Number Of Atoms Research Articles

Machine Learning-Assisted Precision Manufacturing of Atom Qubits in Silicon.

Donor-based qubits in silicon, manufactured using scanning tunneling microscope (STM) lithography, provide a promising route to realizing full-scale quantum computing architectures. This is due to the precision of donor placement, long coherence times, and scalability of the silicon material platform. The properties of multiatom quantum dot qubits, however, depend on the exact number and location of the donor atoms within the quantum dots. In this work, we develop machine learning techniques that allow accurate and real-time prediction of the donor number at the qubit site during STM patterning. Machine learning image recognition is used to determine the probability distribution of donor numbers at the qubit site directly from STM images during device manufacturing. Models in excess of 90% accuracy are found to be consistently achieved by mitigating overfitting through reduced model complexity, image preprocessing, data augmentation, and examination of the intermediate layers of the convolutional neural networks. The results presented in this paper constitute an important milestone in automating the manufacture of atom-based qubits for computation and sensing applications.

Investigation on interfacial compound growth kinetics in Sn-0.7Cu/Cu solder joint and mechanism analysis: Experiments and molecular dynamics simulations

Herein, the interfacial compound growth kinetics and corresponding mechanisms in Sn-0.7Cu/Cu solder joint at aging stage were investigated using both experiments and molecular dynamics simulations. The research results indicate that, the growth rates of interfacial IMCs (Cu6Sn5 IMC and Cu3Sn IMC) are affected by the aging temperature severely, the higher aging temperature leads to the larger growth kinetics for both Cu6Sn5 IMC and Cu3Sn IMC. At aging stage, Cu substrate continuously supplies Cu3Sn IMC with Cu atoms. Those Cu atoms diffuse across Cu3Sn IMC to the Cu3Sn/Cu6Sn5 interface and react with Sn atoms diffused from the Sn-based solder to form new Cu3Sn grains growing towards Cu6Sn5 IMC, and the main crystal orientations are (100), (42–1), and (3−10). As the grain boundary diffusion rate of Cu atoms in Cu3Sn IMC determines the CuSn reaction rate (new Cu3Sn grains formation rate) on Cu3Sn/Cu6Sn5 interface, the growth of Cu3Sn IMC is driven by grain boundary diffusion, which is manifested by a growth index n near to 0.3. Meanwhile, the rod-like Cu6Sn5 IMC preferentially grows into Sn-based solder attributed to the large number of Cu atoms provided by Cu3Sn IMC, which can diffuse to the top of Cu6Sn5 IMC and reacts with Sn-based solder. While when Cu6Sn5 IMC is thick enough, Cu atoms cannot reach to the top of Cu6Sn5 IMC anymore, but diffuse laterally within the Cu6Sn5 grains, resulting in the widening of scallop-like Cu6Sn5 IMCs. As the thickening of Cu6Sn5 IMC is caused by the growth of the existing Cu6Sn5 grains, the diffusion of Cu and Sn atoms in Cu6Sn5 grains plays a decisive role. Therefore, the growth of Cu6Sn5 IMC is driven by bulk diffusion, which is manifested by a growth index n near to 0.5.

Student Translations of the Symbolic Level of Chemistry

The aim of the study was to explore students’ own translation of the symbolic level of a chemical reaction, including the information provided with the use of coefficients, indices, and signs, as well as the preservation of atoms. Students were asked to translate the symbolic level of the combustion of methane with the use of clay modelling. The students had to make active choices regarding the size, shape, two- or three-dimensional structure, and the number of atoms in the molecules included in the reaction using modelling clay. The analysis followed the three levels of analysis as presented by Hedegaard. The results highlight the variations in students’ answers and show the importance of investigating unrestricted translations of the symbolic level of chemistry. Including clay modelling in the educational process is helpful for both educators and students, as it fosters comprehension of underlying processes and enhances awareness of substance structure and atom redistribution across various substances.

Probing the Limit of the Number of Saturated Atoms for Achieving Hyperconjugative Aromaticity.

Aromaticity is a fundamental concept in organic chemistry. Hyperconjugative aromaticity, also known as hyperconjugation-induced aromaticity, has evolved from its origin from main group substituents to transition metal analogues, establishing itself as an important category of aromaticity. Additionally, aromatic compounds comprising two sp3-carbon atoms have recently been reported both experimentally and computationally. However, what is the maximum number of sp3-hybridized atoms needed to maintain hyperconjugative aromaticity? Here, we report that hyperconjugative aromaticity can be achieved in hexa-substituted indoliums and octa-substituted pyrroliums, possessing three-five sp3-hybridized carbon/nitrogen atoms by means of density functional theory (DFT) calculations. The aromaticity was confirmed by using various aromaticity indices, i.e., NICS, MCI, and EDDB. Notably, the strong electron-donating ability and aurophilicity of Au(I) substituents play a pivotal role in maintaining the aromaticity and structural integrity. In addition, increasing the number of hyperconjugative centers will decrease the aromaticity in these five-membered rings. Our findings highlight the significance of transition metal substituents in hyperconjugative aromaticity and offer a novel approach for designing aromatic organometallics.

Massively parallel free energy calculations for in silico affinity maturation of designed miniproteins.

Computational protein design efforts continue to make remarkable advances, yet the discovery of high-affinity binders typically requires large-scale experimental screening of site-saturated mutant (SSM) libraries. Here, we explore how massively parallel free energy methods can be used for in silico affinity maturation of de novo designed binding proteins. Using an expanded ensemble (EE) approach, we perform exhaustive relative binding free energy calculations for SSM variants of three miniproteins designed to bind influenza A H1 hemagglutinin by Chevalier et al. (2017). We compare our predictions to experimental ΔΔ G values inferred from a Bayesian analysis of the high-throughput sequencing data, and to state-of-the-art predictions made using the Flex ddG Rosetta protocol. A systematic comparison reveals prediction accuracies around 2 kcal/mol, and identifies net charge changes, large numbers of alchemical atoms, and slow side chain conformational dynamics as key contributors to the uncertainty of the EE predictions. Flex ddG predictions are more accurate on average, but highly conservative. In contrast, EE predictions can better classify stabilizing and destabilizing mutations. We also explored the ability of SSM scans to rationalize known affinity-matured variants containing multiple mutations, which are non-additive due to epistatic effects. Simple electrostatic models fail to explain non-additivity, but observed mutations are found at positions with higher Shannon entropies. Overall, this work suggests that simulation-based free energy methods can provide predictive information for in silico affinity maturation of designed miniproteins, with many feasible improvements to the efficiency and accuracy within reach.

Semiclassical spectra of the single- and two-photon Tavis-Cummings models

We obtain explicit analytical expressions for the energy spectra of the resonant single- and two-photon Tavis-Cummings models in the asymptotic limit of a large number of atoms, A≫1, and a large number of total excitations, N≫1. We show that both the spectral singularities in the regime N/A∼1 and the equidistant spectra in the regime N/A≫1 can be accurately described in the semiclassical framework.

Anisotropic Effects in Local Anodic Oxidation Nanolithography on Silicon Surfaces: Insights from ReaxFF Molecular Dynamics.

Fully understanding the anisotropic effect of silicon surface orientations in local anodic oxidation (LAO) nanolithography processes is critical to the precise control of oxide quality and rate. This study used ReaxFF MD simulations to reveal the surface anisotropic effects in the LAO through the analysis of adsorbed species, atomic charge, and oxide growth. Our results show that the LAO behaves differently on silicon (100), (110), and (111) surfaces. Specifically, the application of an electric field significantly increases the quantity of surface-adsorbed -OH2 while reducing -OH on the (111) surface, and results in a higher charge on a greater number of Si atoms on the (100) surface. Moreover, the quantity of surface-adsorbed -OH plays a pivotal role in influencing the oxidation rate, as it directly correlates with an increased formation rate of Si-O-Si bonds. During bias-induced oxidation, the (111) surface appears with a high initial oxidation rate among three surfaces, while the (110) surface underwent increased oxidation at higher electric field strengths. This conclusion is based on the analysis of the evolution of Si-O-Si bond number, surface elevation, and oxide thickness. Our findings align well with prior theoretical and experimental studies, providing deeper insights and clear guidance for the fabrication of high-performance nanoinsulator gates using LAO nanolithography.

Odd-even trends in the series of new bis(α,ω-alkanediamine)dibromocadmium(II) coordination polymers: Crystal structure and thermal decomposition

In this paper, organic-inorganic coordination polymers of the CdBr2(H2N-(CH2)n-NH2) general formula, where n = 4 – 10 and 12, were studied. All the materials were synthesized as very fine powders from metal salt and diamine solutions following an analogous simple procedure. Scanning electron microscopy (SEM) images and recorded powder X-ray diffraction patterns (PXRD) allowed for the assessment of the purity and crystallinity of the products. Based on the collected diffraction data, lattice parameters and symmetry were determined. For five of the synthesized compounds (n = 4, 6, 7, 8, and 12) that were of relatively high purity and sufficient crystallinity, crystal structure models were determined and refined. It was found that the structure symmetry depends on the parity of the number of carbon atoms in the diamine molecules. Structures of the investigated compounds belonging to the even series are centrosymmetric while the ones from the odd series are not (P21 space group). Structures’ symmetry of compounds based on even diamines decreases from P2/m to P1¯ with increasing length of the organic molecules. Diamine molecules are aligned parallel to the diagonals of the (010) faces of the unit cell and there is an almost perfectly linear correlation between the value of a lattice parameter and the number of C atoms. There are, however, separate trends for even or odd series. Differential scanning calorimetry (DSC) and non-ambient PXRD measurements provided information about the thermal decomposition of the materials. The temperature of decomposition decreases with the growing length of diamine molecules and achieves the lowest value (176 °C, 449 K) for the compound with 1,12-diaminododecane (the longest diamine among the studied ones) while the sample with 1,4-diaminobutane is the most stable one (up to around 284 °C, 557 K). The studied compounds also show odd-even separate trends concerning the decomposition temperature. The compounds with even diamines start to decompose at relatively higher temperatures than the ones belonging to the odd series.

Spin Polarization Enhances the Catalytic Activity of Monolayer MoSe2 for Oxygen Reduction Reaction.

The key factors in achieving high energy efficiency for proton exchange membrane fuel cells are reducing overpotential and increasing the oxygen reduction rate. Based on first-principles calculations, we induce H atom adsorption on 4 × 4 × 1 monolayer MoSe2 to induce spin polarization, thereby improving the catalytic performance. In the calculation of supercells, the band unfolding method is used to address the band folding effect in doped systems. Furthermore, it is evident from analyzing the unique energy band configuration of MoSe2 that a higher valley splitting value has better catalytic effects on the oxygen reduction reaction. We believe that the symmetries of the distinct adsorption site result in different overpotentials. In addition, when an even number of hydrogen atoms is adsorbed, the monolayer MoSe2 has no spin polarization. The spin can affect the electron transfer process and alter the hybrid energy with the reaction products, thereby regulating its catalytic performance.

Dynamical investigation of NinAgm (n + m = 147, 309, 561) nanoalloys with core–shell orderings

ABSTRACT The structures and dynamical properties of core–shell bimetallic Ni-Ag nanoalloys varying with different sizes and compositions have been studied using Monte Carlo (MC) and Molecular Dynamic (MD) simulations. We have considered the compositions in which the size of the core increases while the total number of atoms is fixed. In this sense, two (Ni13Ag134, Ni55Ag92), three (Ni13Ag296, Ni55Ag254, Ni147Ag162) and four (Ni13Ag548, Ni55Ag506, Ni147Ag414 and Ni309Ag252) compositions were considered for 147, 309 and 561 atoms, respectively. Highly symmetric Mackay icosahedral structures with centred symmetric cores appear for these specific sizes and compositions. Also, smaller Ni atoms tend to occupy the core and Ag atoms prefer to segregate to the surface of the nanoalloy due to its lower surface and cohesive energy. Then, the lowest energy structures obtained by Basin Hopping MC simulations were used as initial configurations for melting simulations. The transitions between different chemical ordering patterns with increasing temperature are possible in these systems while they are still in the solid state. Although there are clear differences in the melting process of the compositions with increasing size of the core, for all cases, surface melting occurs indicating that the Ag shell melts before the inner Ni core.

An Efficient Sparse Recovery STAP Algorithm for Airborne Bistatic Radars Based on Atomic Selection under the Bayesian Framework

The traditional sparse recovery (SR) space-time adaptive processing (STAP) algorithms are greatly affected by grid mismatch, leading to poor performance in airborne bistatic radar clutter suppression. In order to address this issue, this paper proposes an SR STAP algorithm for airborne bistatic radars based on atomic selection under the Bayesian framework. This method adopts the idea of atomic selection for the process of Bayesian inference, continuously evaluating the contribution of atoms to the likelihood function to add or remove atoms, and then using the selected atoms to estimate the clutter support subspace and perform sparse recovery in the clutter support subspace. Due to the inherent sparsity of clutter signals, performing sparse recovery in the clutter support subspace avoids using a massive number of atoms from an overcomplete space-time dictionary, thereby greatly improving computational efficiency. In airborne bistatic radar scenarios where significant grid mismatch exists, this method can mitigate the performance degradation caused by grid mismatch by encrypting grid points. Since the sparse recovery is performed in the clutter support subspace, encrypting grid points does not lead to excessive computational burden. Additionally, this method integrates out the noise term under a new hierarchical Bayesian model, preventing the adverse effects caused by inaccurate noise power estimation during iterations in the traditional SR STAP algorithms, further enhancing its performance. Our simulation results demonstrate the high efficiency and superior clutter suppression performance and target detection performance of this method.

Spatial heterogeneity, sediment-water exchange, and diffusion mechanisms of organophosphate esters from river to coastal aquatic system in a typical economic circle of northern China

Organophosphate esters (OPEs) have proven to be pervasive in aquatic environments globally. However, understanding their partitioning behavior and mechanisms at the sediment-water interface remains limited. This study elucidated the spatial heterogeneity, interfacial exchange, and diffusion mechanisms of 14 OPEs (∑14OPEs) from river to coastal aquatic system. The transport tendencies of OPEs at the sediment-water interface were quantitatively assessed using fugacity methods. The total ∑14OPEs concentrations in water and sediments ranged from 154 ng/L to 528 ng/L and 2.41 ng/g dry weight (dw) to 230 ng/g dw, respectively. This result indicated a descending spatial tendency with moderate variability. OPE distribution was primarily influenced by temperature, pH, and dissolved oxygen levels. As the carbon atom number increased, alkyl and chlorinated OPEs transitioned from diffusion towards the aqueous phase to equilibrium. In contrast, aryl OPEs and triphenylphosphine oxide, which had equivalent carbon atom counts, maintained equilibrium throughout. Diffusion trends of individual OPE congener at the sediment-water interface varied at the same total organic carbon contents (foc). As the foc increased, the fugacity fraction values for all OPE homologs showed a declining trend. The distinct molecular structure of each OPE monomer might lead to unique diffusive behaviors at the sediment-water interface. Higher soot carbon content had a more pronounced effect on the distribution patterns of OPEs. The sediment-water distribution of OPEs was primarily influenced by total organic carbon, sediment particle size, dry density, and moisture content. OPEs displayed the highest sensitivity to fluctuations in ammonium and dissolved organic carbon. This study holds significant scientific and theoretical implications for elucidating the interfacial transport and driving forces of OPEs and comprehending their fate and endogenous release in aquatic ecosystems.

Theoretical study of the effects of surface Cu coordination environment on CO2 hydrogenation to CH3OH

The coordination environment of Cu (the coordination number and arrangement of surface atoms) plays an important role in CO2 hydrogenation to CH3OH. Compared with the extensive studies of the effects of coordination number, the comprehensive effects of coordination number and arrangement of surface atoms were seldom explored in literature. To unravel the effects of surface Cu coordination environment on CO2 hydrogenation to CH3OH, the adsorption and reaction behaviors of H2 and CO2 on Cu(111), (100), (110) and (211) with different coordination numbers and arrangement of surface Cu were systematically calculated by density functional theory (DFT) and kinetic Monte Carlo (kMC) simulation. It was found that the adsorption energies of intermediates in CO2 hydrogenation on Cu surfaces increase with the decrease of coordination number. When the Cu coordination numbers are similar, the charge density on the open surface derived from the different atom arrangement becomes larger and leads to stronger interaction with intermediates than that on the compact one. DFT calculation and kMC simulation indicate that methanol formation pathway follows CO2*→HCOO*→HCOOH*→H2COOH*→H2CO*→CH3O*→CH3OH* on four Cu facets; CO formation is via CO2 direct dissociation on Cu(111), (100) and (110) but COOH* dissociation on (211). The low-coordinated surface Cu with more openness on Cu(211) is the highly active site for CO2 hydrogenation to CH3OH with high turnover of frequency (3.71 × 10−4 s−1) and high selectivity (87.17 %) at 600 K, PCO2 = 7.5 atm and PH2 = 22.5 atm, which is much higher than those on Cu(111), (100) and (110). This work unravels the effects of coordination environment on CO2 hydrogenation at the molecular level and provides an important insight into the design and development of catalysts with high performance in CO2 hydrogenation to CH3OH.

Dataset for quantum-mechanical exploration of conformers and solvent effects in large drug-like molecules

We here introduce the Aquamarine (AQM) dataset, an extensive quantum-mechanical (QM) dataset that contains the structural and electronic information of 59,783 low-and high-energy conformers of 1,653 molecules with a total number of atoms ranging from 2 to 92 (mean: 50.9), and containing up to 54 (mean: 28.2) non-hydrogen atoms. To gain insights into the solvent effects as well as collective dispersion interactions for drug-like molecules, we have performed QM calculations supplemented with a treatment of many-body dispersion (MBD) interactions of structures and properties in the gas phase and implicit water. Thus, AQM contains over 40 global and local physicochemical properties (including ground-state and response properties) per conformer computed at the tightly converged PBE0+MBD level of theory for gas-phase molecules, whereas PBE0+MBD with the modified Poisson-Boltzmann (MPB) model of water was used for solvated molecules. By addressing both molecule-solvent and dispersion interactions, AQM dataset can serve as a challenging benchmark for state-of-the-art machine learning methods for property modeling and de novo generation of large (solvated) molecules with pharmaceutical and biological relevance.

The alloyed cementite (Fe–Ni–Cr)3C: Local environment, atomic magnetic moments, and magnetization from DFT calculation

The alloying element added to carbon steel to enhance its properties also penetrates Fe3C cementite particles, altering their properties and influencing the steel product through them. This is why the impact of alloying elements on cementite has been extensively studied. Ni and Cr exhibit opposing behavior in cementite, so cementite doped with Ni and Cr is investigated using DFT calculations. The data obtained for total energy, lattice, magnetization, local magnetic moments at metal atoms, and their nearest environment are compared to experimental magnetic data for Ni and Cr-alloyed cementite. The relationship between Fe atom magnetic moments and their nearest environment is discussed in comparison between Cr and Ni doping. Decrease in magnetization with Ni and Cr content is attributed to 1) replacement of a larger Fe magnetic moment (mFe = 1.9–2.0 μB) with a smaller or even negative moment (mNi = 0.2–0.5 μB, mCr = −0.3 to −1.0 μB); 2) a decrease in the average Fe moment with the number of Cr atoms in the nearest environment; and 3) a strong dependence of the Curie temperature on Cr content in Cr-doped cementite.

The Reconstruction of Pt(001) Surface and the Shell-Like Reconstruction of the Vicinal Pt(001) Surfaces Revealed by Neural Network Potential.

In this work, a highly accurate neural network potential (NNP) is presented, named PtNNP, and the exploration of the reconstruction of the Pt(001) surface and its vicinal surfaces with it. Contrary to the most accepted understanding of the Pt(001) surface reconstruction, the study reveals that the main driving force behind Pt(001) quasi-hexagonal reconstruction is not the surface stress relaxation but the increased coordination number of the surface atoms resulting in stronger intralayer binding in the reconstructed surface layer. In agreement with experimental observations, the optimized supercell size of the reconstructed Pt(001) surface contains (5×20) unit cells. Surprisingly, the reconstruction of the vicinal Pt(001) surfaces leads to a smooth shell-like surface layer covering the whole surface and diminishing sharp step edges.

Orbital magnetic susceptibility of zigzag carbon nanobelts: a tight-binding study

The magnetic properties of a circular graphene nanoribbon (carbon belt) in a magnetic field parallel to its central axis is studied using a tight-binding model. Orbital magnetic susceptibility is calculated using an analytical expression of the energy eigenvalues as a function of the magnetic flux density for any size, and its temperature dependence is considered. In the absence of electron hopping parallel to the magnetic field, the orbital magnetic susceptibility diverges at absolute zero if the chemical potential is zero and the number of atoms is a multiple of four. As the temperature increases, the magnitude of susceptibility decreases according to the power law, whose exponent depends on the size. In the presence of electron hopping parallel to the magnetic field, the divergence of the susceptibility near absolute zero disappears, and the sign changes with the transfer integral parallel to the magnetic field and the temperature.

Photoinduced Phase Transitions of Imine-Based Liquid Crystal Dimers with Twist-Bend Nematic Phases.

Photoisomerizable molecules in liquid crystals (LCs) allow for photoinduced phase transitions, facilitating applications in a wide variety of photoresponsive materials. In contrast to the widely investigated azobenzene structure, research on the photoinduced phase-transition behavior of imine-based LCs is considerably limited. We herein report the thermal and photoinduced phase-transition behaviors of photoisomerizable imine-based LC dimers with twist-bend nematic (NTB) phases. We synthesize two homologous series of ester- and thioether-linked N-(4-cyanobenzylidene)aniline-based bent-shaped LC dimers with an even number of carbon atoms (n = 2, 4, 6, 8, and 10) in the central alkylene spacers, namely, CBCOOnSBA(CN) and CBOCOnSBA(CN), possessing oppositely directed ester linkages, C=OO and OC=O, respectively. Their thermal phase-transition behavior is examined using polarizing optical microscopy and differential scanning calorimetry. All dimers form a monotropic NTB phase below the temperature of the conventional nematic (N) phase upon cooling. Remarkably, the NTB phases of CBCOOnSBA(CN) (n = 2, 4, 6, and 8) and CBOCOnSBA(CN) (n = 6 and 8) supercool to room temperature and vitrify without crystallization. In addition, the phase-transition temperatures and entropy changes of CBCOOnSBA(CN) are lower than those of CBOCOnSBA(CN) at the same n. Under UV light irradiation, the NTB and N phases transition to the N and isotropic phases, respectively, and reversibly return to their initial LC phases when the UV light is turned off.

Velocity selective multiple two-photon dark and bright resonances in Potassium vapor

We report the observation of two additional sub-natural line width quantum interferences in the D 2 manifold of 39 K vapor, in addition to the usual single Electromagnetically Induced Transparency (EIT) peak. In a typical three level Λ-type system, only one EIT peak is observed. However, here we report observation of two additional line shapes riding on top of the absorption profile. The fact that the hyperfine splitting is smaller than the Doppler width in 39 K allows the probe and control beams to swap their transition pathways in different velocity groups of atoms even when their frequencies are kept constant. Our observations are in striking contrast to standard EIT measurements. These findings are in quantitative agreement with density matrix formalism taking into account velocity-selective two-photon resonances. Owing to the favorably low ground hyperfine splitting (Δ hf ) in 39 K, which allows a significantly large number of atoms with a Doppler shift greater than or equal to the Δ hf , the strength of these additional resonances is strong compared to that of other alkali atoms such as 87 Rb, 133 Cs where these resonances can not be observed. The control photon detuning to atomic transition captures the nature of the coherence; therefore an unusual phenomenon of conversion from perfect transparency to enhanced absorption of the probe photon is observed and explained by utilizing the adiabatic elimination of the excited state in the Master equation. Controlling such dark and bright resonances leads to new applications in quantum technologies such as frequency-offset laser stabilization and long-lived quantum memory.

Odd-Even Alkyl Chain Effects on the Structure and Charge Carrier Transport of Two-Dimensional Sn-Based Perovskite Semiconductors.

Oscillations in the chemical or physical properties of materials, composed of an odd or even number of connected repeating methylene units, are a well-known phenomenon in organic chemistry and materials science. So far, such behavior has not been reported for the important class of materials, perovskite semiconductors. This work reports a distinct odd-even oscillation of the molecular structure and charge carrier transport properties of phenylalkylammonium two-dimensional (2D) Sn-based perovskites in which the alkyl chains in the phenylalkylammonium cations contain varying odd and even carbon numbers. Density functional theory calculations and grazing-incidence wide-angle X-ray scattering characterization reveal that perovskites with organic ligands containing an alkyl chain with an odd number of carbon atoms display a disordered crystal lattice and tilted inorganic octahedra accompanied by reduced mobilities. In contrast, perovskites with cations of an even number of carbon atoms in the alkyl chain form more ordered crystal structures, resulting in improved charge carrier mobilities. Our findings disclose the importance of minor changes in the molecular conformation of organic cations have an effect on morphology, photophysical properties, and charge carrier transport of 2D layered perovskites, showcasing alkyl chain engineering of organic cations to control key properties, of layered perovskite semiconductors.