Using electric vehicles to enhance power outage resilience - An agent-based modeling approach.

Power outages can cause severe disruption to critical infrastructure. With the predicted increase in the electrification of the transport sector, society will become even more vulnerable to the effects of power outages. While increased electric vehicle (EV) adoption will contribute to the electrification process, EVs can also offer capabilities to provide services during an outage. This paper studied the use of a fleet of EVs during the aftermath of a disaster to provide disaster relief by donating power to a shelter, delivering critical supplies and people in need, and providing transport for personnel or performing inspections. While the bulk of the past work has focused on using EVs to increase the resilience of the distribution grid, or individual buildings, to a power outage, this paper was novel in its use of an agent-based model to study EVs that are performing functions to increase the resilience of a community to an outage. The fleet of EVs were provided access to a microgrid with a solar array, one or two EV fast chargers, and three possible sizes of a storage. Useful outputs were produced and studied for such features as daily energy donated to a shelter, daily energy used at the microgrid, and the length of outages that can be supported before the energy is depleted at the microgrid. Results showed that increasing storage size at the microgrid led to substantial increases in the outage length that could be support. Additionally, it was found that focusing a fleet on delivery and transport tasks, as opposed to energy donation, could also increase the length of outages that could be supported.

Subcutaneous injection of adipose stromal cell-secretome improves renal function and reduces inflammation in established acute kidney injury.

BACKGROUND: Adipose stromal cells (ASC) are a form of mesenchymal stromal cells that elicit effects primarily via secreted factors, which may have advantages for the treatment of injury or disease. Several previous studies have demonstrated a protective role for MSC/ASC on mitigating acute kidney injury but whether ASC derived factors could hasten recovery from established injury has not been evaluated. METHODS: We generated a concentrated secretome (CS) of human ASC under well-defined conditions and evaluated its ability to improve the recovery of renal function in a preclinical model of acute kidney injury (AKI) in rats. 24 h following bilateral ischemia/reperfusion (I/R), rats were randomized following determination of plasma creatinine into groups receiving vehicle -control or ASC-CS treatment by subcutaneous injection (2 mg protein/kg) and monitored for evaluation of renal function, structure and inflammation. RESULTS: Renal function, assessed by plasma creatinine levels, recovered faster in ASC-CS treated rats vs vehicle. The most prominent difference between the ASC-CS treated vs vehicle was observed in rats with the most severe degree of initial injury (Pcr > 3.0 mg/dl 24 h post I/R), whereas rats with less severe injury (Pcr < 2.9 mg/dl) recovered quickly regardless of treatment. The quicker recovery of ASC-treated rats with severe injury was associated with less tissue damage, inflammation, and lower plasma angiopoietin 2. In vitro, ASC-CS attenuated the activation of the Th17 phenotype in lymphocytes isolated from injured kidneys. CONCLUSIONS: Taken together, these data suggest that ASC-CS represents a potent therapeutic option to improve established AKI.

Leveraging uncertainty estimates and derivative information in Gaussian process regression for efficient collection and use of molecular simulation data.

We introduce Gaussian Process Regression (GPR) as an enhanced method of thermodynamic extrapolation and interpolation. The heteroscedastic GPR models that we introduce automatically weight provided information by its estimated uncertainty, allowing for the incorporation of highly uncertain, high-order derivative information. By the linearity of the derivative operator, GPR models naturally handle derivative information and, with appropriate likelihood models that incorporate heterogeneous uncertainties, are able to identify estimates of functions for which the provided observations and derivatives are inconsistent due to the sampling bias that is common in molecular simulations. Since we utilize kernels that form complete bases on the function space to be learned, the estimated uncertainty in the model takes into account that of the functional form itself, in contrast to polynomial interpolation, which explicitly assumes the functional form to be fixed. We apply GPR models to a variety of data sources and assess various active learning strategies, identifying when specific options will be most useful. Our active-learning data collection based on GPR models incorporating derivative information is finally applied to tracing vapor-liquid equilibrium for a single-component Lennard-Jones fluid, which we show represents a powerful generalization to previous extrapolation strategies and Gibbs-Duhem integration. A suite of tools implementing these methods is provided at https://github.com/usnistgov/thermo-extrap.

Systematic control of collective variables learned from variational autoencoders.

Variational autoencoders (VAEs) are rapidly gaining popularity within molecular simulation for discovering low-dimensional, or latent, representations, which are critical for both analyzing and accelerating simulations. However, it remains unclear how the information a VAE learns is connected to its probabilistic structure and, in turn, its loss function. Previous studies have focused on feature engineering, ad hoc modifications to loss functions, or adjustment of the prior to enforce desirable latent space properties. By applying effectively arbitrarily flexible priors via normalizing flows, we focus instead on how adjusting the structure of the decoding model impacts the learned latent coordinate. We systematically adjust the power and flexibility of the decoding distribution, observing that this has a significant impact on the structure of the latent space as measured by a suite of metrics developed in this work. By also varying weights on separate terms within each VAE loss function, we show that the level of detail encoded can be further tuned. This provides practical guidance for utilizing VAEs to extract varying resolutions of low-dimensional information from molecular dynamics and Monte Carlo simulations.

Effects of home-based leg heat therapy on walking performance in patients with symptomatic peripheral artery disease: a pilot randomized trial.

Few noninvasive therapies currently exist to improve functional capacity in people with lower extremity peripheral artery disease (PAD). The goal of the present study was to test the hypothesis that unsupervised, home-based leg heat therapy (HT) using water-circulating trousers perfused with warm water would improve walking performance in patients with PAD. Patients with symptomatic PAD were randomized into either leg HT (n = 18) or a sham treatment (n = 16). Patients were provided with water-circulating trousers and a portable pump and were asked to apply the therapy daily (7 days/wk, 90 min/session) for 8 wk. The primary study outcome was the change from baseline in 6-min walk distance at 8-wk follow-up. Secondary outcomes included the claudication onset-time, peak walking time, peak pulmonary oxygen consumption and peak blood pressure during a graded treadmill test, resting blood pressure, the ankle-brachial index, postocclusive reactive hyperemia in the calf, cutaneous microvascular reactivity, and perceived quality of life. Of the 34 participants randomized, 29 completed the 8-wk follow-up. The change in 6-min walk distance at the 8-wk follow-up was significantly higher (P = 0.029) in the group exposed to HT than in the sham-treated group (Sham: median: -0.9; 25%, 75% percentiles: -5.8, 14.3; HT: median: 21.3; 25%, 75% percentiles: 10.1, 42.4, P = 0.029). There were no significant differences in secondary outcomes between the HT and sham group at 8-wk follow-up. The results of this pilot study indicate that unsupervised, home-based leg HT is safe, well-tolerated, and elicits a clinically meaningful improvement in walking tolerance in patients with symptomatic PAD.NEW & NOTEWORTHY This is the first sham-controlled trial to examine the effects of home-based leg heat therapy (HT) on walking performance in patients with peripheral artery disease (PAD). We demonstrate that unsupervised HT using water-circulating trousers is safe, well-tolerated, and elicits meaningful changes in walking ability in patients with symptomatic PAD. This home-based treatment option is practical, painless, and may be a feasible adjunctive therapy to counteract the decline in lower extremity physical function in patients with PAD.

Kidney injury risk during prolonged exposure to current and projected wet bulb temperatures occurring during extreme heat events in healthy young men.

Wet bulb temperatures (Twet) during extreme heat events are commonly 31°C. Recent predictions indicate that Twet will approach or exceed 34°C. Epidemiological data indicate that exposure to extreme heat events increases kidney injury risk. We tested the hypothesis that kidney injury risk is elevated to a greater extent during prolonged exposure to Twet = 34°C compared with Twet = 31°C. Fifteen healthy men rested for 8 h in Twet = 31 (0)°C and Twet = 34 (0)°C. Insulin-like growth factor-binding protein 7 (IGFBP7), tissue inhibitor of metalloproteinase 2 (TIMP-2), and thioredoxin 1 (TRX-1) were measured from urine samples. The primary outcome was the product of IGFBP7 and TIMP-2 ([IGFBP7·TIMP-2]), which provided an index of kidney injury risk. Plasma interleukin-17a (IL-17a) was also measured. Data are presented at preexposure and after 8 h of exposure and as mean (SD) change from preexposure. The increase in [IGFBP7·TIMP-2] was markedly greater at 8 h in the 34°C [+26.9 (27.1) (ng/mL)2/1,000) compared with the 31°C [+6.2 (6.5) (ng/mL)2/1,000] trial (P < 0.01). Urine TRX-1, a marker of renal oxidative stress, was higher at 8 h in the 34°C [+77.6 (47.5) ng/min] compared with the 31°C [+16.2 (25.1) ng/min] trial (P < 0.01). Plasma IL-17a, an inflammatory marker, was elevated at 8 h in the 34°C [+199.3 (90.0) fg/dL; P < 0.01] compared with the 31°C [+9.0 (95.7) fg/dL] trial. Kidney injury risk is exacerbated during prolonged resting exposures to Twet experienced during future extreme heat events (34°C) compared with that experienced currently (31°C), likely because of oxidative stress and inflammatory processes.NEW AND NOTEWORTHY We have demonstrated that kidney injury risk is increased when men are exposed over an 8-h period to a wet bulb temperature of 31°C and exacerbated at a wet bulb temperature of 34°C. Importantly, these heat stress conditions parallel those that are encountered during current (31°C) and future (34°C) extreme heat events. The kidney injury biomarker analyses indicate both the proximal and distal tubules as the locations of potential renal injury and that the injury is likely due to oxidative stress and inflammation.

Learning Efficient, Collective Monte Carlo Moves with Variational Autoencoders.

Discovering meaningful collective variables for enhancing sampling, via applied biasing potentials or tailored MC move sets, remains a major challenge within molecular simulation. While recent studies identifying collective variables with variational autoencoders (VAEs) have focused on the encoding and latent space discovered by a VAE, the impact of the decoding and its ability to act as a generative model remains unexplored. We demonstrate how VAEs may be used to learn (on-the-fly and with minimal human intervention) highly efficient, collective Monte Carlo moves that accelerate sampling along the learned collective variable. In contrast to many machine learning-based efforts to bias sampling and generate novel configurations, our methods result in exact sampling in the ensemble of interest and do not require reweighting. In fact, we show that the acceptance rates of our moves approach unity for a perfect VAE model. While this is never observed in practice, VAE-based Monte Carlo moves still enhance sampling of new configurations. We demonstrate, however, that the form of the encoding and decoding distributions, in particular the extent to which the decoder reflects the underlying physics, greatly impacts the performance of the trained VAE.

Evidence for Entropically Controlled Interfacial Hydration in Mesoporous Organosilicas.

At aqueous interfaces, the distribution and dynamics of adsorbates are modulated by the behavior of interfacial water. Hydration of a hydrophobic surface can store entropy via the ordering of interfacial water, which contributes to the Gibbs energy of solute binding. However, there is little experimental evidence for the existence of such entropic reservoirs, and virtually no precedent for their rational design in systems involving extended interfaces. In this study, two series of mesoporous silicas were modified in distinct ways: (1) progressively deeper thermal dehydroxylation, via condensation of surface silanols, and (2) increasing incorporation of nonpolar organic linkers into the silica framework. Both approaches result in decreasing average surface polarity, manifested in a blue-shift in the fluorescence of an adsorbed dye. For the inorganic silicas, hydrogen-bonding of water becomes less extensive as the number of surface silanols decreases. Overhauser dynamic nuclear polarization (ODNP) relaxometry indicates enhanced surface water diffusivity, reflecting a loss of enthalpic hydration. In contrast, organosilicas show a monotonic decrease in surface water diffusivity with decreasing polarity, reflecting enhanced hydrophobic hydration. Molecular dynamics simulations predict increased tetrahedrality of interfacial water for the organosilicas, implying increased ordering near the nm-size organic domains (relative to inorganic silicas, which necessarily lack such domains). These findings validate the prediction that hydrophobic hydration at interfaces is controlled by the microscopic length scale of the hydrophobic regions. They further suggest that the hydration thermodynamics of structurally heterogeneous silica surfaces can be tuned to promote adsorption, which in turn tunes the selectivity in catalytic reactions.

Affinity of small-molecule solutes to hydrophobic, hydrophilic, and chemically patterned interfaces in aqueous solution.

Performance of membranes for water purification is highly influenced by the interactions of solvated species with membrane surfaces, including surface adsorption of solutes upon fouling. Current efforts toward fouling-resistant membranes often pursue surface hydrophilization, frequently motivated by macroscopic measures of hydrophilicity, because hydrophobicity is thought to increase solute-surface affinity. While this heuristic has driven diverse membrane functionalization strategies, here we build on advances in the theory of hydrophobicity to critically examine the relevance of macroscopic characterizations of solute-surface affinity. Specifically, we use molecular simulations to quantify the affinities to model hydroxyl- and methyl-functionalized surfaces of small, chemically diverse, charge-neutral solutes represented in produced water. We show that surface affinities correlate poorly with two conventional measures of solute hydrophobicity, gas-phase water solubility and oil-water partitioning. Moreover, we find that all solutes show attraction to the hydrophobic surface and most to the hydrophilic one, in contrast to macroscopically based hydrophobicity heuristics. We explain these results by decomposing affinities into direct solute interaction energies (which dominate on hydroxyl surfaces) and water restructuring penalties (which dominate on methyl surfaces). Finally, we use an inverse design algorithm to show how heterogeneous surfaces, with multiple functional groups, can be patterned to manipulate solute affinity and selectivity. These findings, importantly based on a range of solute and surface chemistries, illustrate that conventional macroscopic hydrophobicity metrics can fail to predict solute-surface affinity, and that molecular-scale surface chemical patterning significantly influences affinity-suggesting design opportunities for water purification membranes and other engineered interfaces involving aqueous solute-surface interactions.

Acute effects of leg heat therapy on walking performance and cardiovascular and inflammatory responses to exercise in patients with peripheral artery disease.

Lower-extremity peripheral artery disease (PAD) is associated with increased risk of cardiovascular events and impaired exercise tolerance. We have previously reported that leg heat therapy (HT) applied using liquid-circulating trousers perfused with warm water increases leg blood flow and reduces blood pressure (BP) and the circulating levels of endothelin-1 (ET-1) in patients with symptomatic PAD. In this sham-controlled, randomized, crossover study, sixteen patients with symptomatic PAD (age 65 ± 5.7 years and ankle-brachial index: 0.69 ± 0.1) underwent a single 90-min session of HT or a sham treatment prior to a symptom-limited, graded cardiopulmonary exercise test on the treadmill. The primary outcome was the peak walking time (PWT) during the exercise test. Secondary outcomes included the claudication onset time (COT), resting and exercise BP, calf muscle oxygenation, pulmonary oxygen uptake (V̇O2 ), and plasma levels of ET-1, interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-α). Systolic, but not diastolic BP, was significantly lower (~7 mmHg, p < .05) during HT when compared to the sham treatment. There was also a trend for lower SBP throughout the exercise and the recovery period following HT (p = .057). While COT did not differ between treatments (p = .77), PWT tended to increase following HT (CON: 911 ± 69 s, HT: 954 ± 77 s, p = .059). Post-exercise plasma levels of ET-1 were also lower in the HT session (CON: 2.0 ± 0.1, HT: 1.7 ± 0.1, p = .02). Calf muscle oxygenation, V̇O2 , COT, IL-6, and TNF-α did not differ between treatments. A single session of leg HT lowers BP and post-exercise circulating levels of ET-1 and may enhance treadmill walking performance in symptomatic PAD patients.

Leg heat therapy improves perceived physical function but does not enhance walking capacity or vascular function in patients with peripheral artery disease.

A single session of leg heat therapy (HT) has been shown to elicit increases in leg blood flow and reduce blood pressure (BP) and the circulating levels of endothelin-1 (ET-1) in patients with symptomatic peripheral artery disease (PAD). We assessed whether 6 wk of supervised leg HT (3 times/wk) with water-circulating trousers perfused with water at 48°C improved 6-min walk distance in individuals with PAD compared with a sham treatment. Secondary outcomes included the assessment of leg vascular function, BP, quality of life, and serum ET-1 and nitrite plus nitrate (NOx) levels. Of 32 PAD patients randomized, 30 [age: 68 ± 8 yr; ankle-brachial index (ABI): 0.6 ± 0.1] completed the 3- and 6-wk follow-ups. Participants completed 98.7% of the treatment sessions. Compared with the sham treatment, exposure to HT did not improve 6-min walk distance, BP, popliteal artery reactive hyperemia, cutaneous microvascular reactivity, resting ABI, or serum NOx levels. The change from baseline to 6 wk in scores of the physical functioning subscale of the 36-item Short Form Health Survey was significantly higher in the HT group (control -6.9 ± 10 vs. HT 6.8 ± 15; 95% confidence interval: 2.5-24.3, P = 0.017). Similarly, the change in ET-1 levels after 6 wk was different between groups, with the HT group experiencing a 0.4 pg/mL decrease (95% confidence interval: -0.8-0.0, P = 0.03). These preliminary results indicate that leg HT may improve perceived physical function in symptomatic PAD patients. Additional, larger studies are needed to confirm these findings and determine the optimal treatment regimen for symptomatic PAD patients.NEW & NOTEWORTHY This is the first sham-controlled study to investigate the effects of leg heat therapy (HT) on walking performance, vascular function, and quality of life in patients with peripheral artery disease (PAD). Adherence to HT was high, and the treatment was well tolerated. Our findings revealed that HT applied with water-circulating trousers evokes a clinically meaningful increase in perceived physical function and reduces the serum concentration of the potent vasoconstrictor endothelin-1 in patients with PAD.

Extrapolation and interpolation strategies for efficiently estimating structural observables as a function of temperature and density.

Thermodynamic extrapolation has previously been used to predict arbitrary structural observables in molecular simulations at temperatures (or relative chemical potentials in open-system mixtures) different from those at which the simulation was performed. This greatly reduces the computational cost in mapping out phase and structural transitions. In this work, we explore the limitations and accuracy of thermodynamic extrapolation applied to water, where qualitative shifts from anomalous to simple-fluid-like behavior are manifested through shifts in the liquid structure that occur as a function of both temperature and density. We present formulas for extrapolating in volume for canonical ensembles and demonstrate that linear extrapolations of water's structural properties are only accurate over a limited density range. On the other hand, linear extrapolation in temperature can be accurate across the entire liquid state. We contrast these extrapolations with classical perturbation theory techniques, which are more conservative and slowly converging. Indeed, we show that such behavior is expected by demonstrating exact relationships between extrapolation of free energies and well-known techniques to predict free energy differences. An ideal gas in an external field is also studied to more clearly explain these results for a toy system with fully analytical solutions. We also present a recursive interpolation strategy for predicting arbitrary structural properties of molecular fluids over a predefined range of state conditions, demonstrating its success in mapping qualitative shifts in water structure with density.

Local Heat Therapy to Accelerate Recovery After Exercise-Induced Muscle Damage.

The prolonged impairment in muscle strength, power, and fatigue resistance after eccentric exercise has been ascribed to a plethora of mechanisms, including delayed muscle refueling and microvascular and mitochondrial dysfunction. This review explores the hypothesis that local heat therapy hastens functional recovery after strenuous eccentric exercise by facilitating glycogen resynthesis, reversing vascular derangements, augmenting mitochondrial function, and stimulating muscle protein synthesis.

Skeletal muscle adaptations to heat therapy.

The therapeutic effects of heat have been harnessed for centuries to treat skeletal muscle disorders and other pathologies. However, the fundamental mechanisms underlying the well-documented clinical benefits associated with heat therapy (HT) remain poorly defined. Foundational studies in cultured skeletal muscle and endothelial cells, as well as in rodents, revealed that episodic exposure to heat stress activates a number of intracellular signaling networks and promotes skeletal muscle remodeling. Renewed interest in the physiology of HT in recent years has provided greater understanding of the signals and molecular players involved in the skeletal muscle adaptations to episodic exposures to HT. It is increasingly clear that heat stress promotes signaling mechanisms involved in angiogenesis, muscle hypertrophy, mitochondrial biogenesis, and glucose metabolism through not only elevations in tissue temperature but also other perturbations, including increased intramyocellular calcium and enhanced energy turnover. The few available translational studies seem to indicate that the earlier observations in rodents also apply to human skeletal muscle. Indeed, recent findings revealed that both local and whole-body HT may promote capillary growth, enhance mitochondrial content and function, improve insulin sensitivity and attenuate disuse-induced muscle wasting. This accumulating body of work implies that HT may be a practical treatment to combat skeletal abnormalities in individuals with chronic disease who are unwilling or cannot participate in traditional exercise-training regimens.

Performing solvation free energy calculations in LAMMPS using the decoupling approach.

The decoupling approach to solvation free energy calculations requires scaling the interactions between the solute and the solution with all intramolecular interactions preserved. This paper reports a new procedure that makes it possible to these calculations in LAMMPS. The procedure is tested against built-in GROMACS capabilities. The model compounds chosen to test our methodology are ethanol and biphenyl. The LAMMPS and GROMACS results obtained are in good agreement with each other. This work should help perform solvation free energy calculations in LAMMPS and/or other molecular dynamics software having no built-in functions to implement the decoupling approach.

Water Structure and Properties at Hydrophilic and Hydrophobic Surfaces.

The properties of water on both molecular and macroscopic surfaces critically influence a wide range of physical behaviors, with applications spanning from membrane science to catalysis to protein engineering. Yet, our current understanding of water interfacing molecular and material surfaces is incomplete, in part because measurement of water structure and molecular-scale properties challenges even the most advanced experimental characterization techniques and computational approaches. This review highlights progress in the ongoing development of tools working to answer fundamental questions on the principles that govern the interactions between water and surfaces. One outstanding and critical question is what universal molecular signatures capture the hydrophobicity of different surfaces in an operationally meaningful way, since traditional macroscopic hydrophobicity measures like contact angles fail to capture even basic properties of molecular or extended surfaces with any heterogeneity at the nanometer length scale. Resolving this grand challenge will require close interactions between state-of-the-art experiments, simulations, and theory, spanning research groups and using agreed-upon model systems, to synthesize an integrated knowledge of solvation water structure, dynamics, and thermodynamics.

Effect of Acute Bouts of Volume-Matched High-Intensity Resistance Training Protocols on Blood Glucose Levels.

Monroe, JC, Naugle, KM, and Naugle, KE. Effect of acute bouts of volume-matched high-intensity resistance training protocols on blood glucose levels. J Strength Cond Res 34(2): 445-450, 2020-Resistance exercise has the capability to alter glucose metabolism in healthy adults; however, to what extent single sessions of varying intensities of resistance exercise affect capillary glucose levels is not completely understood. The purpose of this study was to compare the effect of different resistance training intensities on capillary blood glucose levels in healthy adults. Thirteen resistance-trained men (age 24.4 ± 2.7 years) participated in an evaluation and 2 separate experimental resistance training sessions. The experimental sessions were a high-intensity resistance training session (HT) consisting of 7 sets of 3 repetitions at 90% of the participant's estimated 1 repetition maximum (e1RM), and a moderate-/high-intensity resistance training session (MT) consisting of 3 sets of 9 repetitions at 70% of the participant's e1RM. At least 7 days separated the completion of each session. Four glucose readings during each session were recorded using a capillary glucometer: G1 (baseline); G2 (pre-exercise); G3 (after exercise); and G4 (10 minutes after exercise). Results were analyzed using repeated-measures analysis of variances. Analysis revealed a significant decrease in blood glucose levels between G2 and G3, and G2 and G4 in both the HT and MT experimental sessions (p = 0.045). In addition, there was a significant difference in the magnitude of change in glucose levels from G2 to G3 between HT and MT (HT = -38.2 ± 5.3% SE, p = 0.042, MT = -22.2 ± 5.9% SE). Although both of the acute resistance exercise protocols decreased blood glucose levels in healthy men, a greater decrease in blood glucose levels from pre-exercise to post-exercise was observed in HT group compared with MT group.

Best Practices for Foundations in Molecular Simulations [Article v1.0].

This document provides a starting point for approaching molecular simulations, guiding beginning practitioners to what issues they need to know about before and while starting their first simulations, and why those issues are so critical. This document makes no claims to provide an adequate introduction to the subject on its own. Instead, our goal is to help people know what issues are critical before beginning, and to provide references to good resources on those topics. We also provide a checklist of key issues to consider before and while setting up molecular simulations which may serve as a foundation for other best practices documents.

Decoding signatures of structure, bulk thermodynamics, and solvation in three-body angle distributions of rigid water models.

A tetrahedral structure resulting from hydrogen bonding is a hallmark of liquid water and plays a significant role in determining its unique thermophysical properties. This water feature has helped understand anomalous properties and physically interpret and model hydrophobic solvation thermodynamics. Tetrahedrality is well described by the geometric relationship of any central water molecule with two of its nearest neighbors in the first coordination shell, as defined by the corresponding "three-body" angle. While order parameters and even full water models have been developed using specific or average features of the three-body angle distribution, here we examine the distribution holistically, tracking its response to changes in temperature, density, and the presence of model solutes. Surprisingly, we find that the three-body distribution responds by varying primarily along a single degree of freedom, suggesting a remarkably simplified view of water structure. We characterize three-body angle distributions across temperature and density space and identify principal components of the variations with state conditions. We show that these principal components embed physical significance and trace out transitions between tetrahedral and simple-fluid-like behavior. Moreover, we find that the ways three-body angles vary within the hydration shells of model colloids of different types and sizes are nearly identical to the variations seen in bulk water across density and temperature. Importantly, through the principal directions of these variations, we find that perturbations to the hydration-water distributions well predict the thermodynamics associated with colloid solvation, in particular, the relative entropy of this process that captures indirect, solvent-mediated contributions to the hydration free energy.

Computational discovery of chemically patterned surfaces that effect unique hydration water dynamics.

The interactions of water with solid surfaces govern their apparent hydrophobicity/hydrophilicity, influenced at the molecular scale by surface coverage of chemical groups of varied nonpolar/polar character. Recently, it has become clear that the precise patterning of surface groups, and not simply average surface coverage, has a significant impact on the structure and thermodynamics of hydration layer water, and, in turn, on macroscopic interfacial properties. Here we show that patterning also controls the dynamics of hydration water, a behavior frequently thought to be leveraged by biomolecules to influence functional dynamics, but yet to be generalized. To uncover the role of surface heterogeneities, we couple a genetic algorithm to iterative molecular dynamics simulations to design the patterning of surface functional groups, at fixed coverage, to either minimize or maximize proximal water diffusivity. Optimized surface configurations reveal that clustering of hydrophilic groups increases hydration water mobility, while dispersing them decreases it, but only if hydrophilic moieties interact with water through directional, hydrogen-bonding interactions. Remarkably, we find that, across different surfaces, coverages, and patterns, both the chemical potential for inserting a methane-sized hydrophobe near the interface and, in particular, the hydration water orientational entropy serve as strong predictors for hydration water diffusivity, suggesting that these simple thermodynamic quantities encode the way surfaces control water dynamics. These results suggest a deep and intriguing connection between hydration water thermodynamics and dynamics, demonstrating that subnanometer chemical surface patterning is an important design parameter for engineering solid-water interfaces with applications spanning separations to catalysis.