Modulation of physico-chemical and technofunctional properties of quinoa protein isolate: Effect of precipitation acid

The typically low solubility and gelation capacity of plant proteins can impose challenges in the design of high-quality plant-based foods. The acid used during the precipitation step of plant protein isolate extraction can influence protein functionality. Here, acetic acid and citric acid were used to extract quinoa protein isolate (QPI) from quinoa flour, as these acids are more kosmotropic than the commonly used HCl, promoting the stabilisation of the native protein structure. While proximate analysis showed that total protein was similar for the three isolates, precipitation with kosmotropic acids increased soluble protein, which correlated positively with gel strength. Microstructure analysis revealed that these gels contained a less porous protein network with lipid droplet inclusions. This study shows that the choice of precipitation acid offers an opportunity to tailor the properties of quinoa protein isolate for application, a strategy that is likely applicable to other plant protein isolates.

Coherent control from quantum commitment probabilities

We introduce a general definition of a quantum committor in order to clarify reaction mechanisms and facilitate control in processes where coherent effects are important. With a quantum committor, we generalize the notion of a transition state to quantum superpositions and quantify the effect of interference on the progress of the reaction. The formalism is applicable to any linear quantum master equation supporting metastability for which absorbing boundary conditions designating the reactant and product states can be applied. We use this formalism to determine the dependence of the quantum transition state on coherences in a polaritonic system and optimize the initialization state of a conical intersection model to control reactive outcomes, achieving yields of the desired state approaching 100%. In addition to providing a practical tool, the quantum committor provides a conceptual framework for understanding reactions in cases when classical intuitions fail.

Efficient exact exchange using Wannier functions and other related developments in planewave-pseudopotential implementation of RT-TDDFT

The plane-wave pseudopotential (PW-PP) formalism is widely used for the first-principles electronic structure calculation of extended periodic systems. The PW-PP approach has also been adapted for real-time time-dependent density functional theory (RT-TDDFT) to investigate time-dependent electronic dynamical phenomena. In this work, we detail recent advances in the PW-PP formalism for RT-TDDFT, particularly how maximally localized Wannier functions (MLWFs) are used to accelerate simulations using the exact exchange. We also discuss several related developments, including an anti-Hermitian correction for the time-dependent MLWFs (TD-MLWFs) when a time-dependent electric field is applied, the refinement procedure for TD-MLWFs, comparison of the velocity and length gauge approaches for applying an electric field, and elimination of long-range electrostatic interaction, as well as usage of a complex absorbing potential for modeling isolated systems when using the PW-PP formalism.

Surface control in the adsorption of tebuthiuron on modified silver surfaces tracked by surface-enhanced Raman scattering spectroscopy

The vibrational assignment of the Raman and surface-enhanced Raman scattering (SERS) spectra of the herbicide tebuthiuron (TBH) was accomplished, which allowed unprecedented propositions for adsorption geometries on the surface of silver nanoparticles (AgNP). Ascribed SERS features allowed suggesting that the adsorption occurred through nitrogen atoms of thiadiazole group, since intense band shift assigned to ring mode was marking of the coordination with the metallic surface. AgNP were treated with different surface modifiers that leaded to substantial changes in TBH adsorption geometries. Spectral changes, as the enhancement of out-of-plane ring modes, were indicative of the presence of tilted thiadiazole geometries in relation to the silver surface. Density Functional Theory (DFT) calculations from TBH molecules, in isolation and in interaction with ten-atom cluster of silver leaded to obtain theoretical spectra that gave support to interpret experimental Raman and SERS spectra.

Generating synthetic signaling networks for in silico modeling studies

Predictive models of signaling pathways have proven to be difficult to develop. Traditional approaches to developing mechanistic models rely on collecting experimental data and fitting a single model to that data. This approach works for simple systems but has proven unreliable for complex systems such as biological signaling networks. Thus, there is a need to develop new approaches to create predictive mechanistic models of complex systems. To meet this need, we developed a method for generating artificial signaling networks that were reasonably realistic and thus could be treated as ground truth models. These synthetic models could then be used to generate synthetic data for developing and testing algorithms designed to recover the underlying network topology and associated parameters. We defined the reaction degree and reaction distance to measure the topology of reaction networks, especially to consider enzymes. To determine whether our generated signaling networks displayed meaningful behavior, we compared them with signaling networks from the BioModels Database. This comparison indicated that our generated signaling networks had high topological similarities with BioModels signaling networks with respect to the reaction degree and distance distributions. In addition, our synthetic signaling networks had similar behavioral dynamics with respect to both steady states and oscillations, suggesting that our method generated synthetic signaling networks comparable with BioModels and thus could be useful for building network evaluation tools.

Coupling plasmon and catalytic-active hotspots of Au@Pt core-satellite nanoparticles for in-situ spectroscopic observation of plasmon-promoted decarboxylation

Plasmon-induced hot carriers are a promising "active" energy source, attracting increasing attention for their potential applications in photocatalysis and photodetection. Here, we hybridize plasmonic Au spherical nanoparticles (SNPs) with catalytically active Pt nanocrystals to form Au@Pt core-satellite nanoparticles (CSNPs), which act as both an efficient catalyst for plasmon-promoted decarboxylation reaction and a robust surface-enhanced Raman scattering (SERS) substrate for plasmon-enhanced molecular spectroscopic detection. By regulating the coverage of Pt nanocrystals on the Au SNPs, we modulated the "hotspot" structures of the Au@Pt CSNPs to optimize the SERS detecting capability and catalytic decarboxylation performance. The coupling functionalities enable us with unique opportunities to in-situ SERS monitor universal reactions catalyzed by active catalysts (e.g. Pt, Pd) in the chemical industry in real-time. The decarboxylation rate of 4-mercaptophenylacetic acid was dynamically controlled by the surface catalytic decarboxylation step, following first-order overall reaction kinetics. Moreover, the reaction rate exhibited a strong correlation with the local field enhancement |E/E0|4 of the hotspot structure. This work provides spectroscopic insights into the molecule-plasmon interface under the plasmon-promoted catalytic reactions, guiding the rational design of the plasmonic interface of nanocatalysts to achieve desired functionalities.

Non-adiabatic dynamics of photoexcited cyclobutanone: Predicting structural measurements from trajectory surface hopping with XMS-CASPT2 simulations

Over the years, theoretical calculations and scalable computer simulations have complemented ultrafast experiments, as they offer the advantage of overcoming experimental restrictions and having access to the whole dynamics. This synergy between theory and experiment promises to yield a deeper understanding of photochemical processes, offering valuable insights into the behavior of complex systems at the molecular level. However, the ability of theoretical models to predict ultrafast experimental outcomes has remained largely unexplored. In this work, we aim to predict the electron diffraction signals of an upcoming ultrafast photochemical experiment using high-level electronic structure calculations and non-adiabatic dynamics simulations. In particular, we perform trajectory surface hopping with extended multi-state complete active space with second order perturbation simulations for understanding the photodissociation of cyclobutanone (CB) upon excitation at 200 nm. Spin-orbit couplings are considered for investigating the role of triplet states. Our simulations capture the bond cleavage after ultrafast relaxation from the 3s Rydberg state, leading to the formation of the previously observed primary photoproducts: CO + cyclopropane/propene (C3 products), ketene, and ethene (C2 products). The ratio of the C3:C2 products is found to be about 1:1. Within 700 fs, the majority of trajectories transition to their electronic ground state, with a small fraction conserving the initial cyclobutanone ring structure. We found a minimal influence of triplet states during the early stages of the dynamics, with their significance increasing at later times. We simulate MeV-ultrafast electron diffraction (UED) patterns from our trajectory results, linking the observed features with specific photoproducts and the underlying structural dynamics. Our analysis reveals highly intense features in the UED signals corresponding to the photochemical processes of CB. These features offer valuable insights into the experimental monitoring of ring opening dynamics and the formation of C3 and C2 photoproducts.

Complex potential energy surfaces with projected CAP technique: Vibrational excitation of N2

The projected complex absorbing potential (CAP) technique is one of the methods that allow one to extend the bound state methods for computing resonances' energies and widths. Here, we explore the accuracy of the potential energy curves generated with different electronic structure theory methods in combination with the projected CAP technique by considering resonant vibrational excitation (RVE) of N2 by electron impact as a model process. We report RVE cross sections computed using the boomerang model with potential energy curves obtained with CAP-based extended multistate complete active space perturbation theory (XMS-CASPT2) and equation of motion coupled-cluster method for electron attachment with single and double substitution (EOM-EA-CCSD) methods. We also compare potential energy curves computed with several electronic structure methods, including XMS-CASPT2, EOM-EA-CCSD, multireference configuration interaction with singles (MR-CIS) and singles and doubles (MR-CISD). A good agreement is observed between the experiment and simulated RVE cross sections obtained with the potential energy curves generated with XMS-CASPT2 and EOM-EA-CCSD methods, thus highlighting the potential of the projected CAP technique combined with accurate electronic structure methods for dynamical simulations of the processes that proceed through metastable electronic states.

Rational Tuning of the Concentration-independent Enrichment of Prion-like Domains in Stress Granules

Stress granules (SGs) are large ribonucleoprotein assemblies that form in response to acute stress in eukaryotes. SG formation is thought to be initiated by liquid-liquid phase separation (LLPS) of key proteins and RNA. These molecules serve as a scaffold for recruitment of client molecules. LLPS of scaffold proteins in vitro is highly concentration-dependent, yet biomolecular condensates in vivo contain hundreds of unique proteins, most of which are thought to be clients rather than scaffolds. Many proteins that localize to SGs contain low-complexity, prion-like domains (PrLDs) that have been implicated in LLPS and SG recruitment. The degree of enrichment of proteins in biomolecular condensates such as SGs can vary widely, but the underlying basis for these differences is not fully understood. Here, we develop a toolkit of model PrLDs to examine the factors that govern efficiency of PrLD recruitment to stress granules. Recruitment was highly sensitive to amino acid composition: enrichment in SGs could be tuned through subtle changes in hydrophobicity. By contrast, SG recruitment was largely insensitive to PrLD concentration at both a population level and single-cell level. These observations point to a model wherein PrLDs are enriched in SGs through either simple solvation effects or interactions that are effectively non-saturable even at high expression levels.

Accurately Modeling RNA Stem-Loops in an Implicit Solvent Environment

Ribonucleic acid (RNA) molecules can adopt a variety of secondary and tertiary structures in solution, with stem-loops being one of the more common motifs. Here, we present a systematic analysis of 15 RNA stem-loop sequences simulated with molecular dynamics simulations in an implicit solvent environment. Analysis of RNA cluster ensembles showed that the stem-loop structures can generally adopt the A-form RNA in the stem region. Loop structures are more sensitive, and experimental structures could only be reproduced with modification of CH···O interactions in the force field, combined with an implicit solvent nonpolar correction to better model base stacking interactions. Accurately modeling RNA with current atomistic physics-based models remains challenging, but the RNA systems studied herein may provide a useful benchmark set for testing other RNA modeling methods in the future.

Demethylation C-C coupling reaction facilitated by the repulsive Coulomb force between two cations

Carbon chain elongation (CCE) is normally carried out using either chemical catalysts or bioenzymes. Herein we demonstrate a catalyst-free approach to promote demethylation C-C coupling reactions for advanced CCE constructed with functional groups under ambient conditions. Accelerated by the electric field, two organic cations containing a methyl group (e.g., ketones, acids, and aldehydes) approach each other with such proximity that the energy of the repulsive Coulomb interaction between these two cations exceeds the bond energy of the methyl group. This results in the elimination of a methyl cation and the coupling of the residual carbonyl carbon groups. As confirmed by high-resolution mass spectrometry and isotope-labeling experiments, the C-C coupling reactions (yields up to 76.5%) were commonly observed in the gas phase or liquid phase, for which the mechanism was further studied using molecular dynamics simulations and stationary-point calculations, revealing deep insights and perspectives of chemistry.

Modelling intracellular transport in crowded environments: effects of motor association to cargos

In intracellular transports, motor proteins transport macromolecules as cargos to desired locations by moving on biopolymers such as microtubules. Recent experiments suggest that, while moving in crowded environments, cargos that can associate motor proteins during their translocation have larger run-length and association time compared to free motors. Here, we model the dynamics of a cargo that can associate at the most m free motors present on the microtubule track as obstacles to its motion. The proposed models display competing effects of association and crowding, leading to a peak in the run-length with the free-motor density. For m = 2 and 3, we show that this feature is governed by the largest eigenvalue of the transition matrix describing the cargo dynamics. In all the above cases, free motors are assumed to be present on the microtubule as stalled obstacles. We finally compare simulation results for the run-length for general scenarios where the free motors undergo processive motion in addition to binding and unbinding to or from the microtubule.

Plasmonic trimers designed as SERS-active chemical traps for subtyping of lung tumors

Plasmonic materials can generate strong electromagnetic fields to boost the Raman scattering of surrounding molecules, known as surface-enhanced Raman scattering. However, these electromagnetic fields are heterogeneous, with only molecules located at the 'hotspots', which account for ≈ 1% of the surface area, experiencing efficient enhancement. Herein, we propose patterned plasmonic trimers, consisting of a pair of plasmonic dimers at the bilateral sides and a trap particle positioned in between, to address this challenge. The trimer configuration selectively directs probe molecules to the central traps where 'hotspots' are located through chemical affinity, ensuring a precise spatial overlap between the probes and the location of maximum field enhancement. We investigate the Raman enhancement of the Au@Al2O3-Au-Au@Al2O3 trimers, achieving a detection limit of 10-14 M of 4-methylbenzenethiol, 4-mercaptopyridine, and 4-aminothiophenol. Moreover, single-molecule SERS sensitivity is demonstrated by a bi-analyte method. Benefiting from this sensitivity, our approach is employed for the early detection of lung tumors using fresh tissues. Our findings suggest that this approach is sensitive to adenocarcinoma but not to squamous carcinoma or benign cases, offering insights into the differentiation between lung tumor subtypes.

Transcription Factor Condensates Mediate Clustering of MET Regulon and Enhancement in Gene Expression

Some transcription factors (TFs) can form liquid-liquid phase separated (LLPS) condensates. However, the functions of these TF condensates in 3D genome organization and gene regulation remain elusive. In response to methionine (met) starvation, budding yeast TF Met4 and a few co-activators, including Met32, induce a set of genes involved in met biosynthesis. Here, we show that the endogenous Met4 and Met32 form co-localized puncta-like structures in yeast nuclei upon met depletion. Recombinant Met4 and Met32 form mixed droplets with LLPS properties in vitro. In relation to chromatin, Met4 puncta co-localize with target genes, and at least a subset of these target genes is clustered in 3D in a Met4-dependent manner. A MET3pr-GFP reporter inserted near several native Met4 binding sites becomes co-localized with Met4 puncta and displays enhanced transcriptional activity. A Met4 variant with a partial truncation of an intrinsically disordered region (IDR) shows less puncta formation, and this mutant selectively reduces the reporter activity near Met4 binding sites to the basal level. Overall, these results support a model where Met4 and co-activators form condensates to bring multiple target genes into a vicinity with higher local TF concentrations, which facilitates a strong response to methionine depletion.

Master equation modeling of water dissociation in small ionic water clusters: Ag+(H2O) n , n = 4-6

We model temperature-dependent blackbody infrared radiative dissociation (BIRD) rate coefficients of Ag+(H2O) n , n = 4-6, a system with loosely bound water molecules. We employ a master equation modeling (MEM) approach with consideration of absorption and emission of blackbody radiation, comparing single and multiple-well descriptions. The unimolecular dissociation rate coefficients are obtained using the Rice-Ramsperger-Kassel-Marcus (RRKM) theory, employing two approaches to model the sum of states in the transition state, the rigid activated complex (RAC) and the phase space limit (PSL) approach. A genetic algorithm is used to find structures of low-lying isomers for the kinetic modeling. We show that the multiple-well MEM approach with PSL RRKM in the All Wells and Transition States Are Relevant (AWATAR) variant provides a reliable description of Ag+(H2O) n BIRD, in agreement with previously published experimental data. Higher-lying isomers contribute significantly to the overall dissociation rate coefficient, underlying the importance of the multiple-well ansatz in which all isomers are treated on the same footing.

Direct Comparative Studies Revealing the Contribution of TADF Activity of Organic Emitters Towards Efficient Electrochemiluminescence

Electrochemiluminescence (ECL) featuring thermally activated delayed fluorescence (TADF) properties has attracted considerable interest, showcasing their potential for 100 % exciton harvesting, which marks a significant advancement in the realm of organic ECL. However, the challenge of elucidating the precise contribution of TADF to the enhanced ECL efficiency arises due to the lack of comparative studies of organic compounds with or without efficient TADF properties. In this study, we present four carbazole-benzonitrile molecules possessing similar chemical structures and comparable exchange energy (ΔEST). Despite their comparable properties, these compounds exhibited varying TADF efficiencies, warranting a closer examination of their underlying structural and electronic characteristics governing the optical properties. Consequently, intense ECL emission was only observed from 4CzBN with a remarkable TADF efficiency, underscoring the substantial difference in the ECL signal among molecules with comparable ΔEST and similar spectral properties but varying TADF activity.

Advances in mass spectrometry imaging for plant metabolomics-Expanding the analytical toolbox

Mass spectrometry imaging (MSI) has become increasingly popular in plant science due to its ability to characterize complex chemical, spatial, and temporal aspects of plant metabolism. Over the past decade, as the emerging and unique features of various MSI techniques have continued to support new discoveries in studies of plant metabolism closely associated with various aspects of plant function and physiology, spatial metabolomics based on MSI techniques has positioned it at the forefront of plant metabolic studies, providing the opportunity for far higher resolution than was previously available. Despite these efforts, profound challenges at the levels of spatial resolution, sensitivity, quantitative ability, chemical confidence, isomer discrimination, and spatial multi-omics integration, undoubtedly remain. In this Perspective, we provide a contemporary overview of the emergent MSI techniques widely used in the plant sciences, with particular emphasis on recent advances in methodological breakthroughs. Having established the detailed context of MSI, we outline both the golden opportunities and key challenges currently facing plant metabolomics, presenting our vision as to how the enormous potential of MSI technologies will contribute to progress in plant science in the coming years.

Single-Molecule Identification of the Isomers of a Lipidic Antibody Activator

Molecular structural elucidation can be accomplished by different techniques, such as nuclear magnetic resonance or X-ray diffraction. However, the former does not give information about the three-dimensional atomic arrangement, and the latter needs crystallizable solid samples. An alternative is direct, real-space visualization of the molecules by cryogenic scanning tunneling microscopy (STM). This technique is usually limited to thermally robust molecules because an annealing step is required for sample deposition. A landmark development has been the coupling of STM with electrospray deposition (ESD), which smooths the process and widens the scope of the visualization technique. In this work, we present the on-surface characterization of air-, light-, and temperature-sensitive rhamnopolyene with relevance in molecular biology. Supported by theoretical calculations, we characterize two isomers of this flexible molecule, confirming the potential of the technique to inspect labile, non-crystallizable compounds.

Inflammatory response of nanoparticles: Mechanisms, consequences, and strategies for mitigation

Numerous nano-dimensioned materials have been generated as a result of several advancements in nanoscale science such as metallic nanoparticles (mNPs) which have aided in the advancement of related research. As a result, several significant nanoscale materials are being produced commercially. It is expected that in the future, products that are nanoscale, like mNPs, will be useful in daily life. Despite certain benefits, widespread use of metallic nanoparticles and nanotechnology has negative effects and puts human health at risk because of their continual accumulation in closed biological systems, along with their complex and diverse migratory and transformation pathways. Once within the human body, nanoparticles (NPs) disrupt the body's natural biological processes and trigger inflammatory responses. These NPs can also affect the immune system by activating separate pathways that either function independently or interact with one another. Cytotoxic effects, inflammatory response, genetic material damage, and mitochondrial dysfunction are among the consequences of mNPs. Oxidative stress and reactive oxygen species (ROS) generation caused by mNPs depend upon a multitude of factors that allow NPs to get inside cells and interact with biological macromolecules and cell organelles. This review focuses on how mNPs cause inflammation and oxidative stress, as well as disrupt cellular signaling pathways that support these effects. In addition, possibilities and problems to be reduced are addressed to improve future research on the creation of safer and more environmentally friendly metal-based nanoparticles for commercial acceptance and sustainable use in medicine and drug delivery.

On the Topological Phase around Conical Intersections with Tamm-Dancoff Linear-Response Time-Dependent Density Functional Theory

Regions of nuclear-configuration space away from the Franck-Condon geometry can prove problematic for some electronic structure methods, given the propensity of such regions to possess conical intersections, i.e., (highly connected) points of degeneracy between potential energy surfaces. With the likelihood (perhaps even inevitability) for nonadiabatic dynamics simulations to explore molecular geometries in close proximity to conical intersections, it is vital that the performance of electronic structure methods is routinely examined in this context. In a recent paper [Taylor, J. T. J. Chem. Phys. 2023, 159, 214115.], the ability of linear-response time-dependent density functional theory within the adiabatic approximation (AA LR-TDDFT) to provide a proper description of conical intersections, in terms of their topology and topography, was investigated, with particular attention paid to conical intersections between two excited electronic states. For the same prototypical molecules, protonated formaldimine and pyrazine, we herein consider whether AA LR-TDDFT can correctly reproduce the topological phase accumulated by the adiabatic electronic wave function upon traversing a closed path around an excited-to-excited state conical intersection despite not using the appropriate quadratic-response nonadiabatic coupling vectors. Equally, we probe the ability of the ground-to-excited state intersection ring exhibited by AA LR-TDDFT in protonated formaldimine to give rise to a similar topological phase in spite of its incorrect dimensionality.

Effect of N Atom Substitution on Electronic Resonances: A 2D Photoelectron Spectroscopic and Computational Study of Anthracene, Acridine, and Phenazine Anions

The accommodation of an excess electron by polycyclic aromatic hydrocarbons (PAHs) has important chemical and technological implications ranging from molecular electronics to charge balance in interstellar molecular clouds. Here, we use two-dimensional photoelectron spectroscopy and equation-of-motion coupled-cluster calculations of the radical anions of acridine (C13H9N-) and phenazine (C12H8N2-) and compare our results for these species to those for the anthracene anion (C14H10-). The calculations predict the observed resonances and additionally find low-energy two-particle-one-hole states, which are not immediately apparent in the spectra, and offer a slightly revised interpretation of the resonances in anthracene. The study of acridine and phenazine allows us to understand how N atom substitution affects electron accommodation. While the electron affinity associated with the ground state anion undergoes a sizable increase with the successive substitution of N atoms, the two lowest energy excited anion states are not affected significantly by the substitution. The net result is that there is an increase in the energy gap between the two lowest energy resonances and the bound ground electronic state of the radical anion from anthracene to acridine to phenazine. Based on an energy gap law for the rate of internal conversion, this increased gap makes ground state formation progressively less likely, as evidenced by the photoelectron spectra.

Computational Investigation of the Potential and Limitations of Machine Learning with Neural Network Circuits Based on Synaptic Transistors

Synaptic transistors have been proposed to implement neuron activation functions of neural networks (NNs). While promising to enable compact, fast, inexpensive, and energy-efficient dedicated NN circuits, they also have limitations compared to digital NNs (realized as codes for digital processors), including shape choices of the activation function using particular types of transistor implementation, and instabilities due to noise and other factors present in analog circuits. We present a computational study of the effects of these factors on NN performance and find that, while accuracy competitive with traditional NNs can be realized for many applications, there is high sensitivity to the instability in the shape of the activation function, suggesting that, when highly accurate NNs are required, high-precision circuitry should be developed beyond what has been reported for synaptic transistors to date.

Wavelength-Dependent Activity of Oxygen Species in Propane Conversion on Rutile TiO2(110)

Photocatalytic oxidative dehydrogenation of propane (C3H8) into propene (C3H6) under mild conditions holds great potential in the chemical industry, but understanding how active species participate in C3H8 conversion remains a significant challenge. Here, the wavelength-dependent activities of bridging oxygen (Ob2-) and the Ti5c-bound oxygen adatom (OTi2-) of model rutile (R) TiO2(110) in C3H8 conversion have been investigated. Under 257 and 343 nm irradiation, hole-trapped OTi- and Ob- can abstract the hydrogen atom of C3H8, forming the CH3CH•CH3 radical and C3H6. However, the rate of C3H8 conversion with hole-trapped Ob- is strongly dependent on the wavelength, primarily producing the C3H7• radical. In the case of hole-trapped OTi-, C3H6 is the main product, which is nearly independent of wavelength. The differences in the wavelength-dependent activity and product selectivity are likely due to dynamic control rather than thermodynamic control. The result provides a deeper understanding of the dynamic processes involved in the conversion of light alkanes in TiO2 photocatalysis.

Anion Effect on the Excited-State Intramolecular Proton Transfer of 4'-N,N-Diethylamino-3-hydroxyflavone in Ionic Liquids

The excited-state intramolecular proton transfer (ESIPT) reaction of 4'-N,N,-diethylamino-3-hydroxyflavone (C2HF) was studied using time-resolved fluorescence measurements in ionic liquids (ILs) of various anions with a fixed cation (1-ethyl-3-methylimidazolium [C2mim]+). C2HF showed an ESIPT reaction from the normal excited state (N*; keto form) to the tautomer excited state (T*; enol form) where both states are emissive. The ESIPT rate and yield were obtained by analyzing the time-resolved fluorescence spectra measured using the optical Kerr gate method. Both the ESIPT rate and yield decreased with increasing hydrogen-bond accepting ability of the anion. According to density functional theory calculations, the complex formation energy between C2HF and the anion became significantly negative with increasing the hydrogen-bond accepting ability of anion. The pseudoequilibrium constant between N* and T* ([T*]/[N*]) in the electronic excited state decreased with increasing hydrogen-bond accepting ability of the anion, while it increased with increasing the alkyl-chain length of alkyl sulfonate. The excitation wavelength dependence of the ESIPT rate and yield was studied for C2HF in [C2mim][C6H13SO3]. The ESIPT yield decreased by nearly a factor of 2 with increasing excitation wavelength from 360 to 425 nm, although the change in the ESIPT rate was small. The solvation heterogeneity due to the alkyl chain in the anion was considered to be the reason for the excitation wavelength dependence.

Rare Events Sampling Methods for Quantum and Classical Ab Initio Molecular Dynamics

We provide an approach to sample rare events during classical ab initio molecular dynamics and quantum wavepacket dynamics. For classical AIMD, a set of fictitious degrees of freedom are introduced that may harmonically interact with the electronic and nuclear degrees of freedom to steer the dynamics in a conservative fashion toward energetically forbidden regions. A similar approach when introduced for quantum wavepacket dynamics has the effect of biasing the trajectory of the wavepacket centroid toward the regions of the potential surface that are difficult to sample. The approach is demonstrated for a phenol-amine system, which is a prototypical problem for condensed phase-proton transfer, and for model potentials undergoing wavepacket dynamics. In all cases, the approach yields trajectories that conserve energy while sampling rare events.

Expanding insights from in situ cryo-EM

The combination of cryo-electron tomography and subtomogram analysis affords 3D high-resolution views of biological macromolecules in their native cellular environment, or in situ. Streamlined methods for acquiring and processing these data are advancing attainable resolutions into the realm of drug discovery. Yet regardless of resolution, structure prediction driven by artificial intelligence (AI) combined with subtomogram analysis is becoming powerful in understanding macromolecular assemblies. Automated and AI-assisted data mining is increasingly necessary to cope with the growing wealth of tomography data and to maximize the information obtained from them. Leveraging developments from AI and single-particle analysis could be essential in fulfilling the potential of in situ cryo-EM. Here, we highlight new developments for in situ cryo-EM and the emerging potential for AI in this process.

Lewis Acid-Base Pairs: The Bonding Rule of Closed-Shell M···M' Interactions (M = HgII/PdII; M' = AgI/AuI)

Metallophilic interactions are the widespread interactions in multimetal clusters to orientate closed-shell metal self-assembly form linear, facet, or block clusters. The closed-shell metal cation does not have empty valence orbitals, but is able to attract each other. It is still a conundrum to understand the resource in balancing the strong Coulomb repulsion between two cations. Most traditional descriptions attribute the counterintuitive attractions to London dispersion, Pauli repulsions, and ambiguous orbital interactions. However, neither the dispersion nor the unsourced donor-acceptor interaction can be applied to explain the saturability and directionality in multimetal clusters, where the M···M' structure is the basic molecular unit. Here, we clarify the origination of the covalency in closed-shell metallophilic interactions based on the study of heterobimetallic compounds composed of d10-d8 species (AgI/AuI-PdII) and d10-d10 species (AgI/AuI-HgII) obtained from experiments. The inner d electrons not only participate in the metallophilic interactions but also show different Lewis acidity and basicity in the formation of M···M' structures. The present work not only provides us a novel covalent perspective to visualize the closed-shell M···M' interactions but also unveils the truth of metallophilic interactions.

Biospecific Chemistry for Covalent Linking of Biomacromolecules

Interactions among biomacromolecules, predominantly noncovalent, underpin biological processes. However, recent advancements in biospecific chemistry have enabled the creation of specific covalent bonds between biomolecules, both in vitro and in vivo. This Review traces the evolution of biospecific chemistry in proteins, emphasizing the role of genetically encoded latent bioreactive amino acids. These amino acids react selectively with adjacent natural groups through proximity-enabled bioreactivity, enabling targeted covalent linkages. We explore various latent bioreactive amino acids designed to target different protein residues, ribonucleic acids, and carbohydrates. We then discuss how these novel covalent linkages can drive challenging protein properties and capture transient protein-protein and protein-RNA interactions in vivo. Additionally, we examine the application of covalent peptides as potential therapeutic agents and site-specific conjugates for native antibodies, highlighting their capacity to form stable linkages with target molecules. A significant focus is placed on proximity-enabled reactive therapeutics (PERx), a pioneering technology in covalent protein therapeutics. We detail its wide-ranging applications in immunotherapy, viral neutralization, and targeted radionuclide therapy. Finally, we present a perspective on the existing challenges within biospecific chemistry and discuss the potential avenues for future exploration and advancement in this rapidly evolving field.

Singlet Fission in Pechmann Dyes: Planar Chromophore Design and Understanding

Singlet fission in organic chromophores holds the potential for enhancing photovoltaic efficiencies beyond the single-junction limit. The most basic requirement of a singlet fission material is that it has a large energy gap between its first singlet and triplet excited states. Identifying such compounds is not simple and has been accomplished either through computational screening or by subtle modifications of previously known fission materials. Here, we propose an approach that leverages ground and excited-state aromaticity combined with double-bond conformation to establish simple qualitative design rules for predicting fundamental optical properties without the need for computational modeling. By investigating two Pechmann dye isomers, we demonstrate that although their planarity and degree of charge transfer are similar, singlet fission is active in the isomer with a trans-conformation, while the cis-isomer exhibits greater favorability for polaronic processes, experimentally validated using ultrafast and electron spin resonance spectroscopy. Our results offer a new design perspective that provides a rational framework for tailoring optoelectronic systems to specific applications such as singlet fission or triplet-triplet annihilation.

Correlative single-molecule and structured illumination microscopy of fast dynamics at the plasma membrane

Total internal reflection fluorescence (TIRF) microscopy offers powerful means to uncover the functional organization of proteins in the plasma membrane with very high spatial and temporal resolution. Traditional TIRF illumination, however, shows a Gaussian intensity profile, which is typically deteriorated by overlaying interference fringes hampering precise quantification of intensities-an important requisite for quantitative analyses in single-molecule localization microscopy (SMLM). Here, we combine flat-field illumination by using a standard πShaper with multi-angular TIR illumination by incorporating a spatial light modulator compatible with fast super-resolution structured illumination microscopy (SIM). This distinct combination enables quantitative multi-color SMLM with a highly homogenous illumination. By using a dual camera setup with optimized image splitting optics, we achieve a versatile combination of SMLM and SIM with up to three channels. We deploy this setup for establishing robust detection of receptor stoichiometries based on single-molecule intensity analysis and single-molecule Förster resonance energy transfer (smFRET). Homogeneous illumination furthermore enables long-term tracking and localization microscopy (TALM) of cell surface receptors identifying spatial heterogeneity of mobility and accessibility in the plasma membrane. By combination of TALM and SIM, spatially and molecularly heterogenous diffusion properties can be correlated with nanoscale cytoskeletal organization and dynamics.

Explaining Conformational Diversity in Protein Families through Molecular Motions

Proteins play a central role in biological processes, and understanding their conformational variability is crucial for unraveling their functional mechanisms. Recent advancements in high-throughput technologies have enhanced our knowledge of protein structures, yet predicting their multiple conformational states and motions remains challenging. This study introduces Dimensionality Analysis for protein Conformational Exploration (DANCE) for a systematic and comprehensive description of protein families conformational variability. DANCE accommodates both experimental and predicted structures. It is suitable for analysing anything from single proteins to superfamilies. Employing it, we clustered all experimentally resolved protein structures available in the Protein Data Bank into conformational collections and characterized them as sets of linear motions. The resource facilitates access and exploitation of the multiple states adopted by a protein and its homologs. Beyond descriptive analysis, we assessed classical dimensionality reduction techniques for sampling unseen states on a representative benchmark. This work improves our understanding of how proteins deform to perform their functions and opens ways to a standardised evaluation of methods designed to sample and generate protein conformations.

Condensed Matter Systems Exposed to Radiation: Multiscale Theory, Simulations, and Experiment

This roadmap reviews the new, highly interdisciplinary research field studying the behavior of condensed matter systems exposed to radiation. The Review highlights several recent advances in the field and provides a roadmap for the development of the field over the next decade. Condensed matter systems exposed to radiation can be inorganic, organic, or biological, finite or infinite, composed of different molecular species or materials, exist in different phases, and operate under different thermodynamic conditions. Many of the key phenomena related to the behavior of irradiated systems are very similar and can be understood based on the same fundamental theoretical principles and computational approaches. The multiscale nature of such phenomena requires the quantitative description of the radiation-induced effects occurring at different spatial and temporal scales, ranging from the atomic to the macroscopic, and the interlinks between such descriptions. The multiscale nature of the effects and the similarity of their manifestation in systems of different origins necessarily bring together different disciplines, such as physics, chemistry, biology, materials science, nanoscience, and biomedical research, demonstrating the numerous interlinks and commonalities between them. This research field is highly relevant to many novel and emerging technologies and medical applications.

A differentiable Gillespie algorithm for simulating chemical kinetics, parameter estimation, and designing synthetic biological circuits

The Gillespie algorithm is commonly used to simulate and analyze complex chemical reaction networks. Here, we leverage recent breakthroughs in deep learning to develop a fully differentiable variant of the Gillespie algorithm. The differentiable Gillespie algorithm (DGA) approximates discontinuous operations in the exact Gillespie algorithm using smooth functions, allowing for the calculation of gradients using backpropagation. The DGA can be used to quickly and accurately learn kinetic parameters using gradient descent and design biochemical networks with desired properties. As an illustration, we apply the DGA to study stochastic models of gene promoters. We show that the DGA can be used to: (i) successfully learn kinetic parameters from experimental measurements of mRNA expression levels from two distinct E. coli promoters and (ii) design nonequilibrium promoter architectures with desired input-output relationships. These examples illustrate the utility of the DGA for analyzing stochastic chemical kinetics, including a wide variety of problems of interest to synthetic and systems biology.

Protein Condensate Atlas from predictive models of heteromolecular condensate composition

Biomolecular condensates help cells organise their content in space and time. Cells harbour a variety of condensate types with diverse composition and many are likely yet to be discovered. Here, we develop a methodology to predict the composition of biomolecular condensates. We first analyse available proteomics data of cellular condensates and find that the biophysical features that determine protein localisation into condensates differ from known drivers of homotypic phase separation processes, with charge mediated protein-RNA and hydrophobicity mediated protein-protein interactions playing a key role in the former process. We then develop a machine learning model that links protein sequence to its propensity to localise into heteromolecular condensates. We apply the model across the proteome and find many of the top-ranked targets outside the original training data to localise into condensates as confirmed by orthogonal immunohistochemical staining imaging. Finally, we segment the condensation-prone proteome into condensate types based on an overlap with biomolecular interaction profiles to generate a Protein Condensate Atlas. Several condensate clusters within the Atlas closely match the composition of experimentally characterised condensates or regions within them, suggesting that the Atlas can be valuable for identifying additional components within known condensate systems and discovering previously uncharacterised condensates.

Investigation of the exact spin channels in laser-induced spin dynamics in two mononuclear Cu(II) complexes

In the quest to harness the potential of nanospintronic applications, we analyze and investigate the spin channels for the ultrafast spin dynamics in mononuclear Cu2+(tdp)Cl2 (Cutdp) and Cu2+(tdp)Cl2·MeCN (Cutdp·MeCN) using a high-level ab initio many-body theory. In that spirit, we select two slightly different polymerizations arising from one parent complex. We establish the difference in magnetic behavior between the two complexes which arises solely from the geometrical differences. We calculate the static magnetic properties, such as the magnetic anisotropy of the complexes, which is analyzed by means of the magnetic moment of the ground state. The asymmetry of the core Cu-Cl-Cu-Cl axial plane unit is also reflected in the ground state absorption spectra of the two complexes. Comparisons with the experimental data are in good agreement with the exception of one peak in the theoretical calculations for each of the complexes, confirming the reliability of theoretical methods employed. A major finding in this work is the distinction between classical and coherent superpositions of Λ processes. We employ the selective blocking and retention (SBR) technique to find the unique path or paths for spin dynamic scenarios like spin flip and spin transfer. Additionally, we also present two different scenarios in which intermediate states are involved in spin dynamic processes, (i) classical superposition of Λ processes (i.e., there are many unique paths for transition, even with just one intermediate state the transition completes successfully), and (ii) collective coherent superposition of Λ processes (i.e., there is only one path for the transition, which requires more than one intermediate state to be in a specific coherent superposition). As a consequence, we gain insight into the type of correlations (static or dynamic) involved in a particular spin dynamic scenario.

Adaptation processes in Halomicronema hongdechloris, an example of the light-induced optimization of the photosynthetic apparatus on hierarchical time scales

Oxygenic photosynthesis in Halomicronema hongdechloris, one of a series of cyanobacteria producing red-shifted Chl f, is adapted to varying light conditions by a range of diverse processes acting over largely different time scales. Acclimation to far-red light (FRL) above 700 nm over several days is mirrored by reversible changes in the Chl f content. In several cyanobacteria that undergo FRL photoacclimation, Chl d and Chl f are directly involved in excitation energy transfer in the antenna system, form the primary donor in photosystem I (PSI), and are also involved in electron transfer within photosystem II (PSII), most probably at the ChlD1 position, with efficient charge transfer happening with comparable kinetics to reaction centers containing Chl a. In H. hongdechloris, the formation of Chl f under FRL comes along with slow adaptive proteomic shifts like the rebuilding of the D1 complex on the time scale of days. On shorter time scales, much faster adaptation mechanisms exist involving the phycobilisomes (PBSs), which mainly contain allophycocyanin upon adaptation to FRL. Short illumination with white, blue, or red light leads to reactive oxygen species-driven mobilization of the PBSs on the time scale of seconds, in effect recoupling the PBSs with Chl f-containing PSII to re-establish efficient excitation energy transfer within minutes. In summary, H. hongdechloris reorganizes PSII to act as a molecular heat pump lifting excited states from Chl f to Chl a on the picosecond time scale in combination with a light-driven PBS reorganization acting on the time scale of seconds to minutes depending on the actual light conditions. Thus, structure-function relationships in photosynthetic energy and electron transport in H. hongdechloris including long-term adaptation processes cover 10-12 to 106 seconds, i.e., 18 orders of magnitude in time.

Discovery and Manipulation of van der Waals Polarons in Sb2O3 Ultrathin Molecular Crystal

Manipulating single electrons at the atomic scale is vital for mastering complex surface processes governed by the transfer of individual electrons. Polarons, composed of electrons stabilized by electron-phonon coupling, offer a pivotal medium for such manipulation. Here, using scanning tunneling microscopy and spectroscopy (STM/STS) and density functional theory (DFT) calculations, we report the identification and manipulation of a new type of polaron, dubbed van der Waals (vdW) polaron, within mono- to trilayer ultrathin films composed of Sb2O3 molecules that are bonded via vdW attractions. The Sb2O3 films were grown on a graphene-covered SiC(0001) substrate via molecular beam epitaxy. Unlike prior molecular polarons, STM imaging observed polarons at the interstitial sites of the molecular film, presenting unique electronic states and localized band bending. DFT calculations revealed the lowest conduction band as an intermolecular bonding state, capable of ensnaring an extra electron through locally diminished intermolecular distances, thereby forming an intermolecular vdW polaron. We also demonstrated the ability to generate, move, and erase such vdW polarons using an STM tip. Our work uncovers a new type of polaron stabilized by coupling with intermolecular vibrations where vdW interactions dominate, paving the way for designing atomic-scale electron transfer processes and enabling precise tailoring of electron-related properties and functionalities.

Progress in ultrasmall ferrite nanoparticles enhanced T1 magnetic resonance angiography

Contrast-enhanced magnetic resonance angiography (CE-MRA) plays a critical role in diagnosing and monitoring various vascular diseases. Achieving high-sensitivity detection of vascular abnormalities in CE-MRA depends on the properties of contrast agents. In contrast to clinically used gadolinium-based contrast agents (GBCAs), the new generation of ultrasmall ferrite nanoparticles-based contrast agents have high relaxivity, long blood circulation time, easy surface functionalization, and high biocompatibility, hence showing promising prospects in CE-MRA. This review aims to comprehensively summarize the advancements in ultrasmall ferrite nanoparticles-enhanced MRA for detecting vascular diseases. Additionally, this review also discusses the future clinical translational potential of ultrasmall ferrite nanoparticles-based contrast agents for vascular imaging. By investigating the current status of research and clinical applications, this review attempts to outline the progress, challenges, and future directions of using ultrasmall ferrite nanoparticles to drive the field of CE-MRA into a new frontier of accuracy and diagnostic efficacy.

Motorized chain models of the ideal chromosome

An array of motor proteins consumes chemical energy in setting up the architectures of chromosomes. Here, we explore how the structure of ideal polymer chains is influenced by two classes of motors. The first class which we call "swimming motors" acts to propel the chromatin fiber through three-dimensional space. They represent a caricature of motors such as RNA polymerases. Previously, they have often been described by adding a persistent flow onto Brownian diffusion of the chain. The second class of motors, which we call "grappling motors" caricatures the loop extrusion processes in which segments of chromatin fibers some distance apart are brought together. We analyze these models using a self-consistent variational phonon approximation to a many-body Master equation incorporating motor activities. We show that whether the swimming motors lead to contraction or expansion depends on the susceptibility of the motors, that is, how their activity depends on the forces they must exert. Grappling motors in contrast to swimming motors lead to long-ranged correlations that resemble those first suggested for fractal globules and that are consistent with the effective interactions inferred by energy landscape analyses of Hi-C data on the interphase chromosome.

Predicting the Color Polymorphism of ROY from a Time-Dependent Optimally Tuned Screened Range-Separated Hybrid Functional

Polymorphism is a well-known property of molecular crystals, which allows the same molecule to form solids with several crystalline structures that can differ significantly in physical properties. Polymorphs that possess different optical absorption properties in the visible range may exhibit different perceived colors, a phenomenon known as color polymorphism. One striking example of color polymorphism is given by 5-methyl-2-[(2-nitrophenyl)amino]-3-thiophenecarbonitrile, known as ROY for its red-orange-yellow colors. First-principles prediction of color polymorphism may help in polymorph assignment and design but has proven to be challenging. Here, we predict the absorption spectra and simulate the colors of 12 ROY polymorphs using the general, nonempirical method of time-dependent (TD) optimally tuned screened range-separated hybrid (OT-SRSH) functional. For 5 ROY polymorphs with known experimental absorption spectra, we show that the TD-OT-SRSH approach predicts absorption spectra in quantitative agreement with experiment. For all polymorphs, we show that an accurate simulation of the colors is obtained, paving the way to a fully predictive, low-cost calculation of color polymorphism.

Observation of Chirality Transfer in Twisted Few-Layer Graphene

Chiral materials are the focus of research in a variety of fields such as chiroptical sensing, biosensing, catalysis, and spintronics. Twisted two-dimensional (2D) materials are rapidly developing into a class of atomically thin chiral materials that can be effectively modulated through interlayer twist. However, chirality transfer in chiral 2D materials has not been reported. Here, we show that the chirality from the twist interface of graphene can directly transfer to achiral few-layer graphene and lead to a strong chiroptical response probed with circularly polarized Raman spectroscopy. Distinct Raman optical activity (ROA) for the interlayer shear modes in achiral few-layer graphene is observed, with the degree of polarization reaching as high as 0.5. These findings demonstrate the programmability of chiroptical response through stacking and twist engineering in 2D materials and offer insights into the transfer of chirality in atomically thin chiral materials for optical and electronic applications.

Toward Consistent Predictions of Core/Valence Ionization Potentials and Valence Excitation Energies by MRSF-TDDFT

Optimizing exchange-correlation functionals for both core/valence ionization potentials (cIPs/vIPs) and valence excitation energies (VEEs) at the same time in the framework of MRSF-TDDFT is self-contradictory. To overcome the challenge, within the previous "adaptive exact exchange" or double-tuning strategy on Coulomb-attenuating XC functionals (CAM), a new XC functional specifically for cIPs and vIPs was first developed by enhancing exact exchange to both short- and long-range regions. The resulting DTCAM-XI functional achieved remarkably high accuracy in its predictions with errors of less than half eV. An additional concept of "valence attenuation", where the amount of exact exchange for the frontier orbital regions is selectively suppressed, was introduced to consistently predict both VEEs and IPs at the same time. The second functional, DTCAM-XIV, exhibits consistent overall prediction accuracy at ∼0.64 eV. By preferentially optimizing VEEs within the same "valence attenuation" concept, a third functional, DTCAM-VAEE, was obtained, which exhibits improved performance as compared to that of the previous DTCAM-VEE and DTCAM-AEE in the prediction of VEEs, making it an attractive alternative to BH&HLYP. As the combination of "adaptive exchange" and "valence attenuation" is operative, it would be exciting to explore its potential with a more tunable framework in the future.

How Does HF-DFT Achieve Chemical Accuracy for Water Clusters?

Bolstered by recent calculations of exact functional-driven errors (FEs) and density-driven errors (DEs) of semilocal density functionals in the water dimer binding energy [Kanungo, B. J. Phys. Chem. Lett. 2024, 15, 323-328], we investigate approximate FEs and DEs in neutral water clusters containing up to 20 monomers, charged water clusters, and alkali- and halide-water clusters. Our proxy for the exact density is r2SCAN 50, a 50% global hybrid of exact exchange with r2SCAN, which may be less correct than r2SCAN for the compact water monomer but importantly more correct for long-range electron transfers in the noncompact water clusters. We show that SCAN makes substantially larger FEs for neutral water clusters than r2SCAN, while both make essentially the same DEs. Unlike the case for barrier heights, these FEs are small in a relative sense and become large in an absolute sense only due to an increase in cluster size. SCAN@HF, short for SCAN evaluated on the Hartree-Fock (HF) density, produces a cancellation of errors that makes it chemically accurate for predicting the absolute binding energies of water clusters. Likewise, adding a long-range dispersion correction to r2SCAN@HF, as in the composite method HF-r2SCAN-DC4, makes its FE more negative than in r2SCAN@HF, permitting a near-perfect cancellation of FE and DE. r2SCAN by itself (and even more so, r2SCAN evaluated on the r2SCAN 50 density), is almost perfect for the energy differences between water hexamers, and thus probably also for liquid water away from the boiling point. Thus, the accuracy of composite methods like SCAN@HF and HF-r2SCAN-DC4 is not due to the HF density being closer to the exact density, but to a compensation of errors from its greater degree of localization. We also give an argument for the approximate reliability of this unconventional error cancellation for diverse molecular properties. Finally, we confirm this unconventional error cancellation for the SCAN description of the water trimer via Kohn-Sham inversion of the CCSD(T) density.

Orientational Effects and Molecular-Scale Thermoelectricity Control

The orientational effect concept in a molecular-scale junction is established for asymmetric junctions, which requires the fulfillment of two conditions: (1) design of an asymmetric molecule with strong distinct terminal end groups and (2) construction of a doubly asymmetric junction by placing an asymmetric molecule in an asymmetric junction to form a multicomponent system such as Au/Zn-TPP+M/Au. Here, we demonstrate that molecular-scale junctions that satisfy the conditions of these effects can manifest Seebeck coefficients whose sign fluctuates depending on the orientation of the molecule within the asymmetric junction in a complete theoretical investigation. Three anthracene-based compounds are investigated in three different scenarios, one of which displays a bithermoelectric behavior due to the presence of strong anchor groups, including pyridyl and thioacetate. This bithermoelectricity demonstration implies that if molecules with alternating orientations can be placed between an asymmetric source and drain, they can be potentially utilized for increasing the thermovoltage in molecular-scale thermoelectric energy generators (TEGs).

Computational Analysis of Heat Capacity Effects in Protein-Ligand Binding

Heat capacity effects in protein-ligand binding as measured by calorimetric experiments have recently attracted considerable attention, particularly in the field of enzyme inhibitor design. A significant negative heat capacity change upon ligand binding implies a marked temperature dependence of the binding enthalpy, which is of high relevance for attempts to optimize protein-ligand interactions. In this work, we address the question of how well such heat capacity changes can be predicted by computer simulations. We examine a series of human thrombin inhibitors that all bind with ΔCp values of about -0.4 kcal/mol/K and calculate heat capacity changes from plain molecular dynamics simulations of the bound and free states of the enzyme and ligand. The results show that accurate ΔCp estimates within a few tenths of a kcal/mol/K of the experimental values can be obtained with this approach. This allows us to address the structural and energetic origin of the negative heat capacity changes for the thrombin inhibitors, and it is found that conformational equilibria of the free ligands in solution make a major contribution to the observed effect.

Chemically Driven Sintering of Colloidal Cu Nanocrystals for Multiscale Electronic and Optical Devices

Emerging applications of Internet of Things (IoT) technologies in smart health, home, and city, in agriculture and environmental monitoring, and in transportation and manufacturing require materials and devices with engineered physical properties that can be manufactured by low-cost and scalable methods, support flexible forms, and are biocompatible and biodegradable. Here, we report the fabrication and device integration of low-cost and biocompatible/biodegradable colloidal Cu nanocrystal (NC) films through room temperature, solution-based deposition, and sintering, achieved via chemical exchange of NC surface ligands. Treatment of organic-ligand capped Cu NC films with solutions of shorter, environmentally benign, and noncorrosive inorganic reagents, namely, SCN- and Cl-, effectively removes the organic ligands, drives NC grain growth, and limits film oxidation. We investigate the mechanism of this chemically driven sintering by systemically varying the Cu NC size, ligand reagent, and ligand treatment time and follow the evolution of their structure and electrical and optical properties. Cl--treated, 4.5 nm diameter Cu NC films yield the lowest DC resistivity, only 3.2 times that of bulk Cu, and metal-like dielectric functions at optical frequencies. We exploit the high conductivity of these chemically sintered Cu NC films and, in combination with photo- and nanoimprint-lithography, pattern multiscale structures to achieve high-Q radio frequency (RF) capacitive sensors and near-infrared (NIR) resonant optical metasurfaces.

The Impact of Partial Carrier Confinement on Stimulated Emission in Strongly Confined Perovskite Nanocrystals

Semiconductor lead halide perovskites are excellent candidates for realizing low threshold light amplification due to their tunable and highly efficient luminescence, ease of processing, and strong light-matter interactions. However, most studies on optical gain have addressed bulk films, nanowires, or nanocrystals that exhibit little or no size quantization. Here, we show by means of a multitude of optical spectroscopy methods that small CsPbBr3 nanocrystals (NCs) exhibit a progressive red shift of the band-edge transition upon addition of electron-hole pairs, at least one carrier of which occupies a 2-fold degenerate, delocalized state in agreement with strong confinement. We demonstrate that this combination results in a threshold for biexciton gain, well below the limit of one electron-hole pair on average per NC. On the other hand, both the luminescent lifetime and the optical Stark effect of 4.7 nm CsPbBr3 NCs indicate that the oscillator strength of the band-edge transition is considerably smaller than expected from the band-edge absorption. We assign this discrepancy to a mixed confinement regime, with one delocalized and one localized charge carrier, and show that the concomitant reduction of the oscillator strength for stimulated emission accounts for the surprisingly small material gain observed in small NCs. The conclusion of mixed confinement aligns with studies reporting small and large polarons for holes and electrons in lead halide perovskite nanocrystals, respectively, and creates opportunities for understanding multiexciton photophysics in confined perovskite materials.

A Stochastic Landscape Approach for Protein Folding State Classification

Protein folding is a critical process that determines the functional state of proteins. Proper folding is essential for proteins to acquire their functional three-dimensional structures and execute their biological role, whereas misfolded proteins can lead to various diseases, including neurodegenerative disorders like Alzheimer's and Parkinson's. Therefore, a deeper understanding of protein folding is vital for understanding disease mechanisms and developing therapeutic strategies. This study introduces the Stochastic Landscape Classification (SLC), an innovative, automated, nonlearning algorithm that quantitatively analyzes protein folding dynamics. Focusing on collective variables (CVs) - low-dimensional representations of complex dynamical systems like molecular dynamics (MD) of macromolecules - the SLC approach segments the CVs into distinct macrostates, revealing the protein folding pathway explored by MD simulations. The segmentation is achieved by analyzing changes in CV trends and clustering these segments using a standard density-based spatial clustering of applications with noise (DBSCAN) scheme. Applied to the MD-based CV trajectories of Chignolin and Trp-Cage proteins, the SLC demonstrates apposite accuracy, validated by comparing standard classification metrics against ground-truth data. These metrics affirm the efficacy of the SLC in capturing intricate protein dynamics and offer a method to evaluate and select the most informative CVs. The practical application of this technique lies in its ability to provide a detailed, quantitative description of protein folding processes, with significant implications for understanding and manipulating protein behavior in industrial and pharmaceutical contexts.

Energy-Conserving Surface Hopping for Auger Processes

Auger-type processes are ubiquitous in nanoscale materials because quantum confinement enhances Coulomb interactions, and there exist large densities of states. Modeling Auger processes requires the modification of nonadiabatic (NA) molecular dynamics algorithms to include transitions caused by both NA and Coulomb couplings. The system is split into quantum and classical subsystems, e.g., electrons and vibrations, and as a result, energy conservation becomes nontrivial. In surface hopping, an electronic transition induced by NA coupling is accompanied by a classical velocity readjustment to ensure conservation of the total quantum-classical energy. A different treatment is needed for Auger transitions driven by Coulomb interactions. We develop a nonadiabatic molecular dynamics methodology that meticulously differentiates the energy redistribution accompanying hops induced by the NA coupling and the Coulomb interaction and correctly conserves the total energy at each transition. If the transition is driven by a Coulomb interaction, the hop energy is redistributed within the quantum electronic subsystem only. If the transition is NA, the energy is redistributed between the quantum and classical subsystems. Properly maintaining energy conservation for both types of transitions is crucial to generate a correct order of events, obtain accurate transition times, maintain a proper statistical distribution of state populations, and reach thermodynamic equilibrium. We test the method with biexciton annihilation and Auger-assisted hot electron relaxation in a CdSe quantum dot. The sequence of Auger and phonon-driven processes and the calculated time scales are in excellent agreement with the experimental results. The developed approach can be coupled with any surface-hopping method and provides a crucial practical advance to study charge-carrier dynamics in the nanoscale and condensed matter systems.

Developing a Differentiable Long-Range Force Field for Proteins with E(3) Neural Network-Predicted Asymptotic Parameters

Accurately describing long-range interactions is a significant challenge in molecular dynamics (MD) simulations of proteins. High-quality long-range potential is also an important component of the range-separated machine learning force field. This study introduces a comprehensive asymptotic parameter database encompassing atomic multipole moments, polarizabilities, and dispersion coefficients. Leveraging active learning, our database comprehensively represents protein fragments with up to 8 heavy atoms, capturing their conformational diversity with merely 78,000 data points. Additionally, the E(3) neural network (E3NN) is employed to predict the asymptotic parameters directly from the local geometry. The E3NN models demonstrate exceptional accuracy and transferability across all asymptotic parameters, achieving an R2 of 0.999 for both protein fragments and 20 amino acid dipeptide test sets. The long-range electrostatic and dispersion energies can be obtained using the E3NN-predicted parameters, with an error of 0.07 and 0.02 kcal/mol, respectively, when compared to symmetry-adapted perturbation theory (SAPT). Therefore, our force fields demonstrate the capability to accurately describe long-range interactions in proteins, paving the way for next-generation protein force fields.