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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Distinct Surface and Bulk Thermal Behaviors of LiNi 0.6 Mn 0.2 Co 0.2 O 2 Cathode Materials as a Function of State of Charge

Understanding how structural and chemical transformations take place in particles under thermal conditions can inform designing thermally robust electrode materials. Such a study necessitates the use of diagnostic techniques that are capable of probing the transformations at multiple length scales and at different states of charge (SOC). In this study, the thermal behavior ofLiNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC-622) was examined as a function of SOC, using an array of bulk and surface-sensitive techniques. In general, thermal stability decreases as lithium content is lowered and conversion in the bulk to progressively reduced metal oxides (spinels, rock salt) occurs as the temperature is raised. Hard X-ray absorption spectroscopy (XAS) and X-ray Raman spectroscopy (XRS) experiments, which probe the bulk, reveal that Ni and Co are eventually reduced when partially delithiated samples (regardless of the SOC) are heated, although Mn is not. Surface-sensitive synchrotron techniques, such as soft XAS and transmission X-ray microscopy (TXM), however, reveal that for 50% delithiated samples, apparent oxidation of nickel occurs at particle surfaces under some circumstances. This is partially compensated by reduction of cobalt but may also be a consequence of redistribution of lithium ions upon heating. TXM results indicate the movement of reduced nickel ions into particle interiors or oxidized nickel ions to the surface or both. These experiments illustrate the complexity of the thermal behavior of NMC cathode materials. The study also informs the importance of investigating the surface and bulk difference as a function of SOC when studying the thermal behaviors of battery materials.

25 ENERGY STORAGE↗
DOE OSTI2024

Grain boundary solute segregation across the 5D space of crystallographic character

Solute segregation in materials with grain boundaries (GBs) has emerged as a popular method to thermodynamically stabilize nanocrystalline structures. However, the impact of varied GB crystallographic character on solute segregation has never been thoroughly examined. Here, this work examines Co solute segregation in a dataset of 7272 Al bicrystal GBs that span the 5D space of GB crystallographic character. Considerable attention is paid to verification of the calculations in the diverse and large set of GBs. In addition, the results of this work are favorably validated against similar bicrystal and polycrystal simulations. As with other work, we show that Co atoms exhibit strong segregation to sites in Al GBs and that segregation correlates strongly with GB energy and GB excess volume. Segregation varies smoothly in the 5D crystallographic space but has a complex landscape without an obvious functional form.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Ring Size Effects on the Structures of Sandwich Compounds with a Stoichiometry of C 12 H 12 M (M = Ti–Ni)

Ring size effects on geometries and electronic structures were investigated for the (C n H n )M(C m H m ) (n = 4, 5, or 6; m = 8, 7, or 6; m + n = 12; M = Ti–Ni) systems using density functional theory. The lowest-energy C 12 H 12 M structures for the early transition metals titanium, vanadium, and chromium are the experimentally known singlet (η 5 -C 5 H 5 )Ti(η 7 -C 7 H 7 ), doublet (η 5 -C 5 H 5 )V(η 7 -C 7 H 7 ), and singlet (η 6 -C 6 H 6 ) 2 Cr, respectively. The likewise experimentally known singlet (η 6 -C 6 H 6 ) 2 Ti, doublet (η 6 -C 6 H 6 ) 2 V, and singlet (η 5 -C 5 H 5 )Cr(η 7 -C 7 H 7 ) are the secondlowest- energy structures with only a small energy difference between the two vanadium structures. For the later transition metals, dibenzenemetal complexes are the lowest-energy C 12 H 12 M species with two fully bonded hexahapto benzene rings in the lowest-energy manganese and iron derivatives and one hexahapto and one dihapto benzene ring in the lowest-energy cobalt and nickel derivatives. The lowest-energy (C 5 H 5 )M(C 7 H 7 ) structures for the later transition metals iron, cobalt, and nickel have partially bonded nonplanar C 7 H 7 rings with one or two uncomplexed C=C bonds. The (C 4 H 4 )M(C 8 H 8 ) (M = Ti–Ni) structures with the metal sandwiched between four- and eight-membered rings were found to be much higher in energy than their (C 5 H 5 )M(C 7 H 7 ) and (C 6 H 6 ) 2 M isomers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Multivariate Bayesian Optimization of CoO Nanoparticles for CO 2 Hydrogenation Catalysis

The hydrogenation of CO 2 holds promise for transforming the production of renewable fuels and chemicals. However, the challenge lies in developing robust and selective catalysts for this process. Transition metal oxide catalysts, particularly cobalt oxide, have shown potential for CO 2 hydrogenation, with performance heavily reliant on crystal phase and morphology. Achieving precise control over these catalyst attributes through colloidal nanoparticle synthesis could pave the way for catalyst and process advancement. Yet, navigating the complexities of colloidal nanoparticle syntheses, governed by numerous input variables, poses a significant challenge in systematically controlling resultant catalyst features. We present a multivariate Bayesian optimization, coupled with a data-driven classifier, to map the synthetic design space for colloidal CoO nanoparticles and simultaneously optimize them for multiple catalytically relevant features within a target crystalline phase. The optimized experimental conditions yielded small, phase-pure rock salt CoO nanoparticles of uniform size and shape. These optimized nanoparticles were then supported on SiO 2 and assessed for thermocatalytic CO 2 hydrogenation against larger, polydisperse CoO nanoparticles on SiO 2 and a conventionally prepared catalyst. The optimized CoO/SiO 2 catalyst consistently exhibited higher activity and CH 4 selectivity (ca. 98%) across various pretreatment reduction temperatures as compared to the other catalysts. This remarkable performance was attributed to particle stability and consistent H* surface coverage, even after undergoing the highest temperature reduction, achieving a more stable catalytic species that resists sintering and carbon occlusion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Understanding Reaction Networks through Controlled Approach to Equilibrium Experiments Using Transient Methods

We report a combined experimental/theoretical approach to studying heterogeneous gas/solid catalytic processes using low-pressure pulse response experiments achieving a controlled approach to equilibrium that combined with quantum mechanics (QM)-based computational analysis provides information needed to reconstruct the role of the different surface reaction steps. We demonstrate this approach using model catalysts for ammonia synthesis/decomposition. Polycrystalline iron and cobalt are studied via low-pressure TAP (temporal analysis of products) pulse response, with the results interpreted through reaction free energies calculated using QM on Fe-BCC(110), Fe-BCC(111), and Co-FCC(111) facets. In TAP experiments, simultaneous pulsing of ammonia and deuterium creates a condition where the participation of reactants and products can be distinguished in both forward and reverse reaction steps. This establishes a balance between competitive reactions for D* surface species that is used to observe the influence of steps leading to nitrogen formation as the nitrogen product remains far from equilibrium. Here, the approach to equilibrium is further controlled by introducing delay timing between NH 3 and D 2 which allows time for surface reactions to evolve before being driven in the reverse direction from the gas phase. The resulting isotopic product distributions for NH 2 D, NHD 2 , and HD at different temperatures and delay times and NH 3 /D 2 pulsing order reveal the role of the N 2 formation barrier in controlling the surface concentration of NH x * species, as well as providing information on the surface lifetimes of key reaction intermediates. Conclusions derived for monometallic materials are used to interpret experimental results on a more complex and active CoFe bimetallic catalyst.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Thermodynamic and Kinetic Activity Descriptors for the Catalytic Hydrogenation of Ketones

Activity descriptors are a powerful tool for the design of catalysts than can efficiently utilize H 2 with minimal energy losses. In this study, we develop the use of hydricity and H - self-exchange rates as thermodynamic and kinetic descriptors for the hydrogenation of ketones by molecular catalysts. Two complexes with known hydricity, HRh(dmpe) 2 and HCo(dmpe) 2 , were investigated for the catalytic hydrogenation of ketones under mild conditions (1.5 atm, 25 °C). The rhodium catalyst proved to be an efficient catalyst for a wide range of ketones, whereas the cobalt catalyst could only hydrogenate electron-deficient ketones. Using a combination of experiment and electronic structure theory, thermodynamic hydricity values were established for 46 alkoxide/ketone pairs in both MeCN and THF solvent. Through comparison of the hydricities of the catalysts and substrates, it was determined that catalysis was only observed for catalyst/ketone pairs with an exergonic H - transfer step. Mechanistic studies revealed that H - transfer was rate-limiting step for catalysis, allowing for the experimental and computation construction of linear free-energy relationships (LFERs) for H - transfer. Further analysis revealed the LFERs could be reproduced using Marcus theory, in which the H - self-exchange rates for the HRh/Rh + and ketone/alkoxide pairs were used to predict the experimentally measured catalytic barriers within 2 kcal mol -1 . Finally, these studies significantly expand the scope of catalytic reactions that can be analyzed with a thermodynamic hydricity descriptor and firmly establish Marcus theory as a valid approach to develop kinetic descriptors for designing catalysts for H - transfer reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Ultrafast Jahn‐Teller Photoswitching in Cobalt Single‐Ion Magnets

Abstract Single‐ion magnets (SIMs) constitute the ultimate size limit in the quest for miniaturizing magnetic materials. Several bottlenecks currently hindering breakthroughs in quantum information and communication technologies could be alleviated by new generations of SIMs displaying multifunctionality. Here, ultrafast optical absorption spectroscopy and X‐ray emission spectroscopy are employed to track the photoinduced spin‐state switching of the prototypical complex [Co(terpy) 2 ] 2+ (terpy = 2,2′:6′,2″‐terpyridine) in solution phase. The combined measurements and their analysis supported by density functional theory (DFT), time‐dependent‐DFT (TD‐DFT) and multireference quantum chemistry calculations reveal that the complex undergoes a spin‐state transition from a tetragonally elongated doublet state to a tetragonally compressed quartet state on the femtosecond timescale, i.e., it sustains ultrafast Jahn‐Teller (JT) photoswitching between two different spin multiplicities. Adding new Co‐based complexes as possible contenders in the search for JT photoswitching SIMs will greatly widen the possibilities for implementing magnetic multifunctionality and eventually controlling ultrafast magnetization with optical photons.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Co(II) Substitution Enhances the Esterase Activity of a de Novo Designed Zn(II) Carbonic Anhydrase

Abstract Carbonic Anhydrases (CAs) have been a target forde novoprotein designers due to the simplicity of the active site and rapid rate of the reaction. The first reported mimic contained a Zn(II) bound to three histidine imidazole nitrogens and an exogenous water molecule, hence closely mimicking the native enzymes’ first coordination sphere. Co(II) has served as an alternative metal to interrogate CAs due to its d 7 electronic configuration for more detailed solution characterization. We present here the Co(II) substituted [Co(II)(H 2 O/OH − )] N (TRIL2WL23H) 3 n+ that behaves similarly to native Co(II) substituted human‐CAs. Like the Zn(II) analogue, the cobalt‐derivative at slightly basic pH is incapable of hydrolyzing p‐nitrophenylacetate (pNPA); however, as the pH is increased a significant activity develops, which at pH values above 10 eventually yields a catalytic efficiency that exceeds that of the [Zn(II)(OH − )] N (TRIL2WL23H) 3 + peptide complex. X‐ray absorption analysis is consistent with an octahedral species at pH 7.5 that converts to a 5‐coordinate species by pH 11. UV‐vis spectroscopy can monitor this transition, giving a pK a for the conversion of 10.3. We assign this conversion to the formation of a 5‐coordinate Co(II)(N imid ) 3 (OH)(H 2 O) species. The pH dependent kinetic analysis indicates the maximal rate (k cat ), and thus the catalytic efficiency (k cat /K m ), follow the same pH profile as the spectroscopic conversion to the pentacoordinate species. This correlation suggests that the chemically irreversible ester hydrolysis corresponds to the rate determining process.

Chemistry↗
DOE OSTI2023

Influence of aluminum incorporation and aqueous conditions on metal ion release of high-Ni transition metal oxide nanomaterials

Developing a materials perspective of how to control the degradation and negative impact of complex metal oxides requires an integrated understanding of how these nanomaterials transform in the environment and interact with biological systems. Doping with aluminum is known to stabilize oxide materials, but has not been assessed cohesively from synthesis to environmental fate and biological impact. In the present study, the influence of aluminum doping on metal ion release from transition metal oxides was investigated by comparing aqueous transformations of lithium nickel cobalt aluminum oxide (LiNi 0.82 Co 0.15 Al 0.03 O 2 ; NCA) and lithium nickel cobalt oxide (LiNi 0.80 Co 0.20 O 2 ; NC) nanoparticles and by calculating the energetics of metal release using a density functional theory (DFT) and thermodynamics method. Two model environmental organisms were used to assess biological impact, and metal ion release was compared for NCA and NC nanoparticles incubated in their respective growth media: moderately hard reconstituted water (MHRW) for the freshwater invertebrate Daphnia magna (D. magna) and minimal growth medium for the Gram-negative bacterium Shewanella oneidensis MR-1 (S. oneidensis). Further, the amount of metal ions released was reduced for NCA compared to NC in MHRW, which correlated to changes in the modeled energetics of release upon Al substitution in the lattice. In minimal medium, metal ion release was approximately an order of magnitude higher compared to MHRW and was similar to the stoichiometry of the bulk nanoparticles for both NCA and NC. Interpretation of the release profiles and modeling indicated that the increase in total metal ion release and the reduced influence of Al doping arises from lactate complexation of metal ions in solution. The relative biological impacts of NC and NCA exposure for both S. oneidensis and D. magna were consistent with the metal release trends observed for minimal medium and MHRW, respectively. Together, these results demonstrate how a combined experimental and computational approach provides valuable insight into the aqueous transformations and biological impacts of complex metal oxide nanoparticles.

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

Depth-dependent valence stratification driven by oxygen redox in lithium-rich layered oxide

Abstract Lithium-rich nickel-manganese-cobalt (LirNMC) layered material is a promising cathode for lithium-ion batteries thanks to its large energy density enabled by coexisting cation and anion redox activities. It however suffers from a voltage decay upon cycling, urging for an in-depth understanding of the particle-level structure and chemical complexity. In this work, we investigate the Li 1.2 Ni 0.13 Mn 0.54 Co 0.13 O 2 particles morphologically, compositionally, and chemically in three-dimensions. While the composition is generally uniform throughout the particle, the charging induces a strong depth dependency in transition metal valence. Such a valence stratification phenomenon is attributed to the nature of oxygen redox which is very likely mostly associated with Mn. The depth-dependent chemistry could be modulated by the particles’ core-multi-shell morphology, suggesting a structural-chemical interplay. These findings highlight the possibility of introducing a chemical gradient to address the oxygen-loss-induced voltage fade in LirNMC layered materials.

25 ENERGY STORAGE↗
DOE OSTI2020

3D Nanomagnetism in Low Density Interconnected Nanowire Networks

Free-standing, interconnected metallic nanowire networks with densities as low as 40 mg/cm 3 have been achieved over centimeter-scale areas, using electrodeposition into polycarbonate membranes that have been ion-tracked at multiple angles. Networks of interconnected magnetic nanowires further provide an exciting platform to explore 3-dimensional nanomagnetism, where their structure, topology, and frustration may be used as additional degrees of freedom to tailor the materials properties. New magnetization reversal mechanisms in cobalt networks are captured by the first-order reversal curve method, which demonstrate the evolution from strong demagnetizing dipolar interactions to intersection-mediated domain wall pinning and propagation, and eventually to shape-anisotropy dominated magnetization reversal. These findings open up new possibilities for 3-dimensional integrated magnetic devices for memory, complex computation, and neuromorphics.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Rational Design and Synthesis of Hierarchical Porous Mn–N–C Nanoparticles with Atomically Dispersed MnNx Moieties for Highly Efficient Oxygen Reduction Reaction

Developing transition-metal excluding iron and cobalt–nitrogen–carbon (M–N–C) electrocatalysts for the oxygen reduction reaction (ORR) is critical to substantially promote the development of precious-metal-free metal–air batteries and fuel cells. In the work, Mn–N–C nanoparticles with atomically dispersed MnNx moieties were synthesized by pyrolyzing Mn-ion–dual-pyridine coordinated complex, which was obtained via a simple condensation reaction between 2,6-diamino-pyridine and 2,6-diacetyl-pyridine with MnCl 2 as the Mn source. The precursor features with a characteristic structure of dual-pyridine ligand, which possesses a strong coordinating capability for Mn 2+ , facilitating the formation of highly dispersed nitrogen-coordinated Mn sites (MnN x ). Attributed to the highly active atomic MnN x sites, hierarchical pore structure, and high surface area of the Mn–N–C derived from the new precursor, it exhibits outstanding ORR performance in 0.1 M KOH with an almost direct four-electron reaction path and high selectivity of O 2 into H 2 O (low H2O2 production <3.5%). The half-wave potential of Mn–N–C is 0.88 V vs RHE, which is 20 mV higher than that of commercial Pt/C catalyst and reaches to the level of Fe–N–C catalyst obtained by the same method. Meanwhile, the feasibility of Mn–N–C for practical application is validated by its higher-performance power output in Zn–air battery with a maximum power density of 132 mW cm –2 compared to that of Pt/C (121 mW cm –2 ) using the same catalyst loading of 1.0 mg cm –2 . This work develops a convenient route to develop non-Fe or Co–N–C electrocatalyst for the ORR.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Cobalt-Catalyzed Hydrogenation Reactions Enabled by Ligand-Based Storage of Dihydrogen

The use of supporting ligands that can store either protons or electrons has emerged as a powerful strategy in catalysis. While these strategies are potent individually, natural systems mediate remarkable transformations by combining the storage of both protons and electrons in the secondary coordination sphere. As such, there has been recent interest in using this strategy to enable fundamentally different transformations. Furthermore, outsourcing H-atom or hydrogen storage to ancillary ligands can also enable alternative mechanistic pathways and thereby selectivity. Here, we describe the application of this strategy to facilitate radical reactivity in Co-based hydrogenation catalysis. Metalation of previously reported dihydrazonopyrrole ligands with Co results in paramagnetic complexes, which are best described as having Co(II) oxidation states. These complexes catalytically hydrogenate olefins with low catalyst loadings under mild conditions (1 atm H 2 , 23 °C). Mechanistic, spectroscopic, and computational investigations indicate that this system goes through a radical hydrogen-atom transfer (HAT) type pathway that is distinct from classic organometallic mechanisms and is supported by the ability of the ligand to store H 2 . These results show how ancillary ligands can facilitate efficient catalysis, and furthermore how classic organometallic mechanisms for catalysis can be altered by the secondary coordination sphere.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

In Situ Synthesized Homochiral Spiroborate Ester Metal–Organic Framework with Mono–, Di–, and Trivalent Cations

Here we report here a one–step method for synthesizing multi–component and in–situ–formed homochiral spiroborate–ester–based metal–organic framework CPM–B1. This unique material successfully integrates COF fragment spiroborate ester within the MOF and simultaneously incorporate homochirality and helicity. In addition, CPM–B1 is a rare example of framework materials that results from the cooperative assembly of three charge–complementary cations: +1 (lithium), +2 (cobalt), and +3 (boron). The sophistication of the co–assembly is further highlighted by the three structural roles of lithium ions. This unique structure contributes to its multi–functional properties such as ionic conductivity and catalytic activity for oxygen reduction reaction (by CPM–B1 carbonized material) and provides a new path to develop MOF materials with complex secondary building units and multi–functional applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Viability of Additively Manufactured Electrodes for Lithium-Ion Batteries

As the global economy becomes increasingly electrified, the demand for batteries and energy storage is expected to rise significantly, particularly in the transportation and electricity sectors. Lithium-ion batteries (LIBs) are currently the most advanced and widely used technology in this field. Traditionally, LIBs are manufactured using simple 2D planar geometries to maximize production efficiency and minimize costs. However, this approach limits energy density due to the restricted design flexibility of the electrodes. Additive manufacturing (AM) offers a promising solution to enhance the energy density and efficiency of LIBs by enabling the design of architectures that reduce diffusive losses and allow for a greater amount of active material to be incorporated within the same device footprint, thereby minimizing the use of inactive materials. Different AM techniques come with their own set of limitations, including printing speed, material compatibility, and scale, which must be considered when designing electrodes. Scalable and cost-effective methods are particularly important for electric vehicle batteries, while achieving higher energy densities in microbatteries is crucial for the miniaturization of wearable electronics and medical devices. Here, in this study, we simulate various 3D porous electrode designs for LIBs using graphite and nickel manganese cobalt oxide (NMC) electrodes. These designs are selected to represent structures that could be produced using different AM techniques, such as direct ink writing, fused deposition modeling, and stereolithography. Our results indicate that at higher charging rates and increased areal mass loading, 3D structures can outperform traditional 2D electrodes, although the benefits may diminish with more complex designs that are harder to manufacture. The observed gains in energy density are attributed to improved electrode utilization and reduced diffusive energy losses. This comprehensive analysis of structure–performance relationships will provide valuable insights to guide future research on 3D designs, material selection, and AM techniques for additively manufactured battery electrodes.

25 ENERGY STORAGE↗
DOE OSTI2023

Synthesis, structure and canted antiferromagnetism of layered cobalt hydroxide sorbate

Layered hybrid organic–inorganic compounds of the transition metal hydroxides, in which part of the hydroxide ions are exchanged for organic ligands that act as spacers of the 2-dimensional inorganic layers, elicit new or enhanced properties. The interlayer ligands enable fine-tuning of the physicochemical properties of the metal hydroxide layers, including their magnetism. Specifically, within the Co(OH) 2 family of transition ion hydroxides, this approach has been leveraged to stabilize antiferromagnetic and ferrimagnetic ground states for pillared and layered complexes, respectively. Here, in this work, we further investigate the effects of changing dimensionality, local Co coordination, and interlayer spacing on the magnetic ground state of brucite-like β-Co(OH) layered complexes. We report the hydrothermal synthesis of a new crystalline material, Co(OH)(sorb), where the inorganic layers are spaced by monotopic, doubly unsaturated sorbate ligands (sorb = [C 6 H 7 O 2 ] – ). The material was structurally characterized using powder X-ray and neutron diffraction measurements and the crystal structure was solved ab initio from powder diffraction data and refined using the Rietveld method. The magnetic susceptibility and magnetization measurements reveal canted antiferromagnetic ordering with T N = 41.7 K. This report augments our understanding of tuning magnetism through dimensionality in layered complexes and represents a step forward in the design of new 2D layered hybrid compounds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Stability Analysis of Substituted Cobaltocenium [Bis(cyclopentadienyl)cobalt(III)] Employing Chemistry-Informed Neural Networks

Cobaltocenium derivatives are promising components of the anion exchange membranes due to their excellent thermal and alkaline stability under the operating conditions of a fuel cell. Here we present an efficient modeling approach of assessing the chemical stability of substituted cobaltocenium CoCp 2 + based on the computed electronic structure enhanced by machine learning techniques. Within the aqueous environment, the positive charge of the metal cation is balanced by the hydroxide anion through formation of the CoCp 2 + OH¯ complexes, whose dissociation is studied within the implicit solvent employing density functional theory. The data set of about 118 species based on 42 substituent groups characterized by a range of electron- donating (ED) and electron-withdrawing (EW) properties is constructed and analyzed. Given 12 carefully chosen chemistry-informed descriptors of the complexes and relevant fragments, the stability of the complexes is found to strongly correlate with the energies of the highest occupied and lowest unoccupied molecular orbitals, modulated by a switching function of the Hirshfeld charge. The latter is used as a measure of the electron withdrawing-donating character of the substituents. Based on this observation from the conventional regression analysis, two fully connected, feed-forward neural network (FNN) models with different unit structures, called the chemistry-informed (CINN) and the quadratic (QNN) neural networks, are developed. Both models predict the bond dissociation energies of the cobaltocenium complexes with mean relative errors less than 5.40% and average absolute errors less than 0.94 kcal/mol. The results show the potential of QNN to efficiently capture more complex relationships. Here, the concept of incorporating the domain (chemical) knowledge/insight into the neural network structure paves the way to applications of machine learning techniques with small data sets, ultimately leading to better predictive models compared to the conventional regression analysis.

36 MATERIALS SCIENCE↗