Super-resolution fluorescence microscopy techniques are powerful tools to investigate polymer systems. In this review, we address how these techniques have been applied to hydrogel nano- and microparticles, so-called nano- or microgels. We outline which research questions on microgels could be addressed and what new insights could be achieved. Studies of the morphology, shape, and deformation of microgels; their internal compartmentalization; the cross-linker distribution and polarity inside them; and their dynamics and diffusion are summarized. In particular, the abilities to super-resolve structures in three dimensions have boosted the research field and have also allowed researchers to obtain impressive 3D images of deformed microgels. Accessing information beyond 3D localization, such as spectral and lifetime properties and correlative imaging or the combination of data with other methods, shines new light onto polymer systems and helps us understand their complexity in detail. Such future trends and developments are also addressed.

Multidimensional optical spectra are measured from the response of a material system to a sequence of laser pulses and have the capacity to elucidate specific molecular interactions and dynamics whose influences are absent or obscured in a conventional linear absorption spectrum. Interpretation of complex spectra is supported by theoretical modeling of the spectroscopic observable, requiring implementation of quantum dynamics for coupled electrons and nuclei. Performing numerically correct quantum dynamics in this context may pose computational challenges, particularly in the condensed phase. Semiclassical methods based on calculating classical trajectories offer a practical alternative. Here I review the recent application of some semiclassical, trajectory-based methods to nonlinear molecular vibrational and electronic spectra.

Advances in atomic, molecular, and optical physics techniques allowed the cooling of simple molecules down to the ultracold regime (1 mK) and opened opportunities to study chemical reactions with unprecedented levels of control. This review covers recent developments in studying bimolecular chemistry at ultralow temperatures. We begin with a brief overview of methods for producing, manipulating, and detecting ultracold molecules. We then survey experimental works that exploit the controllability of ultracold molecules to probe and modify their long-range interactions. Further combining the use of physical chemistry techniques such as mass spectrometry and ion imaging significantly improved the detection of ultracold reactions and enabled explorations of their dynamics in the short range. We discuss a series of studies on the reaction KRb + KRb → K2 + Rb2 initiated below 1 μK, including the direct observation of a long-lived complex, the demonstration of product rotational state control via conserved nuclear spins, and a test of the statistical model using the complete quantum state distribution of the products.

Because plasmonic metal nanostructures combine strong light absorption with catalytically active surfaces, they have become platforms for the light-assisted catalysis of chemical reactions. The enhancement of reaction rates by plasmonic excitation has been extensively discussed. This review focuses on a less discussed aspect: the induction of new reaction pathways by light excitation. Through commentary on seminal reports, we describe the principles behind the optical modulation of chemical reactivity and selectivity on plasmonic metal nanostructures. Central to these phenomena are excited charge carriers generated by plasmonic excitation, which modify the energy landscape available to surface reactive species and unlock pathways not conventionally available in thermal catalysis. Photogenerated carriers can trigger bond dissociation or desorption in an adsorbate-selective manner, drive charge transfer and multielectron redox reactions, and generate radical intermediates. Through one or more of these mechanisms, a specific pathway becomes favored under light. By improved control over these mechanisms, light-assisted catalysis can be transformational for chemical synthesis and energy conversion.

Time-dependent density functional theory has emerged as a method of choice for calculations of spectra and response properties in physics, chemistry, and biology, with its system-size scaling enabling computations on systems much larger than otherwise possible. While increasingly complex and interesting systems have been successfully tackled with relatively simple functional approximations, there has also been increasing awareness that these functionals tend to fail for certain classes of approximations. Here I review the fundamental challenges the approximate functionals have in describing double excitations and charge-transfer excitations, which are two of the most common impediments for the theory to be applied in a black-box way. At the same time, I describe the progress made in recent decades in developing functional approximations that give useful predictions for these excitations.

Quantum chemistry in the form of density functional theory (DFT) calculations is a powerful numerical experiment for predicting intermolecular interaction energies. However, no chemical insight is gained in this way beyond predictions of observables. Energy decomposition analysis (EDA) can quantitatively bridge this gap by providing values for the chemical drivers of the interactions, such as permanent electrostatics, Pauli repulsion, dispersion, and charge transfer. These energetic contributions are identified by performing DFT calculations with constraints that disable components of the interaction. This review describes the second-generation version of the absolutely localized molecular orbital EDA (ALMO-EDA-II). The effects of different physical contributions on changes in observables such as structure and vibrational frequencies upon complex formation are characterized via the adiabatic EDA. Example applications include red- versus blue-shifting hydrogen bonds; the bonding and frequency shifts of CO, N2, and BF bound to a [Ru(II)(NH3)5]2 + moiety; and the nature of the strongly bound complexes between pyridine and the benzene and naphthalene radical cations. Additionally, the use of ALMO-EDA-II to benchmark and guide the development of advanced force fields for molecular simulation is illustrated with the recent, very promising, MB-UCB potential.

Ionizing rays cause damage to genomes, proteins, and signaling pathways that normally regulate cell activity, with harmful consequences such as accelerated aging, tumors, and cancers but also with beneficial effects in the context of radiotherapies. While the great pace of research in the twentieth century led to the identification of the molecular mechanisms for chemical lesions on the building blocks of biomacromolecules, the last two decades have brought renewed questions, for example, regarding the formation of clustered damage or the rich chemistry involving the secondary electrons produced by radiolysis. Radiation chemistry is now meeting attosecond science, providing extraordinary opportunities to unravel the very first stages of biological matter radiolysis. This review provides an overview of the recent progress made in this direction, focusing mainly on the atto- to femto- to picosecond timescales. We review promising applications of time-dependent density functional theory in this context.

As energy demands increase, electrocatalysis serves as a vital tool in energy conversion. Elucidating electrocatalytic mechanisms using in situ spectroscopic characterization techniques can provide experimental guidance for preparing high-efficiency electrocatalysts. Surface-enhanced Raman spectroscopy (SERS) can provide rich spectral information for ultratrace surface species and is extremely well suited to studying their activity. To improve the material and morphological universalities, researchers have employed different kinds of nanostructures that have played important roles in the development of SERS technologies. Different strategies, such as so-called borrowing enhancement from shell-isolated modes and shell-isolated nanoparticle-enhanced Raman spectroscopy (SHINERS)-satellite structures, have been proposed to obtain highly effective Raman enhancement, and these methods make it possible to apply SERS to various electrocatalytic systems. Here, we discuss the development of SERS technology, focusing on its applications in different electrocatalytic reactions (such as oxygen reduction reactions) and at different nanostructure surfaces, and give a brief outlook on its development.

Multiscale models combining quantum mechanical and classical descriptions are a very popular strategy to simulate properties and processes of complex systems. Many alternative formulations have been developed, and they are now available in all of the most widely used quantum chemistry packages. Their application to the study of light-driven processes, however, is more recent, and some methodological and numerical problems have yet to be solved. This is especially the case for the polarizable formulation of these models, the recent advances in which we review here. Specifically, we identify and describe the most important specificities that the polarizable formulation introduces into both the simulation of excited-state dynamics and the modeling of excitation energy and electron transfer processes.

In this article, we review nonadiabatic molecular dynamics (NAMD) methods for modeling spin-crossover transitions. First, we discuss different representations of electronic states employed in the grid-based and direct NAMD simulations. The nature of interstate couplings in different representations is highlighted, with the main focus on nonadiabatic and spin-orbit couplings. Second, we describe three NAMD methods that have been used to simulate spin-crossover dynamics, including trajectory surface hopping, ab initio multiple spawning, and multiconfiguration time-dependent Hartree. Some aspects of employing different electronic structure methods to obtain information about potential energy surfaces and interstate couplings for NAMD simulations are also discussed. Third, representative applications of NAMD to spin crossovers in molecular systems of different sizes and complexities are highlighted. Finally, we pose several fundamental questions related to spin-dependent processes. These questions should be possible to address with future methodological developments in NAMD.

In the past two decades, machine learning potentials (MLPs) have reached a level of maturity that now enables applications to large-scale atomistic simulations of a wide range of systems in chemistry, physics, and materials science. Different machine learning algorithms have been used with great success in the construction of these MLPs. In this review, we discuss an important group of MLPs relying on artificial neural networks to establish a mapping from the atomic structure to the potential energy. In spite of this common feature, there are important conceptual differences among MLPs, which concern the dimensionality of the systems, the inclusion of long-range electrostatic interactions, global phenomena like nonlocal charge transfer, and the type of descriptor used to represent the atomic structure, which can be either predefined or learnable. A concise overview is given along with a discussion of the open challenges in the field.

The photoacid dynamics of fluorescent proteins include both electronic excited- and ground-state mechanisms of proton transfer. The associated characteristic timescales of these reactions range over many orders of magnitude, and the tunneling, barrier crossing, and relevant thermodynamics have in certain cases been linked to coherent nuclear motion. We review the literature and summarize the experiments and theory that demonstrate proton tunneling in the electronic ground state of the green fluorescent protein (GFP). We also discuss the excited-state proton-transfer reaction of GFP that takes place on the picosecond timescale. Although this reaction has been investigated using several vibrational spectroscopic methods, the interpretation remains unsettled. We discuss recent advances as well as remaining questions, in particular those related to the vibrational mode couplings that involve low-frequency modulations of chromophore vibrations on the timescale of proton transfer.

Upconverting nanoparticles (UCNPs) compose a class of luminescent materials that utilize the unique wavelength-converting properties of lanthanide (Ln) ions for light-harvesting applications, photonics technologies, and biological imaging and sensing experiments. Recent advances in UCNP design have shed light on the properties of local color centers, both intrinsic and controllably induced, within these materials and their potential influence on UCNP photophysics. In this review, we describe fundamental studies of color centers in Ln-based materials, including research into their origins and their roles in observed photodarkening and photobrightening mechanisms. We place particular focus on the new functionalities that are enabled by harnessing the properties of color centers within Ln-doped nanocrystals, illustrated through applications in afterglow-based bioimaging, X-ray detection, all-inorganic nanocrystal photoswitching, and fully rewritable optical patterning and memory.

Since external magnetic fields were first employed to deflect paramagnetic atoms in 1921, a range of magnetic field–based methods have been introduced to state-selectively manipulate paramagnetic species. These methods include magnetic guides, which selectively filter paramagnetic species from all other components of a beam, and magnetic traps, where paramagnetic species can be spatially confined for extended periods of time. However, many of these techniques were developed for atomic—rather than molecular—paramagnetic species. It has proven challenging to apply some of these experimental methods developed for atoms to paramagnetic molecules. Thanks to the emergence of new experimental approaches and new combinations of existing techniques, the past decade has seen significant progress toward the manipulation and control of paramagnetic molecules. This review identifies the key methods that have been implemented for the state-selective manipulation of paramagnetic molecules—discussing the motivation, state of the art, and future prospects of the field. Key applications include the ability to control chemical interactions, undertake precise spectroscopic measurements, and challenge our understanding of chemical reactivity at a fundamental level.

We review a suite of stochastic vector computational approaches for studying the electronic structure of extended condensed matter systems. These techniques help reduce algorithmic complexity, facilitate efficient parallelization, simplify computational tasks, accelerate calculations, and diminish memory requirements. While their scope is vast, we limit our study to ground-state and finite temperature density functional theory (DFT) and second-order many-body perturbation theory. More advanced topics, such as quasiparticle (charge) and optical (neutral) excitations and higher-order processes, are covered elsewhere. We start by explaining how to use stochastic vectors in computations, characterizing the associated statistical errors. Next, we show how to estimate the electron density in DFT and discuss effective techniques to reduce statistical errors. Finally, we review the use of stochastic vectors for calculating correlation energies within the second-order Møller-Plesset perturbation theory and its finite temperature variational form. Example calculation results are presented and used to demonstrate the efficacy of the methods.

The processes of genome expression, regulation, and repair require direct interactions between proteins and DNA at specific sites located at and near single-stranded–double-stranded DNA (ssDNA–dsDNA) junctions. Here, we review the application of recently developed spectroscopic methods and analyses that combine linear absorbance and circular dichroism spectroscopy with nonlinear 2D fluorescence spectroscopy to study the local conformations and conformational disorder of the sugar-phosphate backbones of ssDNA–dsDNA fork constructs that have been internally labeled with exciton-coupled cyanine (iCy3)2 dimer probes. With the application of these methods, the (iCy3)2 dimer can serve as a reliable probe of the mean local conformations and conformational distributions of the sugar-phosphate backbones of dsDNA at various critical positions. The results of our studies suggest a possible structural framework for understanding the roles of DNA breathing in driving the processes of protein–DNA complex assembly and function.

Knowledge of protein structure is crucial to our understanding of biological function and is routinely used in drug discovery. High-resolution techniques to determine the three-dimensional atomic coordinates of proteins are available. However, such methods are frequently limited by experimental challenges such as sample quantity, target size, and efficiency. Structural mass spectrometry (MS) is a technique in which structural features of proteins are elucidated quickly and relatively easily. Computational techniques that convert sparse MS data into protein models that demonstrate agreement with the data are needed. This review features cutting-edge computational methods that predict protein structure from MS data such as chemical cross-linking, hydrogen–deuterium exchange, hydroxyl radical protein footprinting, limited proteolysis, ion mobility, and surface-induced dissociation. Additionally, we address future directions for protein structure prediction with sparse MS data.

Phillip L. Geissler made important contributions to the statistical mechanics of biological polymers, heterogeneous materials, and chemical dynamics in aqueous environments. He devised analytical and computational methods that revealed the underlying organization of complex systems at the frontiers of biology, chemistry, and materials science. In this retrospective we celebrate his work at these frontiers.

Photosynthetic light harvesting exhibits near-unity quantum efficiency. The high efficiency is achieved through a series of energy and charge transfer steps within a network of pigment-containing proteins. Remarkably, high efficiency is conserved across many organisms despite differences in the protein structures and organization that allow each organism to respond to its own biological niche and the stressors within. In this review, we highlight recent progress toward understanding how organisms maintain optimal light-harvesting ability by acclimating to their environment. First, we review the building blocks of photosynthetic light harvesting, energy transfer, and time-resolved spectroscopic techniques. Then, we explore how three classes of photosynthetic organisms—purple bacteria, cyanobacteria, and green plants—optimize their light-harvesting apparatuses to their particular environment. Overall, research has shown that photosynthetic energy transfer is robust to changing environmental conditions, with each organism utilizing its own strategies to optimize photon capture in its particular biological niche.

Elementary events that determine photochemical outcomes and molecular functionalities happen on the femtosecond and subfemtosecond timescales. Among the most ubiquitous events are the nonadiabatic dynamics taking place at conical intersections. These facilitate ultrafast, nonradiative transitions between electronic states in molecules that can outcompete slower relaxation mechanisms such as fluorescence. The rise of ultrafast X-ray sources, which provide intense light pulses with ever-shorter durations and larger observation bandwidths, has fundamentally revolutionized our spectroscopic capabilities to detect conical intersections. Recent theoretical studies have demonstrated an entirely new signature emerging once a molecule traverses a conical intersection, giving detailed insights into the coupled nuclear and electronic motions that underlie, facilitate, and ultimately determine the ultrafast molecular dynamics. Following a summary of current sources and experiments, we survey these techniques and provide a unified overview of their capabilities. We discuss their potential to dramatically increase our understanding of ultrafast photochemistry.