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Como descobrir qual Apple Watch você tem

9 August 2026 at 19:00

O Apple Watch já está no mercado há mais de uma década. De lá para cá, a Maçã lançou inúmeras variações do smartwatch, com tamanhos, cores, materiais e coleções diferentes.

Justamente por isso, muita gente enfrenta dificuldades em identificar exatamente qual modelo de relógio possui. Felizmente, um truque muito simples permite conferir isso no iPhone ou no próprio Apple Watch.

Veja como! ⌚️

Pelo iPhone

  1. Abra o app Watch no seu smartphone.
  2. Toque em “Geral”.
  1. Selecione “Sobre” para conferir o seu modelo de relógio na seção dedicada, além do detalhe que especifica o tamanho e o material dele.

Pelo Apple Watch

  1. Abra os Ajustes (Settings) no seu relógio.
  1. Selecione “Geral”.
  2. Vá em “Sobre” para conferir a informação.

Apple Watch Ultra 3

Cores: natural ou preto
Pulseiras: loop Alpina, loop Trail, Oceano ou estilo milanês de titânio
R$ 7.850,50
R$ 10.499,00

Apple Watch Series 11

Material: alumínio ou titânio
Cores: cinza-espacial, prateado, ouro rosa, preto brilhante, natural, dourado ou ardósia
Tamanho: 42mm ou 46mm
Conectividade: GPS ou GPS + Cellular
Pulseiras: esportiva ou estilo milanês
R$ 4.198,00
R$ 5.499,00

Apple Watch SE 3

Cores: meia-noite ou estelar
Tamanhos: 40mm ou 44mm
Conectividade: GPS ou GPS + Cellular
Pulseira: esportiva
R$ 2.466,78
R$ 3.299,00

NOTA DE TRANSPARÊNCIA: O MacMagazine recebe uma pequena comissão sobre vendas concluídas por meio de links deste post, mas você, como consumidor, não paga nada mais pelos produtos/serviços usando os nossos links de afiliado.

Scientists Develop New 3D Printing Method That Can Build Directly Onto Existing Objects in Seconds

4 August 2026 at 16:54

Researchers have demonstrated an unusual new form of 3D printing capable of building entirely new structures directly onto—and even around—existing objects in just seconds. In a series of experiments, the technique printed microscopic fluid channels around embedded glass spheres, fabricated precision gears onto polished steel rods, and even built a miniature lens directly onto the surface of a working LED.

The breakthrough, described in a paper published in Nature Communications, relies on an advanced form of tomographic volumetric additive manufacturing (TVAM) that allows researchers to “overprint” new structures onto components made from a wide range of materials, including metal, glass, and preassembled microfluidic components. Instead of constructing objects layer by layer like conventional 3D printers, the system projects precisely calculated light patterns into a rotating vat of photosensitive resin, causing an entire three-dimensional object to solidify almost simultaneously within seconds.

The advancement could represent a major step toward making volumetric 3D printing practical in real-world manufacturing environments, where new components often must be integrated with parts that already exist.

It additionally highlights the growing sophistication of computational techniques that can accurately model how light behaves as it passes through materials that absorb, scatter, refract, or reflect light.

“Tomographic Volumetric Additive Manufacturing (TVAM) is a light-based 3D printing technique capable of producing centimeter-scale objects within seconds,” researchers write. “This work demonstrates a broad range of overprinting scenarios, where new structures are directly printed onto or around pre-existing components made from different materials.”

Unlike conventional stereolithography or fused-filament printers that gradually build an object from one direction, tomographic volumetric printing projects hundreds of two-dimensional light patterns into a rotating container filled with liquid resin.

As the resin accumulates enough light energy, the desired three-dimensional structure appears almost simultaneously throughout the volume rather than emerging layer by layer. The approach can produce centimeter-scale objects in mere seconds.

However, until now, one of the technology’s greatest challenges has been accurately calculating how light travels through complicated environments.

Existing objects inside the resin can block, scatter, or bend incoming light, degrading print quality. Conventional models often assume these objects are either completely transparent or completely opaque. This is an oversimplification that breaks down in realistic manufacturing scenarios.

To overcome those limitations, the team developed an upgraded computational framework called Dr.TVAM. Built upon physically based ray tracing, the software models how light propagates through materials with different optical properties while simultaneously optimizing the projected light patterns needed to create the desired object.

Because the framework accounts for reflection, refraction, scattering, absorption, and arbitrary container shapes, it can successfully print structures around components that previously would have interfered with the process.

One of the study’s most compelling demonstrations involved manufacturing microfluidic channels directly inside sealed, preassembled square chambers. Microfluidic devices contain microscopic channels that transport tiny volumes of liquids and are widely used in biomedical research, diagnostics, and organ-on-a-chip systems.

Instead of fabricating the channels separately and assembling the device afterward—a process that can introduce contamination or leaks—the researchers successfully printed perfusable channels directly inside an already assembled chamber while accounting for inlet and outlet structures that would otherwise obstruct the light.

They demonstrated straight channels, branching networks, and spiral geometries capable of carrying fluid after fabrication. Supplementary demonstrations showed colored dye successfully flowing through the finished structures.

The researchers then pushed the concept even further by creating what they describe as context-aware printing. In this experiment, they embedded two tiny glass spheres inside a hydrogel-filled chamber, rapidly determined each sphere’s three-dimensional position using two camera images, and generated customized print patterns in less than a minute.

Those optimized projections produced hollow channels connecting each sphere to inlet and outlet ports while simultaneously printing protective cavities around the spheres themselves. The complete workflow—from detecting the embedded objects to generating printing instructions and fabricating the final structure—required less than three minutes.

That ability could eventually enable highly customized biomedical manufacturing, where printers automatically adapt to the precise location of living tissues, organoids, or other biological materials rather than requiring perfect positioning beforehand.

Another experiment highlighted why precisely modeling light matters.

Previous demonstrations of volumetric overprinting treated metal components as though they completely absorbed incoming light. In reality, polished metal reflects and scatters significant amounts of light, creating distortions that reduce print quality.

Researchers tested both assumptions by printing a gear directly onto a polished steel rod. When the software ignored scattered light, the gear’s fine holes became over-polymerized and poorly defined.

After including realistic scattering behavior into the optical model, however, the resulting gear preserved those elaborate features far more accurately, increasing simulated print fidelity substantially. The improvement was confirmed experimentally.

Researchers even went as far as demonstrating that the process could print directly onto an electronic component.

Using an LED-based volumetric printing system, the researchers fabricated both a miniature lens and a small cross-shaped symbol directly onto the surface of a red LED. When illuminated, the printed lens projected the symbol onto a screen, successfully transforming the LED into a tiny optical projector without requiring additional assembly. The experiment showcased how optical elements themselves could potentially be integrated directly onto existing electronic hardware during manufacturing.

Beyond the individual demonstrations, the work additionally underscores an important trend in additive manufacturing: increasingly sophisticated software is becoming just as important as advances in hardware.

Instead of relying on simplified mathematical approximations, the new framework performs physically based optical simulations capable of modeling arbitrary geometries along with material properties.

The software has been released as open source, along with configuration files and experimental data, allowing other researchers to reproduce and expand upon the 3D printing work.

Although the current demonstrations remain laboratory-scale, the possible implications could extend well beyond experimental 3D printing. Biomedical researchers could eventually fabricate sterile microfluidic systems without multi-step assembly. Optical engineers may integrate lenses directly onto light sources. Manufacturers could add custom features to finished components without redesigning entire production processes.

Researchers also note that future improvements could further increase realism through incorporating additional physical effects, including changes in refractive index during polymerization and the diffusion of chemical inhibitors during printing. Those refinements could expand the technology’s accuracy and enable even more complex manufacturing scenarios.

“In summary, Dr.TVAM, our computational framework, has shown to be capable of modeling different optical situations for TVAM,” researchers write. “We believe this significantly expands the application space for TVAM, enabling the creation of complex, functionalized, and multi-component devices from applications in mechanics, optics, or biofabrication.”

Study: Wechsler F, et al. “Overprinting with tomographic volumetric additive manufacturing.” Nature Communications (2026).

Tim McMillan is a retired law enforcement executive, investigative reporter and co-founder of The Debrief. His writing typically focuses on defense, national security, the Intelligence Community and topics related to psychology. You can follow Tim on Twitter: @LtTimMcMillan.  Tim can be reached by email: tim@thedebrief.org or through encrypted email: LtTimMcMillan@protonmail.com 

This Color-Changing Material Could Give Robots a New Way to Detect Touch

11 July 2026 at 13:56

Engineers at Queen Mary University of London have created a tactile sensor, described in a study published in Science Advances, that allows robots to detect touch using a simple camera.  

The sensor converts mechanical forces into visible color patterns, reducing the need for dense arrays of embedded sensors. Giacomo Sasso, a postdoctoral researcher at Queen Mary’s School of Engineering and Materials Science, led the team that developed this new sensor. Rather than relying on embedded electronic sensors, they created a soft material that changes color when pressed or bent.

This effect, known as structural color, is the same reason butterfly wings look iridescent without pigment. Pressure causes microscopic structures within the material to shift, altering how light reflects and creating a real-time visual indicator of force.

Touch Without the Computation

Most vision-based tactile sensors can map contact and force in detail, but only at the cost of heavy computation that slows them down. Simpler systems are faster, but sacrifice detail. The new material developed by Sasso’s team sidesteps this problem by building the sensing function into the material itself. With just a standard USB camera, researchers can track color changes on the surface and immediately infer pressure, strain, and contact shape without complex data reconstruction.

“You won’t guess how much information is generated when your finger presses a light switch. A human hand contains more than 10,000 mechanoreceptors to do the job, yet touch sensing remains one of the major challenges in robotics,” Sasso said. “We were happy to capture the finger ridges, as no existing technology can reproduce such sensor density at [a] comparable scale and simplicity. The key idea behind this project was to think outside the box: instead of embedding dense and overengineered sensor arrays, sensing is moved into the material itself, where mechanical cues are directly transformed into colour fields and captured using a simple low-cost USB camera.”

Professor James Busfield, one of the paper’s co-authors, described the advantage more simply: “What is particularly powerful is that the information is already in the light signal. You are no longer reconstructing touch – you are observing it directly.”

From Precision Manufacturing to the Operating Room

Reducing the computational demands of touch sensing opens up new possibilities. A robotic gripper made with this material could handle tiny parts more gently, since changes in force are immediately detectable. Prosthetic limbs equipped with similar sensors could also provide users with more detailed tactile feedback.

The researchers also see potential applications in surgery, where detecting subtle pressure differences could help clinicians interpret tissue properties.

A Decade of Groundwork Behind One Material

Professor Federico Carpi from the University of Florence and Professor James Busfield from Queen Mary worked together on this project, merging years of separate work on stretchable sensors and polymer behavior into one material system. This allowed the team to use a mechanochromic material as the sensor itself, not just as a base for electronics.

Many approaches to robotic touch have relied on increasingly complex sensor arrays, wiring, and computing systems. Rather than adding more electronics, Sasso’s team’s approach allows the material itself to encode touch into visible color. It remains unclear whether this color-based method can be scaled for use in commercial robotic hands, but this work suggests that the future of robotic touch might rely as much on smart materials as on advanced electronics.

Austin Burgess is a writer and researcher with a background in sales, marketing, and data analytics. He holds an MBA, a Bachelor of Science in Business Administration, and a data analytics certification. His work focuses on breaking scientific developments, with an emphasis on emerging biology, cognitive neuroscience, and archaeological discoveries.

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