Photoelectrochemical water splitting is a promising route for the renewable production of hydrogen fuel. This work presents the results of a technical and economic feasibility analysis conducted for four hypothetical, centralized, large-scale hydrogen production plants based on this technology. The four reactor types considered were a single bed particle suspension system, a dual bed particle suspension system, a fixed panel array, and a tracking concentrator array. The current performance of semiconductor absorbers and electrocatalysts were considered to compute reasonable solar-tohydrogen conversion efficiencies for each of the four systems. The U.S. Department of Energy H2A model was employed to calculate the levelized cost of hydrogen output at the plant gate at 300 psi for a 10 tonne per day production scale. All capital expenditures and operating costs for the reactors and auxiliaries (compressors, control systems, etc.) were considered. The final cost varied from $1.60-$10.40 per kg H 2 with the particle bed systems having lower costs than the panel-based systems. However, safety concerns due to the cogeneration of O 2 and H 2 in a single bed system and long molecular transport lengths in the dual bed system lead to greater uncertainty in their operation. A sensitivity analysis revealed that improvement in the solar-to-hydrogen efficiency of the panel-based systems could substantially drive down their costs. A key finding is that the production costs are consistent with the Department of Energy's targeted threshold cost of $2.00-$4.00 per kg H 2 for dispensed hydrogen, demonstrating that photoelectrochemical water splitting could be a viable route for hydrogen production in the future if material performance targets can be met. Broader contextAs global energy consumption continues to rise, it is imperative that we develop renewable alternatives to the fossil fuel energy sources that currently power our civilization, curb CO 2 emissions, and secure a permanent energy supply for the future. Although the solutions to these global challenges are likely to consist of many different energy storage and conversion technologies, sustainably produced chemical fuels will likely play an important role due to their high energy density. Hydrogen gas is an especially promising energy carrier, but current hydrogen production processes such as steam methane reforming are unsustainable. Photoelectrochemical (PEC) water splitting is an alternative process that enables sustainable hydrogen production from water using the energy from sunlight. PEC water splitting has been demonstrated on the laboratory scale, but it has never been implemented on a large scale relevant to the global energy demand, so the prospects for scaling up this process have remained controversial. The present paper addresses the technical and economic feasibility of plants producing hydrogen via PEC water splitting. We establish practical operating efficiencies for PEC reactors, detail four potential reactor and centralized plant designs, and discuss the...

Photoelectrochemical (PEC) water splitting for hydrogen production is a promising technology that uses sunlight and water to produce renewable hydrogen with oxygen as a by-product. In the expanding field of PEC hydrogen production, the use of standardized

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Several application fields can benefit from solar-hydrogen technologies via specific short-term and long-term pathways.

Photoelectrochemical solar-to-hydrogen conversion efficiencies as high as 7.8% (based on the lower heating value of hydrogen) have been demonstrated in outdoor testing using a photocathode fabricated from triple junction amorphous silicon-solar cells and a separate catalytic anode. The tests were conducted in a specially designed Teflon-sealed reactor in 1 N KOH with a photoactive area of 0.27 cm2 and anode and cathode areas of 1 cm2. The hydrogen production rates, inferred from direct measurement of the anodic/cathodic currents and confirmed by independent volumetric and gas chromatographic measurements of the evolved hydrogen, were in excellent agreement with the rates expected from the measured solid-state JV behavior of the solar cell and the overpotentials of the thin-film catalysts. The thin-film catalysts, CoMo hydrogen catalysts deposited by sputtering from a compound target and NiFe y O x oxygen catalysts deposited from nickel−iron Permalloy target by reactive sputtering, have, in separate tests, shown no degradation after over 7200 h of operation in 1 N KOH electrolyte. During outdoor testing, the solar-to-hydrogen conversion efficiency decreased in the late afternoon as the blue portion of the spectrum decreased, a result of the spectral sensitivity of the solar cell used to construct the photoelectrode. Detailed modeling of the multijunction amorphous silicon cells is being conducted to identify structures that are better load-matched to the catalyst performance and that could yield higher hydrogen production efficiencies. Future work to advance this technology includes development of improved thin-film catalysts and development of transparent protective coatings that will allow complete immersion of the active electrode into the electrolyte.

The development of energy selective, photon counting X-ray detectors allows for a wide range of new possibilities in the area of computed tomographic image formation. Under the assumption of perfect energy resolution, here we propose a tensor-based iterative algorithm that simultaneously reconstructs the X-ray attenuation distribution for each energy. We use a multi-linear image model rather than a more standard "stacked vector" representation in order to develop novel tensor-based regularizers. Specifically, we model the multi-spectral unknown as a 3-way tensor where the first two dimensions are space and the 3 rd dimension is energy. This approach allows for the design of tensor nuclear norm regularizers, which like its two dimensional counterpart, is a convex function of the multi-spectral unknown. The solution to the resulting convex optimization problem is obtained using an alternating direction method of multipliers (ADMM) approach. Simulation results shows that the generalized tensor nuclear norm can be used as a stand alone regularization technique for the energy selective (spectral) computed tomography (CT) problem and when combined with total variation regularization it enhances the regularization capabilities especially at low energy images where the effects of noise are most prominent.

Despite their importance for humans, there is little consensus on the function of antibiotics in nature for the bacteria that produce them. Classical explanations suggest that bacteria use antibiotics as weapons to kill or inhibit competitors, whereas a recent alternative hypothesis states that antibiotics are signals that coordinate cooperative social interactions between coexisting bacteria. Here we distinguish these hypotheses in the prolific antibiotic-producing genus Streptomyces and provide strong evidence that antibiotics are weapons whose expression is significantly influenced by social and competitive interactions between competing strains. We show that cells induce facultative responses to cues produced by competitors by (i) increasing their own antibiotic production, thereby decreasing costs associated with constitutive synthesis of these expensive products, and (ii) by suppressing antibiotic production in competitors, thereby reducing direct threats to themselves. These results thus show that although antibiotic production is profoundly social, it is emphatically not cooperative. Using computer simulations, we next show that these facultative strategies can facilitate the maintenance of biodiversity in a community context by converting lethal interactions between neighboring colonies to neutral interactions where neither strain excludes the other. Thus, just as bacteriocins can lead to increased diversity via rock-paper-scissors dynamics, so too can antibiotics via elicitation and suppression. Our results reveal that social interactions are crucial for understanding antibiosis and bacterial community dynamics, and highlight the potential of interbacterial interactions for novel drug discovery by eliciting pathways that mediate interference competition.

Cavitation-facilitated microbubble-mediated focused ultrasound therapy is a promising method of drug delivery across the blood-brain barrier (BBB) for treating many neurological disorders. Unlike ultrasound thermal therapies, during which magnetic resonance thermometry can serve as a reliable treatment control modality, real-time control of modulated BBB disruption with undetectable vascular damage remains a challenge. Here a closedloop cavitation controlling paradigm that sustains stable cavitation while suppressing inertial cavitation behavior was designed and validated using a dual-transducer system operating at the clinically relevant ultrasound frequency of 274.3 kHz. Tests in the normal brain and in the F98 glioma model in vivo demonstrated that this controller enables reliable and damage-free delivery of a predetermined amount of the chemotherapeutic drug (liposomal doxorubicin) into the brain. The maximum concentration level of delivered doxorubicin exceeded levels previously shown (using uncontrolled sonication) to induce tumor regression and improve survival in rat glioma. These results confirmed the ability of the controller to modulate the drug delivery dosage within a therapeutically effective range, while improving safety control. It can be readily implemented clinically and potentially applied to other cavitation-enhanced ultrasound therapies.drug delivery | focused ultrasound | acoustic cavitation | treatment control | blood-brain barrier