More than 15 million people worldwide are living with spinal cord injury (SCI), which can affect their sensory and motor functions below the injury level. For individuals with SCI between C5 and C7 cervical levels, this can mean paralysis affecting their limbs and limited voluntary finger and wrist flexion, making it difficult to grasp large, heavy objects.
Now, a team of UC Berkeley engineers from the Embodied Dexterity Group has developed a wearable device to enhance grasping functionality in this population. Dubbed the Dorsal Grasper, this assistive device leverages voluntary wrist extension and uses supernumerary robotic fingers on the back of the hand to facilitate human-robot collaborative grasping.
In a study recently featured in IEEE Transactions on Neural Systems and Rehabilitation Engineering, the researchers demonstrated for the first time how the Dorsal Grasper can expand users’ graspable workspace. Test subjects found that they could easily grasp objects anywhere they could reach their arm, without having to rotate their bodies, which can cause wheelchair users to lose their balance.
A game of chess requires its players to think several moves ahead, a skill that computer programs have mastered over the years. Back in 1996, an IBM supercomputer famously beat the then world chess champion Garry Kasparov. Later, in 2017, an artificial intelligence (AI) program developed by Google DeepMind, called AlphaZero, triumphed over the best computerized chess engines of the time after training itself to play the game in a matter of hours.
More recently, some mathematicians have begun to actively pursue the question of whether AI programs can also help in cracking some of the world’s toughest math problems. But, whereas an average game of chess lasts about 30 to 40 moves, these research-level math problems require solutions that take a million or more steps, or moves.
In a paper appearing on the arXiv preprint server, a team led by Caltech’s Sergei Gukov, the John D. MacArthur Professor of Theoretical Physics and Mathematics, describes developing a new type of machine-learning algorithm that can solve math problems requiring extremely long sequences of steps. The team used their new algorithm to solve families of problems related to an overarching decades-old math problem called the Andrews–Curtis conjecture. In essence, the algorithm can think farther ahead than even advanced programs like AlphaZero.
Combining concepts from statistical physics with machine learning, researchers at the University of Bayreuth have shown that highly accurate and efficient predictions can now be made as to whether a substance will be liquid or gaseous under given conditions. They have published their findings in Physical Review X.
Observation of a glass of water reveals that the water exists in two distinct phases: liquid and gas. Even at room temperature, water molecules are constantly evaporating from the surface of the liquid water and passing into the gas phase. At the same time, some of the water molecules from the gas condense back into the liquid.
The transition from one phase to the other depends on temperature and pressure. Above a critical temperature, the simultaneous coexistence of gas and liquid disappears. The resulting supercritical fluid no longer forms an interface. This is important for industrial processes such as separation, cleaning and production.
The Department of Energy is investing in next-gen microelectronics to curb skyrocketing energy demands. SLAC and other top institutions are developing innovative materials, AI-powered sensing, and brain-inspired computing to push efficiency to new levels. Powering the Future: The Energy Demand o.
Soft actuators produce the mechanical force needed for the functional movements of soft robots, but they suffer from critical drawbacks since previously reported soft actuators often rely on electrical wires or pneumatic tubes for the power supply, which would limit the potential usage of soft robots in various practical applications. In this article, we review the new types of untethered soft actuators that represent breakthroughs and discuss the future perspective of soft actuators. We discuss the functional materials and innovative strategies that gave rise to untethered soft actuators and deliver our perspective on challenges and opportunities for future-generation soft actuators.
For pneumatic actuators, the pneumatic pumps serve an essential role in generating a mechanical force by using compressed gas or moving the liquid for the rapid fluid pressure increase. Yet, the incorporation of the pneumatic pump into the soft robotics would impair the mobility and the core functionalities of the soft robots because the pumps are usually relatively bulky and heavy when compared to the soft robots themselves. To address this issue, several recent studies demonstrated pump-less pneumatic actuation by employing the phase change materials that generate the volume change as the materials switch between liquid and gaseous states, thus resulting in the inflation and deflation of actuators. Here, the pump-less pneumatic actuators can be defined as the soft actuators that do not use the actual pump but generate a pneumatic force by the phase change of material just as if utilizing the pneumatic pump. In other words, the pump-less pneumatic actuators just reproduce the end effect of the pump by a different working mechanism without using the actual pump. The absence of the pneumatic pump in the robotic design also eliminates the need for pneumatic tubes to infuse/extract air into/from the actuator, thereby making the design completely untethered.
Likewise, external stimuli can deliver a considerable amount of mechanical displacement and force needed to actuate the soft robots in an untethered manner: the external stimuli in this article include magnetic field, heat, electricity, light, and humidity. Hence, without physically connecting the electrical tethering to the soft actuators to provide the power source, the external stimuli can enable the soft actuator to produce mechanical displacement since the materials are designed to actuate as programmed. As opposed to the pneumatics-based soft actuators that require the onboard power source (such as a battery or self-powering energy harvesting devices) to supply power to induce pneumatic force, some of these actuators receive the power to induce mechanical displacement in a completely untethered fashion. For example, systematic manipulation of a magnetic field can control the movement of the magnet-driven soft actuator as intended without any type of wiring. Similarly, if the antennas are incorporated into the soft robotic system, electromagnetic waves can be utilized to provide power wirelessly to operate the soft actuators5,6,7,8, or it also enables the remote control of the actuators via wireless communication9,10 Therefore, external stimuli-driven soft actuators retain the potential to represent the breakthrough in the field of soft robotics although there exist considerable limitations to be resolved. In this light, it would be a highly valuable resource to introduce untethered soft actuators and discuss the future perspective of new types of soft robots. There are a considerable number of review articles on soft actuators and robotics11,12,13,14,15. However, no review paper has dealt with recent advances in untethered soft actuators for soft robotics that demonstrated meaningful outcomes within a few years. Recently, roboticists and researchers proposed an explosive number of soft actuators for soft robots based on innovative structural designs and functional materials that represent breakthroughs in the field of soft robotics. Furthermore, as the field of soft actuators is relatively new and drawing a substantial amount of interest in the related fields, there exists a demand for an article that systematically reviews the current trend and informs the opportunities to contribute to the field. In this regard, we believe that the timely and thorough review of the recent advances in untethered soft actuators will be informative for the general readers who wish to draw insights and gain potential perspectives in the field.
In this article, we introduce the representative works of the untethered soft actuators that serve as breakthroughs in soft robotics and further discuss the imminent challenges of the soft actuators to be addressed. Soft actuators can also be applied to rigid robots since the actuators reviewed in this paper operate in an untethered configuration. However, we intentionally circumscribed the scope and focused mainly on soft actuators for soft robots because the incorporation of soft actuators into the soft robot can make the entire robot soft and compliant. There exist specific applications where the soft robots exhibit comparative strengths over rigid robots such as navigating through the tortuous space16,17, exploring deep-sea at extremely high pressure18, or minimally invasive surgery19. Furthermore, to present these works systematically, the paper categorizes the soft actuators by four representative working mechanisms (1. pneumatically/hydraulically-driven, 2. magnetically-driven, 3. heat-driven, and 4. electrically-driven) and further examines each actuating mechanism in relation to the untethered soft robots as illustrated in Fig. 1. The paper examines the strengths and limitations of each actuating method and concludes with the future perspective of untethered soft actuators for soft robotics. Box 1 provides the general summary that addresses the strategies to provide the power source for actuation control of the soft robots. Additionally, Table 1 draws the overall comparison of each soft actuating method to highlight the strengths, weaknesses, and other key features such as response time and output force range. On the other hand, Table 2 captures key highlights of representative soft actuators that operate based on a variety of mechanisms and thus delivers a more specific comparison.
Rigid, lizard-like tails are simple, but mammal-style tails may be lighter and better for space. Researchers studied how tails aid midair maneuverability in animals and robots, focusing on inertial appendages that generate body rotation.
Inspired by lizards and geckos, roboticists have designed rigid, single-plane tails to enhance stability and control in aerial and terrestrial robots. Some robotic tails aid in landing, flight reorientation, and high-speed turns. However, vertebrate (like cats and squirrels) tails are more complex, consisting of multiple vertebrae that allow for diverse movements.
By analyzing mammalian tails, researchers found that increasing bone segments within the same length enhances rotational ability. To evaluate tail effectiveness, they developed simulations optimizing tail trajectories for precise body rotations. Unlike previous models that assumed rigid structures, their approach considers deformability and realistic control constraints.
A joint research team has developed an innovative quantum-classical computing approach to design photochromic materials—light-sensitive compounds—offering a powerful tool to accelerate material discovery. Their findings were published in Intelligent Computing.
Building on their previous work in the same journal, the researchers introduced a computational-basis variational quantum deflation method as the foundation of their approach.
To validate its effectiveness, the team conducted a case study in photopharmacology, screening 4,096 diarylethene derivatives. They identified five promising candidates that exhibited two critical properties: large maximum absorbance wavelengths and high oscillator strengths. These characteristics are crucial for applications such as light-controlled drug delivery in photopharmacology.
Nanoparticle researchers spend most of their time on one thing: counting and measuring nanoparticles. Each step of the way, they have to check their results. They usually do this by analyzing microscopic images of hundreds of nanoparticles packed tightly together. Counting and measuring them takes a long time, but this work is essential for completing the statistical analyses required for conducting the next, suitably optimized nanoparticle synthesis.
Alexander Wittemann is a professor of colloid chemistry at the University of Konstanz. He and his team repeat this process every day. “When I worked on my doctoral thesis, we used a large particle counting machine for these measurements. It was like a cash register, and, at the time, I was really happy when I could measure three hundred nanoparticles a day,” Wittemann remembers.
However, reliable statistics require thousands of measurements for each sample. Today, the increased use of computer technology means the process can move much more rapidly. At the same time, the automated methods are very prone to errors, and many measurements still need to be conducted, or at least double-checked, by the researchers themselves.
AI, Deep Dive, spacetime inertia, unified energy framework, gravity, dark matter, dark energy, black holes, emergent gravity, energy inertia, mass-energy interactions, missing mass problem, cosmic expansion, event horizon mechanics, Einstein’s General Relativity, spacetime curvature, galactic rotation curves, quantum field theory, spacetime as energy, energy resistance, inertial effects, graviton alternative, energy density distribution, inverse-square law, gravitational lensing, galactic halos, high-energy cosmic regions, X-ray emissions, electromagnetic fields, cosmological constant, accelerating universe, large-scale inertia, spacetime resistance, event horizon physics, singularity alternatives, James Webb Space Telescope, early galaxy formation, modified gravity, inertia-driven cosmic expansion, energy saturation point, observational cosmology, new physics, alternative gravity models, astrophysical testing, theoretical physics, unification of forces, experimental validation, fundamental physics revolution, black hole structure, cosmic energy fields, energy gradient effects, resistance in spacetime, extreme energy zones, black hole event horizons, quantum gravity, astrophysical predictions, future space observations, high-energy astrophysics, cosmic structure formation, inertia-based galaxy evolution, spacetime fluid dynamics, reinterpreting physics, mass-energy equivalence.
Description: In this deep dive into the nature of gravity, dark matter, and dark energy, we explore a groundbreaking hypothesis that could revolutionize our understanding of the universe. What if gravity is not a fundamental force but an emergent property of spacetime inertia? This novel framework, proposed by Dave Champagne, reinterprets the role of energy and inertia within the fabric of the cosmos, suggesting that mass-energy interactions alone can account for gravitational effects—eliminating the need for exotic matter or hypothetical dark energy forces.
We begin by examining the historical context of gravity, from Newton’s classical mechanics to Einstein’s General Relativity. While these theories describe gravitational effects with incredible accuracy, they still leave major mysteries unsolved, such as the unexplained motions of galaxies and the accelerating expansion of the universe. Traditionally, these anomalies have been attributed to dark matter and dark energy—hypothetical substances that have yet to be directly observed. But what if there’s another explanation?
By treating spacetime itself as an energy field with intrinsic inertia, we propose that gravitational effects arise naturally from the resistance of this energy to changes in motion. Just as mass resists acceleration due to inertia, energy may also exhibit resistance at cosmic scales, leading to effects that mimic gravity, dark matter, and dark energy. This perspective offers a fresh way to interpret the missing mass problem, suggesting that the high-energy environments surrounding galaxies create inertia effects that explain their rotational speeds—without requiring an invisible mass component.
We explore how this framework extends to cosmic expansion. Instead of postulating an unknown repulsive force (dark energy), spacetime inertia may drive the acceleration of the universe as a natural consequence of energy distribution at vast scales. Could this be an alternative to Einstein’s cosmological constant? We analyze how large-scale resistance effects could account for the observations of an accelerating cosmos.
