anisotropic, supporting a hypothesis that the current-induced resistance changes are due to a repopulating of antiferromagnetic domains. Our calculations indicate that the transport anisotropy of Fe 1/3 NbS 2 in the zigzag phase is reduced relative to stripe, consistent with the relative magnitudes of resistivity changes in experiment. Finally, our calculations reveal the likely directionality of the current-domain response, specifically, which domains are energetically stabilized for a given current direction.

36 MATERIALS SCIENCE↗

Investigating Combinations of Alkali Metal Oxides and Hydrogenation Catalysts for Reactive Capture of CO2 to Useful C1 Products

As the world endures environmental crises associated with climate change and the rise of atmospheric CO2 concentrations from anthropogenic CO2 emission, carbon capture and utilization (CCU) technologies are increasingly necessary. Reactive carbon capture (RCC) technologies, in which capture and conversion of CO2 occur in a single reactor, are more energetically and economically attractive by avoiding the need to purify, compress, and transport the captured CO2. To this end, dual function materials (DFMs) - composed of sorbents and catalysts co-dispersed on the same high surface area carrier - have been developed. The sorbent component allows for selective capture of CO2 from a gas stream and the catalyst component subsequently performs the in-situ conversion of the adsorbed CO2 upon introduction of a reactive gas (typically H2). The end product of the most established DFM, comprised of Ru and/or Ni with an alkaline sorbent, is methane via the CO2 methanation reaction. While renewable methane would be an excellent transition fuel, fossil methane is inexpensive (averaging $2.57/MMBTU in pre-pandemic 2019) and the economics of renewable methane utilization are noncompetitive. This requires the design and investigation of DFMs that enable CO2 capture and conversion to more valuable and more useful C1 products like CO or methanol (average price of methanol was $20.61/MMBTU in pre-pandemic 2019). These products can then be further upgraded to high energy density synthetic fuels, and related carbonaceous products, for more sustainable alternatives in industries that are difficult to decarbonize, specifically heavy duty vehicles and aviation. Herein, we report various sorbent + catalyst combinations to achieve the production of useful C1 products through reactive capture of CO2.

carbon capture↗

Plastic Parallel Pathways Platform- 4P Model

The U.S. generates 42 million metric tons of plastic waste each year - the most of any country - of which less than 9% is recycled. This represents an estimated loss of $2.3 billion and 3.4 EJ embodied energy per year. Plastic use reduction, reuse and recycling are thus increasingly important, but making informed policy and research decisions within this space can be challenging given the diverse range of available solutions. Various recycling and waste management options are available for plastics, such as conversion into energy (incineration, pyrolysis, gasification), conversion to lower- or higher-grade plastics (mechanical recycling, chemical or enzymatic depolymerization processes, dissolution) or up-cycling to feedstock chemicals (photo/electro/catalytic methods, pyrolysis, gasification). While many previous publications have investigated a subset of these options, there is currently no modelling platform that can quantitatively assess and compare the economic and environmental impacts of all these different plastic management pathways and their respective products simultaneously. To directly compare the benefits and disadvantages of plastic-to-x technologies, we propose a novel analysis framework: the Plastic Parallel Pathways Platform (4P). 4P will model a systems analysis framework for capturing plastic material flows processed via different waste management scenarios. The total economic cost and greenhouse gas emissions (as well as additional economic, energetic, and environmental metrics indicators) of a given scenario will be calculated enabling comparison to other scenarios, thereby informing decisions on plastic recycling pathways.

circular economy↗

Influence of Surface Ligands on Energetics at FASnI 3 /C 60 Interfaces and Their Impact on Photovoltaic Performance

Interfacial chemistry and energetics significantly impact the performance of photovoltaic devices. In the case of Pb-containing organic metal halide perovskites, photoelectron spectroscopy has been used to determine the energetic alignment of frontier electronic energy levels at various interfaces present in the photovoltaic device. For the Sn-containing analogues, which are less toxic, no such measurements have been made. Through a combination of ultraviolet, inverse, and X-ray photoelectron spectroscopy (UPS, IPES, and XPS, respectively) measurements taken at varying thickness increments during stepwise deposition of C 60 on FASnI 3 , we present the first direct measurements of the frontier electronic energy levels across the FASnI 3 /C 60 interface. The results show band bending in both materials and transport gap widening in FASnI 3 at the interface with C 60 . The XPS results show that iodide diffuses into C 60 and results in n-doping of C 60 . This iodide diffusion out of FASnI 3 impacts the valence and conduction band energies of FASnI 3 more than the core levels, with the core level shifts displaying a different trend than the valence and conduction bands. Surface treatment of FASnI 3 with carboxylic acids and bulky ammonium substituted surface ligands results in slight alterations in the interfacial energetics, and all surface ligands result in similar or improved PV performance relative to the untreated devices. Finally, the greatest PV stability results from treatment with a fluorinated carboxylic acid derivative; however, iodide diffusion is still observed to occur with this surface ligand.

interfacial energetics↗

Exploring the Effects of Node Topology, Connectivity, and Metal Identity on the Binding of Nerve Agents and Their Hydrolysis Products in Metal–Organic Frameworks

Recent studies have shown that metal–organic frameworks (MOFs) built from hexanuclear M(IV) oxide cluster nodes are effective catalysts for nerve agent hydrolysis, where the properties of the active sites on the nodes can strongly influence the reaction energetics. The connectivity and metal identity of these M6 nodes can be easily tuned, offering extensive opportunities for computational screening to predict promising new materials. Thus, we used density functional theory (DFT) to examine the effects of node topology, connectivity, and metal identity on the binding energies of multiple nerve agents and their corresponding hydrolysis products. By computing an optimization metric based on the relative binding strengths of key hydrolysis reaction species (water, agent, and bidentate-bound products), we predicted optimal M6 nodes for hydrolyzing specific nerve agent and simulant molecules, where our results are in qualitative agreement with observed experimental trends. This analysis highlighted the notion that no single metal or node topology is optimal for all possible organophosphates, suggesting that MOFs should be selected based on the agent of interest. Using the large amount of data generated from our DFT calculations, we then derived quantitative structure–activity relationship (QSAR) models to help explain the complex trends observed in the binding energies. Through linear regression, we identified the most important descriptors for describing the binding of nerve agents and their hydrolysis products to M6 nodes. These results suggested that both molecular and node properties, including both structural and chemical features, collectively contribute to the binding energetics. By performing a thorough statistical analysis, we showed that our QSAR models are capable of making quantitatively accurate binding energy predictions for nerve agents and their hydrolysis products in a wide variety of M(IV)-MOFs. In conclusion, the insights gained herein can be used to guide future experiments for the synthesis of MOFs with enhanced catalytic activity for organophosphate hydrolysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Discovery of spontaneous de-interpenetration through charged point-point repulsions

Entanglement is an energetically favorable occurrence, pervasive in both nature and synthetic systems, where networks prefer to entwine with one another rather than remain open and accessible. As a result of entanglement, valuable internal pore space, useful for applications such as catalysis, storage, and sensing, is lost. Here, we detail our discovery of a phenomenon termed “charged point-point repulsion,” which energetically favors dis-entanglement, transforming a densely packed uranium-based framework with 14.2 and 19.8 Å pores into an open material with 40.7 Å pores and record-high void fraction and pore volume. We anticipate that the phenomenon described in this work could be widely generalized for the direct and systematic production of non-entangled structures with an abundance of valuable pore space and far-reaching practical importance. More fundamentally, this study compels a re-evaluation of the thermodynamics of porosity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Characterization of the fatigue threshold behavior of UHMWPE

Ultra-high-molecular-weight-polyethylene (UHMWPE) has been the material of choice for bearings in total joint replacements (TJRs) for decades as a result of its excellent wear resistance, chemical inertness, energetic toughness, low friction, and biocompatibility. Utilization of this polymer in orthopedic devices requires oxidation, wear, and fatigue resistance. Balancing these important properties by tailoring processing techniques and modulating microstructural features has been an ongoing endeavor in the field. Research into the clinical applications of UHMWPE has primarily focused on the challenges of wear and oxidation while studies into the realm of fatigue have been more limited. Literature gaps exist in fully understanding the fatigue crack initiation near notches or propagation of small existing flaws in UHMWPE used in TJRs. In particular, the characterization of the fatigue thresholds and near-threshold fatigue behavior of orthopedic grade UHMWPE has yet to be thoroughly explored. In this work, we characterized the fatigue crack arrest threshold of clinically-relevant UHMWPE formulations. Correlations between the fatigue thresholds and bulk mechanical properties as well as microstructural properties were examined across these medical resins. The important role played by crosslinking in influencing the fatigue performance of UHMWPE is highlighted in this study. In addition, it is established that J-integral fracture toughness is the best predictor of fatigue thresholds and could possibly be used as a stand-in metric for fatigue performance if thresholds cannot be directly ascertained. Finally, this study corroborates that the true constitutive parameters best describe the mechanical behavior of UHMWPE.

Cross-linking↗

Doping of Cr in Graphene Using Electron Beam Manipulation for Functional Defect Engineering

Chromium atoms in graphene have been proposed to exhibit magnetic moments and spin-selective conducting states depending on the local bonding geometry within the graphene structure, which could lead to interesting applications in spintronics. Despite this interest, there are few direct experimental reports of Cr dopants in graphene even though it is theorized to be stable. Here, we demonstrate the introduction of single Cr dopant atoms into the graphene lattice and onto graphene edges through the controlled use of a focused electron beam in a scanning transmission electron microscope. Here, we show local control of doping locations, and when coupled with targeted in situ milling during scanning of the e-beam, these strategies demonstrate an important component of the fabrication of tailored nanostructured devices in the electron microscope. The approach is validated with first-principles calculations to understand synthesis pathways during fabrication and reveal the energetics and local properties of Cr atoms embedded in graphene; for example, Cr doping can convert graphene into a magnetic and semiconducting material, which suggests Cr-doped graphene can be used as a building block for potential electronic devices and a means to construct them.

36 MATERIALS SCIENCE↗

Unraveling two distinct polymorph transition mechanisms in one n-type single crystal for dynamic electronics

Cooperativity is used by living systems to circumvent energetic and entropic barriers to yield highly efficient molecular processes. Cooperative structural transitions involve the concerted displacement of molecules in a crystalline material, as opposed to typical molecule-by-molecule nucleation and growth mechanisms which often break single crystallinity. Cooperative transitions have acquired much attention for low transition barriers, ultrafast kinetics, and structural reversibility. However, cooperative transitions are rare in molecular crystals and their origin is poorly understood. Crystals of 2-dimensional quinoidal terthiophene (2DQTT-o-B), a high-performance n-type organic semiconductor, demonstrate two distinct thermally activated phase transitions following these mechanisms. Here we show reorientation of the alkyl side chains triggers cooperative behavior, tilting the molecules like dominos. Whereas, nucleation and growth transition is coincident with increasing alkyl chain disorder and driven by forming a biradical state. We establish alkyl chain engineering as integral to rationally controlling these polymorphic behaviors for novel electronic applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Polarons are probes of the dynamic nanoscale environments found in electrochemically doped π-conjugated polymers

Charge carriers (i.e., polarons) in electrochemically doped organic (semi)conductors are proposed to be regulated by several physicochemical features, including the chemical compositions and structures of the π-conjugated frameworks of the semiconductor building blocks, the chemistry of the electrolyte (considering both the salt and solvent), multiscale and time-dependent morphology variations across the material as a function of electrochemical processes, and assorted permutations of these and other factors. To address these hypotheses, we investigate the energetic, optoelectronic, chemical, and local structural properties of negative polarons (radical anions) as a function of electrochemical doping in the donor–acceptor, π-conjugated redox copolymer P(NDI2OD-T2), also referred to as N2200. A critical finding is that there is not just “one type” of polaron in electrochemically doped P(NDI2OD-T2). Rather, an ensemble of polarons exists, with the polarons having optoelectronic signatures that are defined by their nanoscale environments. Importantly, the polaron optical signatures serve as local probes for how the operando electrochemical environments are dynamically working in concert to facilitate charge transport. Collectively, the distinctive and extensive integration of theory and measurement science presented here establishes a baseline for the roles that semiconductor and electrolyte chemistries and dynamic structural features have on polarons in electrochemically doped organic semiconductors and how these factors influence the energetics and rates of polaron transport.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Finite-size correction for slab supercell calculations of materials with spontaneous polarization

Abstract The repeated slab approach has become a de facto standard to accurately describe surface properties of materials by density functional theory calculations with periodic boundary conditions. For materials exhibiting spontaneous polarization, we show that the conventional scheme of passivation with pseudo hydrogen is unable to realize a charge-neutral surface. The presence of a net surface charge induces via Gauss’s law a macroscopic electric field through the slab and results in poor size convergence with respect to the thickness of the slab. We propose a modified passivation method that accounts for the effect of spontaneous polarization, describes the correct bulk limits and boosts convergence with respect to slab thickness. The robustness, reliability, and superior convergence of energetics and electronic structure achieved by the proposed method are demonstrated using the example of polar ZnO surfaces.

Chemistry↗

Sulfur-enhanced dynamics of coinage metal(111) surfaces: Step edges versus terraces as locations for metal-sulfur complex formation

The propensity of trace amounts of sulfur adsorbed on coinage metal(111) surfaces to dramatically enhance surface dynamics has been demonstrated by STM observations of accelerated 2D island decay for Cu and Ag. It is generally accepted that this enhancement is due to the formation of adsorbed metal-sulfur complexes, which facilitate surface mass transport of the metal. These complexes were originally proposed to form on terraces following the extraction of metal atoms from step edges and subsequent combination with sulfur on the terraces. However, even when thermodynamically feasible, this mechanism may not be kinetically viable for some complexes due to limited coupling of the complex concentration to the surface diffusion flux of metal atoms. Focusing on the case of Cu, we assess various scenarios where complexes are formed either on terraces or instead directly at step edges, the latter being a new paradigm. In this work, a new pathway is proposed for the formation on terraces. A rich variety of structures incorporating S at step edges exist, which could provide a viable source for complexes, at least from a thermodynamic perspective. However, it is necessary to also assess the activation barrier for complex formation and detachment from step edges. This is facilitated by the nudged-elastic-band analysis of the minimum energy path for this process utilizing machine-learning derived potentials based on density functional theory energetics for the metal-sulfur system.

36 MATERIALS SCIENCE↗

Electronic Structure Calculations for Improving Catalyst Design for Use in the Hybrid Sulfur Cycle

The hybrid sulfur cycle is a promising means for efficient production of large quantities of hydrogen with a small carbon footprint. However, many challenges remain in designing catalysts that are stable at high temperatures and have high sulfur tolerance. Theoretical calculations can provide fundamental insights at the electronic scale to improve our understanding of reaction mechanisms and surface energetics, thereby facilitating improved catalyst design. Here, density functional theory was used to explore the reaction energetics of the hybrid sulfur cycle on Pt, Au, and Pt - Au surfaces. A database of information has been built that contains calculations from which adsorption energetics and density of states information can be extracted.

36 MATERIALS SCIENCE↗

Smart culture medium optimization for recombinant protein production: Experimental, modeling, and AI/ML-driven strategies

Recombinant protein production (RPP) is central to biotechnology, where recombinant proteins are used as either end products or catalysts in the synthesis of chemicals, fuels, and materials. Among the major cost drivers, culture medium plays a pivotal role in determining protein yield and quality. This review presents a comprehensive perspective on the critical stages of “smart” culture medium optimization: planning, screening, modeling, optimization, and validation. In the planning stage, we examine the nutritional and energetic roles of medium components, including carbon, nitrogen, amino acids, salts, and trace metals, and their impacts on culture parameters such as pH, oxidative state, and osmolality. We highlight the variability in trace metal content due to water sources, culture vessels, and raw materials, which can substantially influence RPP. The screening stage covers Design of Experiments (DoE) approaches, assessing their theoretical basis, implementation, and limitations. For modeling, we describe methods that integrate experimental data to develop predictive models for smart medium formulation. Model-based optimization strategies can then be employed to select optimal media compositions for a given application. The validation stage aims to evaluate model predictions and provide feedback for model training and refinement. Finally, we survey mechanistic and artificial intelligence/machine learning (AI/ML)-driven models as integrated, transformational tools for predictive modeling of bioprocess conditions, nutrient availability, cellular metabolism, and protein quality, with the goal of optimizing culture media to enhance protein yields while reducing costs and environmental impact. We conclude by addressing the challenges of translating laboratory-scale medium optimization to industrial-scale settings and exploring future AI/ML-driven approaches that may overcome current bottlenecks and accelerate medium design for RPP. Overall, this review provides a unified framework for advancing smart medium design in RPP.

Artificial Intelligence/Machine Learning (AI/ML)↗

Realignment and suppression of charge density waves in the rare-earth tritellurides 𝑅⁢Te 3 (𝑅 = La, Gd, Er)

The rare-earth tritellurides have a rich phase diagram that includes charge density waves (CDWs), superconductivity, and magnetic order, offering a platform to study the interplay between these phases on a square-net system. Prior studies have shown that defects can affect the CDW characteristics in these materials, yet coupling between the CDW order and the underlying microstructure has not been studied at the nanoscale. Here we use scanning transmission electron microscopy at cryogenic temperatures to directly visualize the effects of defects on the CDW order and provide a spatially resolved microscopic correlation between the CDW transition and structural defects. Here, we show that in the presence of extended defects, such as dislocations and stacking faults, the weak orthorhombicity of the rare-earth tritellurides is lost and the material becomes pseudotetragonal. Since the orthorhombicity acts as a symmetry breaking field for the CDW transitions in rare-earth tritellurides, the presence of these extended defects modulates the energetics of the CDWs and suppresses the ground-state CDW phase at low temperature.

Charge density waves↗

Analysis and prediction of reaction kinetics using the degree of rate control

“Degree of rate control” (DRC) analysis provides a quantitative approach for analysing the kinetics of multi-step reaction mechanisms that has been widely applied to both heterogeneous and homogeneous catalysis research, as well as electrocatalysis. The DRC of any given transition state or intermediate is defined as a partial derivative such that it approximately equals the fractional increase in net rate to the product of interest per differential decrease in its standard-state free energy for that species (÷RT), holding constant the standard-state free energies of all other transition states and intermediates. Even very complex mechanisms usually have only a few species with non-zero DRCs and are thus the species whose interactions with the catalyst most strongly affect the net rate. These key DRC values thus offer a simple and intuitive route to optimize catalyst materials, especially with the assistance of computational methods like density functional theory (DFT). These high-DRC species are also the species whose energetics must be most accurately measured or calculated to achieve an accurate kinetic model for any reaction mechanism. In simple cases with a single “rate-determining step”, the DRC for its transition state (TS) is + 1. Catalyst-bound intermediates, on the other hand, often have negative DRCs equal to a small integer times their fractional occupancy of catalyst sites. The apparent activation energy equals a weighted average of the standard-state enthalpies (relative to reactants) of all the species (intermediates, transition states and products) in the reaction mechanism, each weighted by its DRC (+RT). It has been shown that the apparent transfer coefficient in electrocatalysis, an inverted form of the Tafel slope, is a weighted average of the number of electrons transferred to generate each intermediate or product species in the mechanism, weighted again by the DRC. Quantitative analysis of kinetic isotope effects (KIEs, or the ratio of net rates for different reactant isotopes) in complex mechanisms has shown that the logarithm of the KIE equals the weighted average over all species in the mechanism of the difference between the two isotopes in their standard-state free energies (÷RT), again weighted by the DRC. The reaction orders with respect to fluid-phase concentrations of reactants, products and intermediates have also been proven to be directly related to DRCs. Thus, there are numerous experimental observables which equate to short linear combinations of DRCs, so that combinations of experimental measurements might provide access to DRC values. Since its invention for transition states in 1994 and its generalization to include intermediates in 2009, the DRC has thus far mainly been calculated for microkinetic models based either entirely on DFT or on DFT with the key energies (i.e., those for high-DRC species) being fine-tuned to match experiments. The relationships summarized in this work provide new opportunities for using experiments earlier in the development and optimization of microkinetic models that require input from computational catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Stability-limiting heterointerfaces of perovskite photovoltaics

Optoelectronic devices consist of heterointerfaces formed between dissimilar semiconducting materials. The relative energy level alignment between contacting semiconductors determinately affects the heterointerface charge injection and extraction dynamics. For perovskite solar cells (PSCs), the heterointerface between the top perovskite surface and a charge-transporting material (CTM) is often treated for defect passivation to improve PSC stability and performance. However, such surface treatments could also affect the heterointerface energetics. Here we show that surface treatments may induce a negative work function shift (i.e. more n-type), which activates halide migration to aggravate PSC instability. Therefore, despite the beneficial effects of surface passivation, this detrimental side effect limits the maximum stability improvement attainable for PSCs treated in these ways. Furthermore, this trade-off between the beneficial and detrimental effects should guide further work on improving PSC stability via surface treatments.

14 SOLAR ENERGY↗