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Depolymerization as a Design Strategy: Depolymerization Etching of Polymerization-Induced Microphase Separations
Thermally triggered depolymerization has traditionally been viewed through the lens of sustainability and recycling, not as a constructive tool for materials design. Herein, we show that selective, thermally triggered depolymerization to gaseous monomer serves as a solvent-free strategy for generating porosity in nanostructured polymer materials, offering a means to bypass the mass transport limitations inherent in conventional solution-based etching. As a demonstration platform, we employed polymerization-induced microphase separation (PIMS) to generate disordered bicontinuous block copolymer structures with embedded depolymerizable domains. By incorporating a methacrylate block susceptible to thermal depolymerization within a cross-linked, depolymerization-resistant styrenic matrix, we developed a process we term depolymerization etching of polymerization-induced microphase separations (DEPIMS). This approach enables highly selective and efficient domain removal via reversion to monomer to produce mesoporous materials with high surface areas (>200 m 2 /g). Subsequent surface functionalization yielded mesoporous adsorbents with tunable uptake kinetics and among the highest dye adsorption capacities reported for PIMS-derived materials, demonstrating the adaptability of the DEPIMS platform for chemical separations. DEPIMS can also be extended to a gram-scale, one-pot approach to yield mesoporous materials with recoverable monomer in under 12 h. These findings reposition thermal depolymerization from a sustainability tool to a broadly enabling strategy for scalable, on-demand fabrication of functional nanostructured materials.
Blueprinting extendable nanomaterials with standardized protein blocks
A wooden house frame consists of many different lumber pieces, but because of the regularity of these building blocks, the structure can be designed using straightforward geometrical principles. The design of multicomponent protein assemblies, in comparison, has been much more complex, largely owing to the irregular shapes of protein structures. Here we describe extendable linear, curved and angled protein building blocks, as well as inter-block interactions, that conform to specified geometric standards; assemblies designed using these blocks inherit their extendability and regular interaction surfaces, enabling them to be expanded or contracted by varying the number of modules, and reinforced with secondary struts. Using X-ray crystallography and electron microscopy, we validate nanomaterial designs ranging from simple polygonal and circular oligomers that can be concentrically nested, up to large polyhedral nanocages and unbounded straight ‘train track’ assemblies with reconfigurable sizes and geometries that can be readily blueprinted. Because of the complexity of protein structures and sequence–structure relationships, it has not previously been possible to build up large protein assemblies by deliberate placement of protein backbones onto a blank three-dimensional canvas; the simplicity and geometric regularity of our design platform now enables construction of protein nanomaterials according to ‘back of an envelope’ architectural blueprints.
Density Functional Tight-Binding Models for Band Structures of Transition-Metal Alloys and Surfaces across the d -Block
First-principles electronic structure simulations are an invaluable tool for understanding chemical bonding and reactions. While machine-learning models such as interatomic potentials significantly accelerate the exploration of potential energy surfaces, electronic structure information is generally lost. Particularly in the field of heterogeneous catalysis, simulated electron band structures provide fundamental insights into catalytic reactivity. This ab initio knowledge is preserved in semiempirical methods such as density functional tight binding (DFTB), which extend the accessible computational length and time scales beyond first-principles approaches. In this paper here we present Shell-Optimized Atomic Confinement (SOAC) DFTB electronic-part-only parametrizations for bulk and surface band structures of all d-block transition metals that enable efficient predictions of electronic descriptors for large structures or high-throughput studies on complex systems outside the computational reach of density functional theory.
ATRP Enhances Structural Correlations In Polymerization–Induced Phase Separation**
Synthetic methods to control the structure of materials at sub–micron scales are typically based on the self–assembly of structural building blocks with precise size and morphology. On the other hand, many living systems can generate structure across a broad range of length scales in one step directly from macromolecules, using phase separation. Here, we introduce and control structure at the nano– and microscales through polymerization in the solid state, which has the unusual capability of both triggering and arresting phase separation. In particular, we show that atom transfer radical polymerization (ATRP) enables control of nucleation, growth, and stabilization of phase–separated poly–methylmethacrylate (PMMA) domains in a solid polystyrene (PS) matrix. ATRP yields durable nanostructures with low size dispersity and high degrees of structural correlations. Furthermore, we demonstrate that the length scale of these materials is controlled by the synthesis parameters.
Structural complexity in the f -block: small deviations of the complexation of lanthanides by O,Oʹ -diethylmonothiophosphate
Dithiophosphinic acids undergo radiolytic degradation during the extraction of actinides in used nuclear fuel. These will degrade into monothiophosphinic acids and then to phosphinic acids. To elucidate how the complexes that are formed during these radioactive separations change as the ligand degrades, the mixed donor ligand O,O′- diethylmonothiophosphate is chosen as an analog for the monothiophosphinic intermediate. Herein, the monothiophosphate complexes Ln 2 (OPS(OEt) 2 ) 6 (H 2 O) 8 (Ln = La) (La 2 L 6 H 2 O), Ln 2 (OPS(OEt) 2 ) 6 (EtOH) 4 (Ln = La) (La 2 L 6 EtOH), K 2 [Ln(OPS(OEt) 2 ) 5 (H 2 O) 2 ]·H 2 O·CH 2 Cl 2 , (Ln = Ce) (CeL 5 -α), K 2 [Ln(OPS(OEt) 2 ) 5 (H 2 O) 2 ]·H 2 O·CH 2 Cl 2 , (Ln = Pr) (PrL 5 -β), K[Ln(OPS(OEt) 2 ) 4 (H 2 O) 3 ], (Ln = Pr, Sm-Er) (ML 4 ), and K 3 [Ln(OPS(OEt) 2 ) 6 ], (Ln = Dy) (DyL 6 ) were synthesized and characterized using single-crystal X-ray diffraction and optical spectroscopy. Although the lanthanides contract in a nearly linear fashion, the structural changes observed as the f-block is traversed in these compounds are not necessarily a hard line but more so a blend of different structure types possible for each f-element. Furthermore, comparison of the Ln−O bond lengths shows a nearly linear contraction, but the Ln−S bond lengths do not monotonically decrease because of the hard Lewis acidity of the Ln 3+ cations.
Shaping Symmetry and Molding Morphology of Triply-Periodic Network Assemblies via Molecular Design and Processing of Block Copolymers
Final technical report on DOE project conducted at Texas A & M University Dept. of Materials Science and Engineering concerning finding and understanding the design rules for triply periodic, bicontinuous morphological microdomain structures of block copolymers.
Areal interpolation of population projections consistent with different SSPs from 1-km resolution to block level based on USA Structures dataset
Population data are normally collected at various census administrative levels, and areal interpolation of population is often required to transform population to the desired spatial resolution. Building footprint datasets, such as Microsoft building footprints, have proven to be useful in estimating population distribution and can therefore be used for areal interpolation of population. In addition to Microsoft building footprints, the recently released USA Structures dataset provides additional information such as building type and building height for some regions, which may provide valuable information for a better depiction of population distribution and improved population areal interpolation accuracy. In this study, we have conducted areal interpolation of population projections consistent with three different Shared Socioeconomic Pathways (SSP2, SSP3, and SSP5) from 1-km grid cells to block level in Washington state for every ten years from 2020 to 2040 based on USA Structures. We assessed USA Structures-based population downscaling accuracy using U.S. decennial survey data in 2020 under three different downscaling schemes, including population downscaling from census tracts to block groups, from census tracts to blocks, and from block groups to blocks. The resulting accuracies were compared with those based on Microsoft building footprints. The comparison showed that USA Structures achieved higher accuracies across different population density regions and areas with different urbanization extent within our study area.
A medium-range structure motif linking amorphous and crystalline states
Amorphous materials have no long-range order, but there are ordered structures at short range (2–5 Å), medium range (5–20 Å) and even longer length scales. While regular and semiregular polyhedra are often found as short-range ordering in amorphous materials, the nature of medium-range order has remained elusive. Consequently, it is difficult to determine whether there exists any structural link at medium range or longer length scales between the amorphous material and its crystalline counterparts. Moreover, an amorphous material often crystallizes into a phase of different composition, with very different underlying structural building blocks, further compounding the issue. Here, we capture an intermediate crystalline cubic phase in a Pd-Ni-P amorphous alloy and reveal the structure of the medium-range order, a six-membered tricapped trigonal prism cluster (6M-TTP) with a length scale of 12.5 Å. We find that the 6M-TTP can pack periodically to several tens of nanometres to form the cube phase. Our experimental observations provide evidence of a structural link between the amorphous and crystalline phases in a Pd-Ni-P alloy at the medium-range length scale and suggest that it is the connectivity of the 6M-TTP clusters that distinguishes the crystalline and amorphous phases. These findings will shed light on the structure of amorphous materials at extended length scales beyond that of short-range order.
Reversible Changes in the Grain Structure and Conductivity in a Block Copolymer Electrolyte
Here, we study the phase behavior of a triblock organic–inorganic hybrid copolymer, poly(polyhedral oligomeric silsesquioxane)-b-poly(ethylene oxide)-b-poly(polyhedral oligomeric silsesquioxane) (POSS-PEO-POSS)/lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) salt mixture, as a function of temperature. The polymer exhibits a lamellar morphology both in the neat state and in the presence of salt. However, the average grain size increases substantially when the electrolyte is heated above 113 °C. The grain structure of this sample changes reversibly with temperature, that is, smaller grains reappear when the electrolyte is cooled below 113 °C. While annealing block copolymers at high temperatures often leads to an increase in the grain size, this change is generally irreversible. The reason for the reversible change in the grain structure of the POSS-PEO-POSS/LiTFSI electrolyte is discussed. The ionic conductivity of the electrolyte also exhibits reversible changes in this temperature window. Knowledge of the grain structure is crucial for understanding ion transport in nanostructured electrolytes.
Thermodynamic Basis for the Stabilization of Helical Peptoids by Chiral Sidechains
Peptoids are a class of highly customizable biomimetic foldamers that retain properties from both proteins and polymers. It has been shown that peptoids can adopt peptide-like secondary structures through the careful selection of sidechain chemistries, but the underlying conformational landscapes that drive these assemblies at the molecular level remain poorly understood. Given the high flexibility of the peptoid backbone, it is essential that methods applied to study peptoid secondary structure formation possess the requisite sensitivity to discriminate between structurally similar yet energetically distinct microstates. In this work, a generalizable simulation scheme is used to robustly sample the complex folding landscape of various 12mer polypeptoids, resulting in a predictive model that links sidechain chemistry with preferential assembly into one of 12 accessible backbone motifs. Using a variant of the metadynamics sampling method, four peptoid dodecamers are simulated in water: sarcosine, N-(1-phenylmethyl)glycine (Npm), (S)-N-(1-phenylethyl)glycine (Nspe), and (R)-N-(1-phenylethyl)glycine (Nrpe)–to determine the underlying entropic and energetic impacts of hydrophobic and chiral peptoid sidechains on secondary structure formation. Our results indicate that the driving forces to assemble Nrpe and Nspe sequences into polyproline type-I helices in water are found to be enthalpically driven, with small benefits from an entropic gain for isomerization and steric strain due to the presence of the chiral center. The minor entropic gains from bulky chiral sidechains in Nrpe- and Nspe-containing peptoids can be explained through increased configurational entropy in the cis state. However, overall assembly into a helix is found to be overall entropically unfavorable. Furthermore, these results highlight the importance of considering the many various competing interactions in the rational design of peptoid secondary structure building blocks.
Tunable Metal–Organic Frameworks Based on 8-Connected Metal Trimers for High Ethane Uptake
Metal trimers [M 3 (O/OH)](OOCR) 6 are among the most important structural building blocks. From these trimers, a great success has been achieved in the design of 6- or 9-connected framework materials with various topological features and outstanding gas-sorption properties. In comparison, 8-connected trimer-based MOFs are rare. Given multiple competitive pathways for the formation of 6- or 9-connected frameworks, it remains challenging to identify synthetic or structural parameters that can be used to direct self-assembly process towards trimer-based 8-connected materials. Here, we reveal a viable strategy called angle bending modulation for creating a prototypical MOF type based on 8-connected M 3 (OH)(OOCR) 5 (Py-R) 3 trimers, M = Zn, Co, Fe). As a proof of concept, we synthesized six members in this family using three types of ligands (CPM-80, -81, and -82). These materials do not possess open-metal sites and show excellent uptake capacity for various hydrocarbon gas molecules and inverse C 2 H 6 /C 2 H 4 selectivity. CPM-81-Co, made from 2,5-furandicarboxylate and isonicotinate, features selectivity of 1.80 with high uptake capacity for ethane (123 cm 3 /g -1 ) and ethylene (113 cm 3 /g -1 ) at 298 K and 1 bar.
Approximate symmetries in d = 4 CFTs with an Einstein gravity dual
By applying the stress-tensor-scalar operator product expansion (OPE) twice, we search for algebraic structures in d = 4 conformal field theories (CFTs) with a pure Einstein gravity dual. We find that a rescaled mode operator defined by an integral of the stress tensor T ++ on a d = 2 plane satisfies a Virasoro-like algebra when the dimension of the scalar is large. The structure is enhanced to include a Kac-Moody-type algebra if we incorporate the T -- component. In our scheme, the central terms are finite. It remains challenging to directly compute the stress-tensor sector of d = 4 scalar four-point functions at large central charge, which, based on holography and bootstrap methods, were recently shown to have a Virasoro/ $\mathcal{W}$-algebra vacuum block-like structure.
Enhanced purification coupled with biophysical analyses shows cross-β structure as a core building block for Streptococcus mutans functional amyloids
Streptococcus mutans is an etiologic agent of human dental caries that forms dental plaque biofilms containing functional amyloids. Three amyloidogenic proteins, P1, WapA, and Smu_63c were previously identified. C123 and AgA are naturally occurring amyloid-forming fragments of P1 and WapA, respectively. We determined that four amyloidophilic dyes, ThT, CDy11, BD-oligo, and MK-H4, differentiate C123, AgA, and Smu_63c amyloid from monomers, but non-specific binding to bacterial cells in the absence of amyloid precludes their utility for identifying amyloid in biofilms. Congo redinduced birefringence is a more specific indicator of amyloid formation and differentiates biofilms formed by wild-type S. mutans from a triple ΔP1/WapA/Smu_63c mutant with reduced bioiflm forming capabilities. Amyloid accumulation is a late event, appearing in older S. mutans biofilms after 60hours of growth. Amyloid derived from pure preparations of all three proteins is visualized by electron microscopy as mat-like structures. Typical amyloid fibers become evident following protease digestion to eliminate non-specific aggregates and monomers. Amyloid mats, similar in appearance to those reported in S. mutans biofilm extracellular matrices, are reconstituted by co-incubation of monomers and amyloid fibers. X-ray fiber diffraction of amyloid mats and fibers from all three proteins demonstrate patterns reflective of a cross-β amyloid structure.
Discontinuous Galerkin discretization for quantum simulation of chemistry
All-electron electronic structure methods based on the linear combination of atomic orbitals method with Gaussian basis set discretization offer a well established, compact representation that forms much of the foundation of modern correlated quantum chemistry calculations—on both classical and quantum computers. Despite their ability to describe essential physics with relatively few basis functions, these representations can suffer from a quartic growth of the number of integrals. Recent results have shown that, for some quantum and classical algorithms, moving to representations with diagonal two-body operators can result in dramatically lower asymptotic costs, even if the number of functions required increases significantly. We introduce a way to interpolate between the two regimes in a systematic and controllable manner, such that the number of functions is minimized while maintaining a block-diagonal structure of the two-body operator and desirable properties of an original, primitive basis. Techniques are analyzed for leveraging the structure of this new representation on quantum computers. Empirical results for hydrogen chains suggest a scaling improvement from O(N 4.5 ) in molecular orbital representations to O(N 2.6 ) in our representation for quantum evolution in a fault-tolerant setting, and exhibit a constant factor crossover at 15 to 20 atoms. Moreover, we test these methods using modern density matrix renormalization group methods classically, and achieve excellent accuracy with respect to the complete basis set limit with a speedup of 1–2 orders of magnitude with respect to using the primitive or Gaussian basis sets alone. These results suggest our representation provides significant cost reductions while maintaining accuracy relative to molecular orbital or strictly diagonal approaches for modest-sized systems in both classical and quantum computation for correlated systems.
Low-Dimensional Contact Layers for Enhanced Perovskite Photodiodes
Controlling defects and energy-band alignments are of paramount importance to the development of high-performance perovskite-based photodiodes. Yet, concurrent improvements in interfacial contacts and defect reduction simply by tailoring bottom contacts have not been investigated. An effective strategy is reported that can simultaneously improve energy-band alignments and structural defects by introducing low-dimensional contact (LDC) layers at the bottom interface. It is found that LDC-based perovskites considerably suppress undesirable structural defects induced by microstrains, resulting in reduced nonradiative recombination centers and improved carrier lifetimes. Additionally, the resulting LDC-based interface structures help block minority carrier injection from the electrodes by forming built-in electric fields. As a consequence, LDC-based perovskite photodiodes showed improved light detection capabilities. Finally, the result opens an avenue to yield highly efficient photodiodes.
A duality-based coupling of Cosserat crystal plasticity and phase field theories for modeling grain refinement
High-rate deformation processes of metals entail intense grain refinement and special attention needs to be paid to capture the evolution of microstructure. In this article, a new formulation for coupling Cosserat crystal plasticity and phase field is developed. A common approach is to penalize kinematic incompatibility between lattice orientation and displacement-based elastic rotation. However, this can lead to significant solution sensitivity to the penalty parameter, resulting in low accuracy and convergence rates. To address these issues, a duality-based formulation is developed which directly imposes the rotational kinematic compatibility. A weak inf-sup-based skew-symmetric stress projection is introduced to suppress instabilities present in the dual formulation. An additional least squares stabilization is introduced to suppress the spurious lattice rotation with a suitable parameter range derived analytically and validated numerically. The required high-order continuity is attained by the reproducing kernel approximation. It is observed that equal order displacement-rotation-phase field approximations are stable, which allows efficient employment of the same set of shape functions for all independent variables. The proposed formulation is shown to yield superior accuracy and convergence with marginal parameter sensitivity compared to the penalty-based approach and successfully captures the dominant rotational recrystallization mechanism including block dislocation structures and grain boundary migration.
Progressive Hedging Decomposition for Solutions of Large-Scale Process Family Design Problems
Rapid, wide-scale deployment of green process systems, such as carbon capture or water desalination systems, is essential for combatting climate change. Methods relying on traditional design or modularity fail to capture the benefits of both economies of numbers and economies of scale. We have proposed process family design, which designs a family of processes simultaneously exploiting opportunities for common elements. In previous work, we explored different optimization formulations to solve this problem. In this work, we develop a decomposition approach to tackle larger problems efficiently. We solve a water desalination case study, which is too large to solve within a reasonable timeframe with the discretization formulation. We exploit the block angular structure of the discretization problem to decompose and solve using Progressive Hedging (PH). We use the open-source Python package mpi-sppy to execute PH which allows us to leverage parallelization and a HPC cluster to further improve solution time.