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At least 1,153 records · Page 64

Architector for high-throughput cross-periodic table 3D complex building

Abstract Rare-earth and actinide complexes are critical for a wealth of clean-energy applications. Three-dimensional (3D) structural generation and prediction for these organometallic systems remains a challenge, limiting opportunities for computational chemical discovery. Here, we introduce Architector , a high-throughput in-silico synthesis code for s-, p-, d-, and f-block mononuclear organometallic complexes capable of capturing nearly the full diversity of the known experimental chemical space. Beyond known chemical space, Architector performs in-silico design of new complexes including any chemically accessible metal-ligand combinations. Architector leverages metal-center symmetry, interatomic force fields, and tight binding methods to build many possible 3D conformers from minimal 2D inputs including metal oxidation and spin state. Over a set of more than 6,000 x-ray diffraction (XRD)-determined complexes spanning the periodic table, we demonstrate quantitative agreement between Architector-predicted and experimentally observed structures. Further, we demonstrate out-of-the box conformer generation and energetic rankings of non-minimum energy conformers produced from Architector , which are critical for exploring potential energy surfaces and training force fields. Overall, Architector represents a transformative step towards cross-periodic table computational design of metal complex chemistry.

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Methods to Calculate Electronic Excited-State Dynamics for Molecules on Large Metal Clusters with Many States: Ensuring Fast Overlap Calculations and a Robust Choice of Phase

Here, we present an efficient set of methods for propagating excited-state dynamics involving a large number of configuration interaction singles (CIS) or Tamm-Dancoff approximation (TDA) single-reference excited states. Specifically, (i) following Head-Gordon et al., we implement an exact evaluation of the overlap of singly-excited CIS/TDA electronic states at different nuclear geometries using a biorthogonal basis and (ii) we employ a unified protocol for choosing the correct phase for each adiabat at each geometry. For many-electron systems, the combination of these techniques significantly reduces the computational cost of integrating the electronic Schrodinger equation and imposes minimal overhead on top of the underlying electronic structure calculation. As a demonstration, we calculate the electronic excited-state dynamics for a hydrogen molecule scattering off a silver metal cluster, focusing on high-lying excited states, where many electrons can be excited collectively and crossings are plentiful. Interestingly, we find that the high-lying, plasmon-like collective excitation spectrum changes with nuclear dynamics, highlighting the need to simulate non-adiabatic nuclear dynamics and plasmonic excitations simultaneously. In the future, the combination of methods presented here should help theorists build a mechanistic understanding of plasmon-assisted charge transfer and excitation energy relaxation processes near a nanoparticle or metal surface.

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Library of Advanced Materials for Engineering (LAM) 5.8

Accurate and efficient constitutive modeling remains a cornerstone issue for solid mechanics analysis. Over the years, the LAMÉ advanced material model library has grown to address this challenge by implementing models capable of describing material systems spanning soft polymers to stiff ceramics including both isotropic and anisotropic responses. Inelastic behaviors including (visco)plasticity, damage, and fracture have all incorporated for use in various analyses. This multitude of options and flexibility, however, comes at the cost of many capabilities, features, and responses and the ensuing complexity in the resulting implementation. Therefore, to enhance confidence and enable the utilization of the LAMÉ library in application, this effort seeks to document and verify the various models in the LAMÉ library. Specifically, the broader strategy, organization, and interface of the library itself is first presented. The physical theory, numerical implementation, and user guide for a large set of models is then discussed. Importantly, a number of verification tests are performed with each model to not only have confidence in the model itself but also highlight some important response characteristics and features that may be of interest to end-users. Finally, in looking ahead to the future, approaches to add material models to this library and further expand the capabilities are presented.

36 MATERIALS SCIENCE↗

Library of Advanced Materials for Engineering (LAMÉ) 5.10

Accurate and efficient constitutive modeling remains a cornerstone issue for solid mechanics analysis. Over the years, the LAMÉ advanced material model library has grown to address this challenge by implementing models capable of describing material systems spanning soft polymers to stiff ceramics including both isotropic and anisotropic responses. Inelastic behaviors including (visco)plasticity, damage, and fracture have all incorporated for use in various analyses. This multitude of options and flexibility, however, comes at the cost of many capabilities, features, and responses and the ensuing complexity in the resulting implementation. Therefore, to enhance confidence and enable the utilization of the LAMÉ library in application, this effort seeks to document and verify the various models in the LAMÉ library. Specifically, the broader strategy, organization, and interface of the library itself is first presented. The physical theory, numerical implementation, and user guide for a large set of models is then discussed. Importantly, a number of verification tests are performed with each model to not only have confidence in the model itself but also highlight some important response characteristics and features that may be of interest to end-users. Finally, in looking ahead to the future, approaches to add material models to this library and further expand the capabilities are presented.

36 MATERIALS SCIENCE↗

The General Atomic and Molecular Electronic Structure System (GAMESS): Novel Methods on Novel Architectures

The primary focus of GAMESS over the last 5 years has been the development of new high-performance codes that are able to take effective and efficient advantage of the most advanced computer architectures, both CPU and accelerators. These efforts include employing density fitting and fragmentation methods to reduce the high scaling of well-correlated (e.g., coupled-cluster) methods as well as developing novel codes that can take optimal advantage of graphical processing units and other modern accelerators. Because accurate wave functions can be very complex, an important new functionality in GAMESS is the quasi-atomic orbital analysis, an unbiased approach to the understanding of covalent bonds embedded in the wave function. Finally, best practices for the maintenance and distribution of GAMESS are also discussed.

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Origin of the background absorption in carbon nanotubes: Phonon-assisted excitonic continuum

Excitonic effects in 1D semiconductors can be qualitatively different from those in higher dimensions. In particular, the Sommerfeld factor, the ratio of the above-band-edge excitonic continuum absorption to free electron-hole pair generation, has been shown to be less than 1 (suppressed) in 1D systems while it is larger than 1 (enhanced) in 2D and 3D systems. Strong continuum suppression indeed exists in semiconducting single-wall carbon nanotubes, a prototypical 1D semiconductor. However, absorption spectra for carbon nanotubes are typically fit with a combination of Lorentzians and a polynomial background baseline with little physical meaning. We performed absorption measurements in aligned single-chirality (6,5) carbon nanotube films. The obtained spectra were fit with our theoretical model obtained by solving the Boltzmann scattering equation involving fifty-nine different types of transitions among three different types of quasiparticles. Specifically, we took into account microscopic interactions between photons, phonons, and excitons, including their dispersions, which unambiguously demonstrated that the background absorption is due to phonon-assisted transitions from the semiconductor vacuum to finite-momentum continuum states of excitons. The excellent agreement we obtained between experiment and theory suggests that our numerical technique can be seamlessly extended to compute strongly out-of-equilibrium many-body dynamics and time-resolved spectra in low-dimensional materials.

36 MATERIALS SCIENCE↗

Library of Advanced Materials for Engineering (LAMÉ) 4.58

Accurate and efficient constitutive modeling remains a cornerstone issue for solid mechanics analysis. Over the years, the LAMÉ advanced material model library has grown to address this challenge by implementing models capable of describing material systems spanning soft polymers to stiff ceramics including both isotropic and anisotropic responses. Inelastic behaviors including (visco)plasticity, damage, and fracture have all incorporated for use in various analyses. This multitude of options and flexibility, however, comes at the cost of many capabilities, features, and responses and the ensuing complexity in the resulting implementation. Therefore, to enhance confidence and enable the utilization of the LAMÉ library in application, this effort seeks to document and verify the various models in the LAMÉ library. Specifically, the broader strategy, organization, and interface of the library itself is first presented. The physical theory, numerical implementation, and user guide for a large set of models is then discussed. Importantly, a number of verification tests are performed with each model to not only have confidence in the model itself but also highlight some important response characteristics and features that may be of interest to end-users. Finally, in looking ahead to the future, approaches to add material models to this library and further expand the capabilities are presented.

36 MATERIALS SCIENCE↗

Reversible Ligand Protonation in Noninnocent Constrained-Geometry-Like Group 4 Complexes

The proligands C 5 H 5 CMe 2 CHPhOx R (R = Me 2 , CHMe 2 , and CMe 3 ) react with M(NMe 2 ) 4 (M = Ti, Zr, and Hf) to give monodeprotonated (Ox R CHPhCMe 2 C 5 H 4 )M(NMe 2 ) 3 , doubly deprotonated (C 5 H 4 CMe 2 CPhOx R )M(NMe 2 ) 2 , or a mixture of both. The observed products depend on reaction conditions, the oxazoline substituent, and the metal center, with 4-t-butyl-oxazoline or Ti giving only the monodeprotonated (Ox R CHPhCMe 2 C 5 H 4 )M(NMe 2 ) 3 . Amine elimination from (Ox R CHPhCMe 2 C 5 H 4 )M(NMe 2 ) 3 to give (C 5 H 4 CMe 2 CPhOx R )M(NMe 2 ) 2 is reversible for 4,4-dimethyl- and 4-isopropyl-oxazoline-based ligands in Zr or Hf complexes. Temperature-dependent kinetic studies of the equilibration of (C 5 H 4 CMe 2 CPhOx Me2 )Zr(NMe 2 ) 2 , HNMe 2 and (Ox Me2 CHPhCMe 2 C 5 H 4 )Zr(NMe 2 ) 3 provide the experimental thermodynamic parameters ΔS° = -17.4 ± 2.6 cal·mol –1 K –1 and ΔH° = -6.8 ± 0.8 kcal·mol –1 . An Eyring plot of the rate constants, determined from the system as it approaches equilibrium, gives the activation entropy and activation enthalpy for the addition of (C 5 H 4 CMe 2 CPhOx Me2 )Zr(NMe 2 ) 2 and HNMe 2 as -36 ± 4 cal·mol –1 K –1 and 8.9 ± 1.3 kcal·mol –1 , respectively; the elimination of HNMe 2 from (Ox Me2 CHPhCMe 2 C 5 H 4 )Zr(NMe 2 ) 3 is characterized by ΔS ‡ = -19 ± 5 cal·mol –1 K –1 and ΔH ‡ = 15.7 ± 1.5 kcal·mol –1 . DFT computational models indicate a single-step, nonlinear transfer of the H between the benzylic position of the noninnocent, oxazoline-coordinated ligand and NMe 2 . Computations also confirm the negative activation entropy and the trends in the barriers support the experimental results. Together, these studies indicate the importance of steric effects from the oxazoline ligand, metal center, ancillary ligands, and leaving group on the shuttling of the proton between HNMe 2 and the noninnocent ligand. Finally, these effects suggest that coordination of oxazoline to the metal center is a key part of the benzylic deprotonation and noninnocent behavior of the cyclopentadienyl-oxazoline ligand.

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Field Programmable Gate Arrays for Enhancing the Speed and Energy Efficiency of Quantum Dynamics Simulations

We present the first application of field programmable gate arrays (FPGAs) as new, customizable hardware architectures for carrying out fast and energy-efficient quantum dynamics simulations of large chemical/material systems. Instead of tailoring the software to fixed hardware, which is the typical case for writing quantum chemistry code for central processing units (CPUs) and graphics processing units (GPUs), FPGAs allow us to directly customize the underlying hardware (even at the level of specific electrical signals in the circuit) to give a truly optimized computational performance for quantum dynamics calculations. By offloading the most intensive and repetitive calculations onto an FPGA, we show that the computational performance of our real-time electron dynamics calculations can even exceed that of optimized commercial mathematical libraries running on high-performance GPUs. In addition to this impressive computational speedup, we show that FPGAs are immensely energy-efficient and consume 4 times less energy than modern GPU or CPU architectures. These energy savings are a practical and important metric for supercomputing centers (many of which exceed over $1 million in power costs alone), as exascale computing capabilities become more widespread and commonplace. Taken together, the implementation techniques and performance metrics of our study demonstrate that FPGAs could play a promising role in upcoming quantum chemistry and materials science applications, particularly for the acceleration and energy-efficient execution of quantum dynamics calculations.

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The carbon challenge: Design, synthesis, and chemisorption behavior of solid sorbents in direct air capture of carbon dioxide

Direct air capture (DAC) of CO 2 is a promising solution for reducing the carbon footprint through "negative emission" technology. However, the low CO 2 concentration (~400 ppm) and the dynamic nature of DAC processes present challenges in designing effective sorbent systems. Recent advancements in material design and structural engineering have led to the development of high-performance solid sorbents, offering a more stable, safe, and energy-efficient alternative to traditional liquid CO 2 capture methods. This review highlights progress in solid sorbent-based DAC, focusing on amine-modified materials, hydrogen-bonded frameworks, and ionic liquid-engineered scaffolds. The discussion covers design principles, synthesis methodologies, and their impact on CO 2 chemisorption, comparing the advantages and limitations of each approach. Characterization techniques, especially operando methods and computational tools, are reviewed to understand sorbent behavior during CO 2 integration and release. The reaction pathways and interaction mechanisms of these sorbents with CO 2 are analyzed to guide future design. Additionally, the CO 2 chemisorption behaviors, including capacity, sorption kinetics, recyclability, and durability in the presence of gaseous impurities and under humid conditions will be evaluated and compared. Further, the review offers unique insights into the physical properties, chemical structures, and surface engineering effects of these sorbents, based on comprehensive characterization and evaluation techniques.

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Manipulating Pore Topology and Functionality to Promote Fluorocarbon-Based Adsorption Cooling

With the worldwide demand for refrigeration and cooling expected to triple, it is increasingly important to search for alternative energy resources to drive the refrigeration cycles with reduced electricity consumption. Recently, adsorption cooling has gained increased attention since energy reallocation in such systems is based on gas adsorption/desorption, which can be driven by waste/natural heat sources. Eco-friendly sorption-based cooling relies on the cyclic transfer of refrigerant gas from a high to low energy state by the pseudo-compression effect resulting from adsorption and desorption. The driving force for energy transfer relies on heat rather than electricity. The performance of a sorption chiller is primarily influenced by this cyclic sorption behavior, which is characterized as the working capacity of the porous sorbent. Thus increases in this working capacity directly translate to a more compact and efficient cooling system. How-ever, a lack of highly effective sorbent/refrigerant pairs lowers cooling performance, and therefore has limited applicability. To this end, synthetic metal-organic frameworks (MOFs) and covalent organic polymers (COPs) possess higher porosity and greater tunability leading to more substantial potential benefits for adsorption, compared to traditional sorbent materials. Similarly, hydrofluorocarbon refrigerants have more favorable applicability given ease of operation above atmospheric pressures due to suitable saturated vapor pressures and boiling points. For these reasons, our work focuses on an ongoing strategy to promote sorption cooling via improvements in the sorbent/refrigerant pair. Specifically, we target the interaction of hydrofluorocarbon refrigerants with MOF/COP materials at a molecular level by interpreting the host-guest chemistry and the role of framework pore topology. These molecular level differences translate to cooling performance, which is described herein. These strategies include engineering framework porosity (i.e., pore size, pore volume) by using elongated organic linkers and stereochemistry control during synthesis; manipulating the sorb-ate/sorbent interaction by introducing functional moieties or unsaturated metal centers to enhance working capacities in narrow pressure ranges; varying pore topology/morphology to impact adsorption isotherm behavior; and leveraging defective sites within the frameworks to further enhance adsorption capability. Here this atomic level understanding of sorb-ate-sorbent interactions is conducted using various in situ experimental techniques such as synchrotron-based X-ray diffraction, X-ray absorption spectroscopy, in situ Fourier transform infrared spectroscopy, and direct sorption energies determinization with calorimetry. Moreover, the experimentally studied interactions and the corresponding adsorption mechanism are corroborated by computational studies using density functional theory (DFT) and grand canonical Monte Carlo (GCMC) simulations. Using this approach, we envision the capability to engineer designed frameworks with precise molecular control to target refrigerant molecules and thereby enhance the performance of desired working pairs for sorption-based cooling.

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Toward a persistent event-streaming system for high-performance computing applications

High-performance computing (HPC) applications have traditionally relied on parallel file systems and file transfer services to manage data movement and storage. Alternative approaches have been proposed that use direct communications between application components, trading persistence and fault tolerance for speed. Event-driven architectures, as popularized in enterprise contexts, present a compelling middle ground, avoiding the performance cost and API constraints of parallel file systems while retaining persistence and offering impedance matching between application components. However, adapting streaming frameworks to HPC workloads requires addressing challenges unique to HPC systems. This paper investigates the potential for a streaming framework designed for HPC infrastructures and use cases. We introduce Mofka, a persistent event-streaming framework designed specifically for HPC environments. Mofka combines the capabilities of a traditional streaming service with optimizations tailored to the HPC context, such as support for massively multicore nodes, efficient scaling for large producer-consumer workflows, RDMA-enabled high-performance network communications, specialized network fabrics with multiple links per node, and efficient handling of large scientific data payloads. Built using the Mochi suite of HPC data service components, Mofka provides a lightweight, modular, and high-performance solution for persistent streaming in HPC systems. We present the architecture of Mofka and evaluate its performance against Kafka and Redpanda using benchmarks on diverse platforms, including Argonne's Polaris and Oak Ridge's Frontier supercomputers, showing up to 8× improvement in throughput in some scenarios. We then demonstrate its utility in several real-world applications: a tomographic reconstruction pipeline, a workflow for the discovery of metal-organic frameworks for carbon capture, and the instrumentation of Dask workflows for provenance tracking and performance analysis.

HPC↗

Deep Learning Approaches for Predicting the Surface Tension of Ionic Liquids

Ionic liquids (ILs) are a novel class of solvents that have attracted significant attention due to their unique and tunable properties. Among their physiochemical characteristics, surface tension plays a critical role in various industrial applications including electrolytes, heat transfer fluids, and separation processes. However, because of the exploratory nature of IL design and the vast combinatorial space of possible anion–cation pairs, the experimental determination of these properties is often impractical, being both time-consuming and costly. To overcome these challenges, computational approaches are increasingly employed to develop accurate predictive models that can accelerate IL discovery and design. In this study, we present two deep learning (DL) models for predicting the surface tension of ILs across a broad temperature range at a constant pressure. The models use simplified molecular input line entry system, SMILES, representations of ILs to extract molecular features as inputs. Both DL models demonstrate excellent agreement with experimental data, achieving an R 2 value of 0.990 and a root-mean-square error of 0.792 mN/m. In conclusion, these results offer valuable insights for the rapid screening and rational design of ILs with tailored surface tension values.

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Structural and Dynamical Roles of Bound Polymer Chains in Rubber Reinforcement

The addition of nanofillers to rubber matrices is a powerful route to improve the mechanical properties. Here, we focus on a molecular understanding of basic mechanisms that are important for the reinforcement in rubbers. The key role in this process is ascribed to bound rubber (BR) that engages with the matrix as well as with adjacent nanofillers. To date, this understanding has been impeded by the lack of experimental tools to directly probe the BR chains buried in a polymer matrix composed of the same polymer. To tackle this challenge, we combine neutron scattering/spectroscopy techniques with isotope-labeling and molecular dynamics simulations. The system is a simplified carbon-black-filled polybutadiene. The combined experimental and computational results provide new insights into the local structural and dynamical heterogeneities of BR chains and their interactions with the matrix polymer, highlighting (i) the structural partition of the bound chains into three components (i.e., trains, loops, and tails) and their fractions; (ii) their dynamical hierarchies, i.e., the trains that remain immobile on the filler surface, the loops that are fairly large and hence allow the interdigitation of matrix chains, and the tails with their unique characteristics to reach far out into the matrix and entangle with matrix chains. These multiple roles of the constituent components of the BR chains promote the formation of a well-developed adhesive polymer–filler interface, enhancing the elastic property of a filled rubber. Finally, the comprehensive understanding derived and validated by the model rubber will be translatable to many other polymer nanocomposites.

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Effect of Delta and Omicron Mutations on the RBD-SD1 Domain of the Spike Protein in SARS-CoV-2 and the Omicron Mutations on RBD-ACE2 Interface Complex

The receptor-binding domain (RBD) is the essential part in the Spike-protein (S-protein) of SARS-CoV-2 virus that directly binds to the human ACE2 receptor, making it a key target for many vaccines and therapies. Therefore, any mutations at this domain could affect the efficacy of these treatments as well as the viral-cell entry mechanism. We introduce ab initio DFT-based computational study that mainly focuses on two parts: (1) Mutations effects of both Delta and Omicron variants in the RBD-SD1 domain. (2) Impact of Omicron RBD mutations on the structure and properties of the RBD-ACE2 interface system. The in-depth analysis is based on the novel concept of amino acid-amino acid bond pair units (AABPU) that reveal the differences between the Delta and/or Omicron mutations and its corresponding wild-type strain in terms of the role played by non-local amino acid interactions, their 3D shapes and sizes, as well as contribution to hydrogen bonding and partial charge distributions. Our results also show that the interaction of Omicron RBD with ACE2 significantly increased its bonding between amino acids at the interface providing information on the implications of penetration of S-protein into ACE2, and thus offering a possible explanation for its high infectivity. Our findings enable us to present, in more conspicuous atomic level detail, the effect of specific mutations that may help in predicting and/or mitigating the next variant of concern.

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Modeling of Sagging for 3D Printed Layers During the Curing Process

Here, a printed layer of silica-enforced poly(dimethylsiloxane)-co-(diphenylsiloxane) is modeled as a two-phase system consisting of air and polymer with an interface set up during the printing process. The structural geometry changes mostly due to the action of surface tension, while all material properties are strongly temperature dependent. Polymer flow is described using equations of the extended Herschel–Bulkley model, with parameters strongly dependent on temperature and degree of curing. Parameters of the model are determined using flow sweep measurements and separate experiments with vertical structure sagging at different temperatures. The curing process is modeled using dependencies between the curing rate, degree of curing, and temperature obtained in studies by differential scanning calorimetry. The developed model is used for simulations of printed structure deformations with different initial and boundary conditions.

36 MATERIALS SCIENCE↗

A highly efficient and durable air electrode for intermediate-temperature reversible solid oxide cells

Solid oxide cells (SOCs) are considered the most efficient system for reversible conversion between chemical and electrical energy, thus having potential to be an attractive technology for a sustainable energy future. To achieve high round-trip efficiency, highly efficient and durable air electrode materials are needed to minimize energy loss associated with oxygen reduction reaction (ORR) and oxygen evolution reaction (OER). Here we report a bi-functional air electrode material, PrBa 0.9 Co 1.96 Nb 0.04 O 5+δ , demonstrating outstanding electrochemical performance (e.g., achieving peak power densities of over 1.5 and 1 W cm –2 , respectively, for Gd 0.1 Ce 0.9 O 1.95 and BaZr 0.1 Ce 0.7 Y 0.1 Yb 0.1 O 3-δ based fuel cells at 600 °C) while maintaining excellent stability (e.g., having a degradation rate of 40 mV per 1,000 h for H 2 O electrolysis cells). Finally, the excellent property of the new electrode is attributed to the improved stability from Nb doping and the enhanced electrocatalytic activity from tuning Ba deficiency, as confirmed by experimental results and computational analysis.

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Assembly of short amphiphilic peptoids into nanohelices with controllable supramolecular chirality

Abstract A long-standing challenge in bioinspired materials is to design and synthesize synthetic materials that mimic the sophisticated structures and functions of natural biomaterials, such as helical protein assemblies that are important in biological systems. Herein, we report the formation of a series of nanohelices from a type of well-developed protein-mimetics called peptoids. We demonstrate that nanohelix structures and supramolecular chirality can be well-controlled through the side-chain chemistry. Specifically, the ionic effects on peptoids from varying the polar side-chain groups result in the formation of either single helical fiber or hierarchically stacked helical bundles. We also demonstrate that the supramolecular chirality of assembled peptoid helices can be controlled by modifying assembling peptoids with a single chiral amino acid side chain. Computational simulations and theoretical modeling predict that minimizing exposure of hydrophobic domains within a twisted helical form presents the most thermodynamically favorable packing of these amphiphilic peptoids and suggests a key role for both polar and hydrophobic domains on nanohelix formation. Our findings establish a platform to design and synthesize chiral functional materials using sequence-defined synthetic polymers.

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