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At least 1,225 records · Page 68

Significance of the structural configuration of B2 disorder in Co and Ti based Heusler alloys

We investigate here structural (at local and global levels) and transport properties for 𝑋 2 ⁢MnAl (𝑋= Co and Ti). Additionally, the magnetic properties were also studied for Ti 2 ⁢MnAl. Our x-ray diffraction results show that both the compounds stabilize in B2 disordered phase with cubic structure of 𝑃⁢𝑚⁢$\overline{3}$⁢𝑚 space group. Further, the structural configuration of the above disordered phase for both the compounds was identified using combined studies of x-ray absorption spectroscopy and multiple scattering calculations at the transition metal 𝐾 edges. Upon such identification, in the case of Co 2 ⁢Mn 1−𝑦⁢ Cr 𝑦 ⁢Al (𝑦= 0, 0.05, 0.1, 0.2) with change in 𝑦, we are able to establish a better connection quantitatively between the inverse of Mn-Co bonds and peak in the temperature-dependent resistivity. This highlights the crucial importance of a detailed understanding of the nature of B2 disorder. In the case of 𝑦=0, in the temperature range of study, the resistivity is driven by the functional form associated with (a) three-dimensional enhanced electron-electron Coulomb interaction scattering mechanism and (b) an unconventional one-magnon process. For Ti 2 ⁢MnAl, the transport shows metallic glasslike behavior at high temperature, while at low temperature it follows both the Cote-Meisel's model and quantum correction model. In this compound, the magnetic studies suggest the formation of superparamagnetic clusters in the paramagnetic matrix at low temperatures. Our density functional theory results are in line with the transport and magnetic properties. In literature, the spin polarization percentage (𝑃) for 𝑋= Co in B2 disordered phase is 76%. However, the present results emphasize the fact that in B2 disordered phase, the value of 𝑃 can range from 90% to 71% depending on the structural configuration introduced by swapping of the atomic positions of Mn and Al. For the compound under study, the value of percentage spin polarization obtained ranges between 82% to 85%. In addition, we also identify the origin of the difference in the shape of the Mn 3⁢𝑑 density of states for both the alloys. In conclusion, our results for 𝑋= Co alloy highlights the importance of identifying the specific structural configuration associated with a particular disorder category especially in the estimation of 𝑇 𝑐 and 𝑃 and for 𝑋= Ti, the physical properties can be tuned by varying the position of 𝐸 𝐹 and thereby its utilization in device applications.

36 MATERIALS SCIENCE↗

Critical structural parameter determining magnetic phases in the F⁡e 2 ⁢M⁢o 3 ⁢O 8 altermagnet system

A systematic structural investigation of F⁡e 2 ⁢M⁢o 3⁢ O 8 as a function of pressure, temperature, and magnetic field reveals that the 𝑃⁢6 3 ⁢𝑚⁢𝑐 space group remains robust over a wide range of conditions. No changes in the long-range crystal structure are observed for pressures up to 10 GPa, temperatures between 11 K and 300 K, and magnetic fields up to 9 T. The magnetostructural response, quantified by Δ⁢𝑐/𝑐, is determined for magnetic fields applied transverse to the crystallographic 𝑐 axis, demonstrating strong magnetoelastic coupling. The well-known magnetic-field-induced transition is confirmed to be first order and isostructural, occurring between two distinct altermagnetic states. Importantly, this transition can also be accessed using magnetic fields applied within the 𝑎𝑏 plane. When expressed in terms of the 𝑐/𝑎 ratio, the structural evolution under pressure (0–10 GPa) maps continuously onto that observed across the full Zn substitution range in (F⁡e 1−𝑦⁢ Z⁢n 𝑦 )2 M⁢o 3 ⁢O 8 ⁢(0 ≤ 𝑦 ≤ 1), indicating a common underlying structural control parameter. Furthermore, these results demonstrate that the 𝑐-axis lattice parameter is the primary structural degree of freedom governing magnetic behavior under external tuning parameters. More broadly, they indicate that magnetic order in this family of complex oxides (𝐴 2 ⁢M⁢o 3 ⁢O 8 , 𝐴 = Co,Mn,Ni) can be systematically tuned via pressure. This tunability highlights these materials as promising platforms for controllable magnetic switching, particularly in thin films integrated with piezoelectric substrates.

36 MATERIALS SCIENCE↗

Ferromagnetism and structural phase transition in rhombohedral PrI r 3

The synthesis, structural, magnetic, thermal, and transport properties are reported for polycrystalline PrI⁢r 3 . At room temperature PrI⁢r 3 displays the rhombohedral space group R–3m and a PuNi 3 -type structure. At around 70 K a phase transition to a monoclinic C⁢2/m structure is observed and continued cooling reveals temperature independent behavior of the unit cell volume. Further, PrI⁢r 3 undergoes a paramagnetic to ferromagnetic transition with T c =7.5K. The temperature dependent magnetic susceptibility follows the Curie-Weiss law with a positive Curie-Weiss temperature, and an effective moment that is close to the theoretical effective moment for a free P⁢r +3 ion. Finally, the structural transition introduces further complexity into the behavior of PuNi 3 -type materials and highlights the importance of temperature-dependent structural studies to complement physical property measurements in intermetallic compounds.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Tuning the structure and superconductivity of SrNi 2⁢ P 2 by Rh substitution

The compound SrNi 2⁢ P 2 is unique among the ThCr 2 ⁢Si 2 class since it exhibits a temperature-induced transition upon cooling from an uncollapsed tetragonal (ucT) state to a one-third-collapsed orthorhombic (tcO) state where one out of every three P-rows bond across the Sr layers. This compound is also known for exhibiting bulk superconductivity below 1.4 K at ambient pressure. Here, in this paper, we report on the effects of Rh substitution in Sr⁢(Ni 1-x ⁢Rh x ) 2 ⁢P 2 on the structural and superconducting properties. We studied the variation of the nearest P-P distances as a function of the Rh fraction at room temperature, as well as its temperature dependence for selected compositions. We find that increasing the Rh fraction leads to a decrease in the transition temperature between the ucT and tcO states, until a full suppression of the tcO state for x ≥ 0.166. The superconducting transition first remains nearly insensitive to the Rh fraction, and then it increases to 2.3 K after the tcO state is fully suppressed. These results are summarized in a phase diagram, built upon the characterization by energy dispersive x-ray spectroscopy, x-ray diffraction, resistance, magnetization, and specific heat measurements done on crystalline samples with varying Rh content. The relationship between band structure, crystal structure, and superconductivity is discussed based on previously reported band structure calculations on SrRh 2 ⁢P 2 . Moreover, the effect of Rh fraction on the stress-induced structural transitions is also addressed by means of strain-stress studies done by uniaxial compression of single-crystalline micropillars of Sr⁢(Ni 1-x ⁢Rh x ) 2 ⁢P 2 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Social network structure and the spread of complex contagions from a population genetics perspective

Ideas, behaviors, and opinions spread through social networks. If the probability of spreading to a new individual is a non-linear function of the fraction of the individuals’ affected neighbors, such a spreading process becomes a “complex contagion”. This non-linearity does not typically appear with physically spreading infections, but instead can emerge when the concept that is spreading is subject to game theoretical considerations (e.g. for choices of strategy or behavior) or psychological effects such as social reinforcement and other forms of peer influence (e.g. for ideas, preferences, or opinions). Here we study how the stochastic dynamics of such complex contagions are affected by the underlying network structure. Motivated by simulations of complex contagions on real social networks, we present a framework for analyzing the statistics of contagions with arbitrary non-linear adoption probabilities based on the mathematical tools of population genetics. The central idea is to use an effective lower-dimensional diffusion process to approximate the statistics of the contagion. This leads to a tradeoff between the effects of ”selection” (microscopic tendencies for an idea to spread or die out), random drift, and network structure. Our framework illustrates intuitively several key properties of complex contagions: stronger community structure and network sparsity can significantly enhance the spread, while broad degree distributions dampen the effect of selection compared to random drift. Finally, we show that some structural features can exhibit critical values that demarcate regimes where global contagions become possible for networks of arbitrary size. Our results draw parallels between the competition of genes in a population and memes in a world of minds and ideas. Our tools provide insight into the spread of information, behaviors, and ideas via social influence, and highlight the role of macroscopic network structure in determining their fate.

59 BASIC BIOLOGICAL SCIENCES↗

Structure of disordered TiO 2 phases from ab initio based deep neural network simulations

Amorphous TiO 2 (a-TiO 2 ) is widely used in many fields, ranging from photo-electrochemistry to bio-engineering, hence detailed knowledge of its atomic structure is of scientific and technological interest. Here we use an ab initio-based deep neural network potential (DP) to simulate large scale atomic models of crystalline and disordered TiO 2 with molecular dynamics. Our DP reproduces the structural properties of all (11) TiO 2 crystalline phases, predicts the densities and structure factors of molten and amorphous TiO 2 with only a few percent deviation from experiments, and describes the pressure dependence of the amorphous structure in agreement with recent observations. Furthermore, it can be extended to model additional structures and compositions and can be thus of great value in the study of TiO 2 -based (nano-)materials.

36 MATERIALS SCIENCE↗

Epitaxial growth, magnetoresistance, and electronic band structure of GdSb magnetic semimetal films

Motivated by observations of extreme magnetoresistance (XMR) in bulk crystals of rare-earth monopnictide (RE-V) compounds and emerging applications in novel spintronic and plasmonic devices based on thin-film semimetals, we have investigated the electronic band structure and transport behavior of epitaxial GdSb thin films grown on III-V semiconductor surfaces. The Gd 3 + ion in GdSb has a high spin S=7/2 and no orbital angular momentum, serving as a model system for studying the effects of antiferromagnetic order and strong exchange coupling on the resulting Fermi surface and magnetotransport properties of RE-Vs. Here, we present a surface and structural characterization study mapping the optimal synthesis window of thin epitaxial GdSb films grown on III-V lattice-matched buffer layers via molecular-beam epitaxy. To determine the factors limiting XMR in RE-V thin films and provide a benchmark for band-structure predictions of topological phases of RE-Vs, the electronic band structure of GdSb thin films is studied, comparing carrier densities extracted from magnetotransport, angle-resolved photoemission spectroscopy (ARPES), and density-functional theory (DFT) calculations. ARPES shows a hole-carrier rich, topologically trivial, semimetallic band structure close to complete electron-hole compensation, with quantum confinement effects in the thin films observed through the presence of quantum-well states. DFT-predicted Fermi wave vectors are in excellent agreement with values obtained from quantum oscillations observed in magnetic field-dependent resistivity measurements. An electron-rich Hall coefficient is measured despite the higher hole-carrier density, attributed to the higher electron Hall mobility. The carrier mobilities are limited by surface and interface scattering, resulting in lower magnetoresistance than that measured for bulk crystals.

36 MATERIALS SCIENCE↗

Structural phase diagram for Sm-substituted BiFeO 3 multiferroics

The structural evolution of Sm substituted BiFe⁢O 3 is studied by total x-ray scattering and structure modeling. It is shown that the crystal structure changes from polar to antipolar and then to nonpolar when the Sm to Bi ratio in the material approaches 20% and 40%, respectively, with no intermixing between the structure types. The evolution is driven by lattice strain induced by the difference in the size of Sm and Bi atoms, leading to changes in the pattern of octahedral tilts and Bi off-centering, which, in turn, induce changes in the multiferroic properties. Furthermore, the substitution ratio at which the different structure types emerge appears to be tied up with the average radius of the atomic species occupying the Bi sites in the perovskite lattice and volume occupied by a formula unit, rendering both quantities useful predictor variables for guiding computational searches for substituted BiFe⁢O 3 multiferroics with improved functional properties.

Ferroelectricity↗

Electronic structure of nitrogen-doped lutetium hydrides

First-principles density functional theory (DFT) calculations of supercell structures based on N-doped Fm $\bar3$m LuH 3 reveal configurations of Fm $\bar3$m Lu 8 H 23–x N that exhibit novel electronic properties such as flat bands, sharply peaked densities of states (van Hove singularities, vHs), and intersecting Dirac cones near the Fermi energy (E F ). These electronic properties are present when N substitutes H in the octahedral interstices of Fm $\bar3$ m LuH 3 . These structures also exhibit an interconnected metallic hydrogen network, a common feature of high-T c hydride superconductors. Electronic property systematics gives an estimate of T c for one structure that is well above the critical temperatures predicted for structures considered previously. DFT + U has an especially strong effect on one of the structures considered, enhancing the vHs and flat bands near E F . Finally, these results provide a basis for understanding the electronic properties observed for nitrogen-doped lutetium hydride.

36 MATERIALS SCIENCE↗

Structures of five salt forms of disulfonated monoazo dyes

The structures of five s -block metal salt forms of three disulfonated monoazo dyes are presented. These are poly[di-μ-aqua-diaqua[μ 4 -3,3'-(diazane-1,2-diyl)bis(benzenesulfonato)]disodium(I)], [Na 2 (C 12 H 8 N 2 O 6 S 2 )(H 2 O) 4 ] n , (I), catena -poly[[tetraaquacalcium(II)]-μ-3,3'-(diazane-1,2-diyl)bis(benzenesulfonato)], [Ca(C 12 H 8 N 2 O 6 S 2 )(H 2 O) 4 ] n , (II), catena -poly[[[diaquacalcium(II)]-μ-2-(4-amino-3-sulfonatophenyl)-1-(4-sulfonatophenyl)diazenium] dihydrate], {[Na(C 12 H 10 N 3 O 6 S 2 )(H 2 O) 2 ]·2H 2 O} n , (III), hexaaquamagnesium bis[2-(4-amino-3-sulfonatophenyl)-1-(4-sulfonatophenyl)diazenium] octahydrate, [Mg(H 2 O) 6 ](C 12 H 10 N 3 O 6 S 2 ) 2 ·8H 2 O, (IV), and poly[[{μ 2 -4-[2-(4-amino-2-methyl-5-methoxyphenyl)diazen-1-yl]benzene-1,3-disulfonato}di-μ-aqua-diaquabarium(II)] dihydrate], {[Ba(C 14 H 13 N 3 O 7 S 2 )(H 2 O) 4 ]·2H 2 O} n , (V). Compound (III) is that obtained on crystallizing the commercial dyestuff Acid Yellow 9 [74543-21-8]. The Mg species is a solvent-separated ion-pair structure and the others are all coordination polymers with bonds from the metal atoms to sulfonate groups. Compound (I) is a three-dimensional coordination polymer, (V) is a two-dimensional coordination polymer and both (II) and (III) are one-dimensional coordination polymers. The coordination behaviour of the azo ligands and the water ligands, the dimensionality of the coordination polymers and the overall packing motifs of these five structures are contrasted to those of monosulfonate monoazo congers. It is found that (I) and (II) adopt similar structural types to those of monosulfonate species but that the other three structures do not.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Isopropyl 3-deoxy-α- D - ribo -hexopyranoside (isopropyl 3-deoxy-α-D-glucopyranoside): evaluating trends in structural parameters

Isopropyl 3-de­oxy-α-D-ribo-hexo­pyran­oside (isopropyl 3-de­oxy-α-D-gluco­py­ran­oside), C 9 H 18 O 5 , (I), crystallizes from a methanol–ethyl acetate solvent mixture at room temperature in a 4C1 chair con­form­ation that is slightly dis­torted towards the C5 S C1 twist-boat form. A com­parison of the structural parameters in (I), methyl α-D-gluco­pyran­oside, (II), α-D-gluco­pyranosyl-(1→4)-D-glucitol (maltitol), (III), and 3-de­oxy-α-D-ribo-hexo­pyran­ose (3-de­oxy-α-D-gluco­pyran­ose), (IV), shows that most endocyclic and exocyclic bond lengths, valence bond angles and torsion angles in the aldohexo­pyranosyl rings are more affected by anomeric configuration, aglycone structure and/or the con­form­ation of exocyclic substituents, such as hy­droxy­methyl groups, than by mono­deoxy­genation at C3. The structural effects observed in the crystal structures of (I)–(IV) were confirmed though density functional theory (DFT) calculations in com­puted structures (I) c –(IV) c . Exocyclic hy­droxy­methyl groups adopt the gauche–gauche (gg) con­form­ation (H5 anti to O6) in (I) and (III), and the gauche–trans (gt) con­form­ation (C4 anti to O6) in (II) and (IV). The O-glycoside linkage con­form­ations in (I) and (III) resemble those observed in disaccharides containing β-(1→4) linkages.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Derived crystal structure of martensitic materials by solid–solid phase transformation

A mathematical description of crystal structure is proposed consisting of two parts: the underlying translational periodicity and the distinct atomic positions up to the symmetry operations in the unit cell, consistent with the International Tables for Crystallography. By the Cauchy–Born hypothesis, such a description can be integrated with the theory of continuum mechanics to calculate a derived crystal structure produced by solid–solid phase transformation. In addition, the expressions for the orientation relationship between the parent lattice and the derived lattice are generalized. Additionally, the derived structure rationalizes the lattice parameters and the general equivalent atomic positions that assist the indexing process of X-ray diffraction analysis for low-symmetry martensitic materials undergoing phase transformation. The analysis is demonstrated in a CuAlMn shape memory alloy. From its austenite phase (L2 1 face-centered cubic structure), it is identified that the derived martensitic structure has orthorhombic symmetry Pmmn with the derived lattice parameters a d = 4.36491, b d = 5.40865 and c d = 4.2402 Å, by which the complicated X-ray Laue diffraction pattern can be well indexed, and the orientation relationship can be verified.

36 MATERIALS SCIENCE↗

Computing Bottleneck Structures at Scale for High-Precision Network Performance Analysis

The Theory of Bottleneck Structures is a recently-developed framework for studying the performance of data networks. It describes how local perturbations in one part of the network propagate and interact with others. This framework is a powerful analytical tool that allows network operators to make accurate predictions about network behavior and thereby optimize performance. Previous work implemented a software package for bottleneck structure analysis, but applied it only to toy examples. In this work, we introduce the first software package capable of scaling bottleneck structure analysis to production-size networks. Here, we benchmark our system using logs from ESnet, the Department of Energy's high-performance data network that connects research institutions in the U.S. Using the previously published tool as a baseline, we demonstrate that our system achieves vastly improved performance, constructing the bottleneck structure graphs in 0.21 s and calculating link derivatives in 0.09 s on average. We also study the asymptotic complexity of our core algorithms, demonstrating good scaling properties and strong agreement with theoretical bounds. These results indicate that our new software package can maintain its fast performance when applied to even larger networks. They also show that our software is efficient enough to analyze rapidly changing networks in real time. Overall, we demonstrate the feasibility of applying bottleneck structure analysis to solve practical problems in large, real-world data networks.

benchmark↗

Reinforcement Learning of Structured Stabilizing Control for Linear Systems With Unknown State Matrix

This paper delves into designing feedback control gains for a continuous-time linear quadratic regulator (LQR) problem that is constrained to certain predefined structure with unknown state matrix. We bring forth the ideas from reinforcement learning (RL) in conjunction with sufficient stability and performance guarantees in order to design these structured gains using the trajectory measurements of states and controls. Here we first formulate a model-based framework using dynamic programming (DP) to embed the structural constraint to the LQR gain computation in the continuous-time setting, and then subsequently, formulate a policy iteration RL algorithm that can alleviate the requirement of known state matrix in conjunction with maintaining the feedback gain structure. The design enables a distributed learning control design which is necessary for many large-scale cyber-physical systems. Theoretical guarantees are provided for stability and convergence of the structured reinforcement learning (SRL) algorithm. We validate our theoretical results with numerical simulations on a multi-agent networked linear time-invariant (LTI) dynamic system.

42 ENGINEERING↗

From remotely sensed solar-induced chlorophyll fluorescence to ecosystem structure, function, and service: Part I—Harnessing theory

Solar-induced chlorophyll fluorescence (SIF) is a remotely sensed optical signal emitted during the light reactions of photosynthesis. The past two decades have witnessed an explosion in availability of SIF data at increasingly higher spatial and temporal resolutions, sparking applications in diverse research sectors (e.g., ecology, agriculture, hydrology, climate, and socioeconomics). These applications must deal with complexities caused by tremendous variations in scale and the impacts of interacting and superimposing plant physiology and three-dimensional vegetation structure on the emission and scattering of SIF. At present, these complexities have not been overcome. To advance future research, the two companion reviews aim to (1) develop an analytical framework for inferring terrestrial vegetation structures and function that are tied to SIF emission, (2) synthesize progress and identify challenges in SIF research via the lens of multi-sector applications, and (3) map out actionable solutions to tackle these challenges and offer our vision for research priorities over the next 5-10 years based on the proposed analytical framework. This paper is the first of the two companion reviews, and theory oriented. It introduces a theoretically rigorous yet practically applicable analytical framework. Guided by this framework, we offer theoretical perspectives on three overarching questions: (1) The forward (mechanism) question—How are the dynamics of SIF affected by terrestrial ecosystem structure and function? (2) The inference question: What aspects of terrestrial ecosystem structure, function, and service can be reliably inferred from remotely sensed SIF and how? (3) The innovation question: What innovations are needed to realize the full potential of SIF remote sensing for real-world applications under climate change? In conclusion, the analytical framework elucidates that process complexity must be appreciated in inferring ecosystem structure and function from the observed SIF; this framework can serve as a diagnosis and inference tool for versatile applications across diverse spatial and temporal scales.

59 BASIC BIOLOGICAL SCIENCES↗

On the vulnerability of data-driven structural health monitoring models to adversarial attack

Many approaches at the forefront of structural health monitoring rely on cutting-edge techniques from the field of machine learning. Recently, much interest has been directed towards the study of so-called adversarial examples; deliberate input perturbations that deceive machine learning models while remaining semantically identical. This article demonstrates that data-driven approaches to structural health monitoring are vulnerable to attacks of this kind. In the perfect information or ‘white-box’ scenario, a transformation is found that maps every example in the Los Alamos National Laboratory three-storey structure dataset to an adversarial example. Also presented is an adversarial threat model specific to structural health monitoring. The threat model is proposed with a view to motivate discussion into ways in which structural health monitoring approaches might be made more robust to the threat of adversarial attack.

60 APPLIED LIFE SCIENCES↗

Structural features of xylan dictate reactivity and functionalization potential for bio-based materials

Plant-based materials have the potential to replace some petroleum-based products, offering compostability and biodegradability as critical advantages. Xylan-rich biomass sources are gaining recognition due to their abundance and underutilization in current industrial applications. Research of potential xylan applications has been complicated by the complex and heterogeneous structure that varies for different xylan feedstocks. Acylation is a broadly used reaction in functionalization of polysaccharides at an industrial scale. However, the efficiency of this reaction varies with the xylan source. To optimize xylan valorization, a systematic understanding of structure–reactivity relationships is essential. This study explores, characterizes, and compares various xylan feedstocks in the acylation process. Xylan feedstocks were analyzed for their chemical composition, degree of polymerization, branching, solubility, and presence of impurities. These features were correlated with xylan glycotypes’ reactivity toward functionalization with succinic anhydride in an optimized DMSO/KOH condition, achieving carboxyl contents of up to 1.46. We used principal component analysis and hierarchical clustering to identify key structural features of xylan that promote its reactivity. Our findings reveal that xylans with higher xylose content and lower degrees of branching exhibit enhanced reactivity, achieving higher carboxyl content and yields. Structural analyses confirmed successful modification, and light scattering analyses showed dramatic changes in the solution properties. Succinylation improves the solubility and film-forming properties of native xylans. This study shows key structure–reactivity relationships in xylan succinylation, establishing that low branching, high xylose content, and reduced lignin impurity enhance chemical functionalization. The results offer a framework for selecting optimal biomass feedstocks and support future efforts in genetic and synthetic biology to design plants with tunable xylan architectures. These findings advance the hemicellulose valorization for applications in coatings and packaging.

Acylation↗

LigninGraphs: lignin structure determination with multiscale graph modeling

Lignin is an aromatic biopolymer found in ubiquitous sources of woody biomass. Designing and optimizing lignin valorization processes requires a fundamental understanding of lignin structures. Experimental characterization techniques, such as 2D-heteronuclear single quantum coherence (HSQC) nuclear magnetic resonance (NMR) spectra, could elucidate the global properties of the polymer molecules. Computer models could extend the resolution of experiments by representing structures at the molecular and atomistic scales. We introduce a graph-based multiscale modeling framework for lignin structure generation and visualization. The framework employs accelerated rejection-free polymerization and hierarchical Metropolis Monte Carlo optimization algorithms. We obtain structure libraries for various lignin feedstocks based on literature and new experimental NMR data for poplar wood, pinewood, and herbaceous lignin. The framework could guide researchers towards feasible lignin structures, efficient space exploration, and future kinetics modeling. Its software implementation in Python, LigninGraphs, is open-source and available on GitHub.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗